Glossary

Account whitelisting in AML is the process of creating a list of customers, businesses, governments, or other entities that a financial institution or business considers safe, verified, and trusted.

Customized account whitelists help organizations become more resource-efficient by focusing on high-risk entities while reducing checks on customers who have previously been verified and pose no threat of financial crime.

By integrating a customized account safelist in the business rules for transaction screening and monitoring, organizations can reduce the number of false positives and generate more accurate alerts.

With Siron®One, you can gain time and efficiency by including a customized account allowlist of individuals or entities that have demonstrated compliance over the years or have low transaction monitoring thresholds for expedited or simplified due diligence.

Autorité de Contrôle Prudentiel et de Résolution (ACPR) is France’s prudential supervisory and resolution authority associated with Banque de France (the French central bank). The ACPR issues various guidelines and regulations to ensure the stability and integrity of the financial sector.

ACPR is responsible for prudential supervision of banks, credit institutions, financial conglomerates, and insurance companies, AML/CTF and regulatory oversight, consumer protection, and financial stability, including resolution of failing institutions to prevent disruption of the financial system.

Adverse media screening or negative news screening is integral to customer due diligence. In this process, customers are screened against negative news sources to identify problematic client relationships and safeguard the company’s reputation.

Together with other compliance use cases, such as perpetual KYC and real-time transaction sanctions screening and monitoring, Siron®One utilizes AI-based adverse media screening to generate a dynamic customer risk profile that provides more contextual information for easier decision-making.

Siron®One uses Natural Language Processing and Generative AI in Adverse Media screening to sift through voluminous amounts of data, including fake news. It generates a summary of searched content and saves manual effort.

AI Blackbox refers to a phenomenon where the inner workings of an AI model are unknown. A machine learning or deep learning system can be trained on data and provide outputs, but users have no clarity on how the AI came to that conclusion (whether correct or not).

ML essentially has three components: the algorithm, which is a set of rules and procedures; the training data through which it learns to identify patterns; and the ML model, which is what people use after the AI has been trained on the data. Any of these components could be hidden and create a “black box.”

It’s impossible to account for all permutations in training data or neural networks, and hence, difficult to reverse engineer an explainable AI. Thus, having humans in the loop is critical in high-risk areas where an unexplainable output can lead to harm, such as financial or social justice. Nevertheless, Siron®One offers several “Explainable AIs”, where we’ll show reason codes that help you understand why a specific score was high/low.

AI Ethics is concerned with strengthening the beneficial use of AI while mitigating potential adverse outcomes. Ethical AI is explainable, fair, and trustworthy, and it’s trained on data that is free of biases and discrimination.

AI ethics is a multidimensional field that covers everything from the true cost of innovation, sustainability, and inclusivity to morality, beneficence, and justice.

Companies building and using AI must reconcile AI’s role in job loss, technological singularity or superiority, and data privacy and intellectual rights. While adopting AI is becoming mandatory, doing so responsibly is fundamental.

Often, alerts generated by AML software for suspicious activity pose no risk and lead to bottlenecks. Compliance officers review these alerts manually to determine if they are false positives or genuine risks that require filing a suspicious activity report (SAR).

Alert hibernation adds another layer to this binary approach by “hibernating” an alert for future review based on customer risk profiles and risk thresholds. The hibernated alert remains open, and when the same customer generates alerts in the future that cross the risk threshold, the compliance officer acts on the alert.

Siron®One uses ML and predictive analytics for auto-alert hibernation. Customers are assigned a risk score during onboarding and are segmented into clusters. Alerts are auto hibernated when the activity falls within risk thresholds. When the deviation score surpasses a pre-determined risk score, it generates higher-risk alerts, thus reducing the number of alerts that compliance officers need to focus on.

Siron®One machine learning model uses Generative AI to understand your alerts. Based on past alert data, the machine learning model can score future alerts based on their potential importance, allowing you to focus on higher-priority alerts first.

ML-based alert prediction scores help users sort through alerts quicker and focus on tasks that require immediate attention, ensuring that all alerts are handled in a timely manner.

Siron®One scores each alert it generates based on its urgency and the probability that it requires investigation and filing a suspicious activity report.

Alert prediction scores help users make timely decisions, mitigate risks, and reduce investigative efforts. Advanced machine learning and predictive analytics in Siron®OneAlert Prediction Score increase accuracy and reduce false positives, identify patterns in emerging criminal activities, and keep businesses compliant.

Compliance and AML software generates alerts based on triggering events that deviate from pre-set business rules to notify of suspicious activities. Managing the alert queue is critical in responding to suspicious transactions timely, without being inundated or distracted by low or no risk or even false alerts.

Effective alert queue management requires rules on how to assess, prioritize, respond to, and resolve alerts so that compliance managers can focus on critical alerts, act timely, and minimize vulnerabilities without straining their resources.

Siron®One alert queue management combines a powerful rules engine with AI to score and prioritize alerts based on risk levels. This hybrid approach reduces false positives and negatives, leading to more accurate alerts and allowing you to dedicate time to urgent and high-risk alerts in real-time. Based on defined business rules, Siron®One can also auto-resolve or hibernate alerts, helping manage the alert queue more effectively.

Algorithms are procedures a program follows to execute an operation or render a calculation. Although essentially the same, AI algorithms are infinitely more complex and tell the AI how to learn and operate independently. An AI algorithm uses training data to learn and execute tasks. Hence, a clean and robust dataset is crucial to a well-performing AI model.

There are three types of AI algorithms depending on whether the training data is labeled or unlabeled. Supervised learning uses labeled data for training, and these algorithms are used in classification and regression problems.

Unsupervised learning uses unlabeled data to identify patterns, correlations, and clusters in datasets. Siron®One customer clustering and deviations use unsupervised and semi-supervised AI algorithms.

Reinforcement learning works by providing positive or negative feedback and adjusting the AI’s output or action to maximize the positive feedback. This kind of algorithm is used in autonomous vehicles and robotics.

Anti-money laundering (AML) regulations, laws, and risk management efforts are crafted to prevent money laundering.

The process of money laundering consists of three stages:
– Placement, whereby the “dirty” money is placed into the financial system.
– Layering, which are methods that obscure the source of funds.
– Integration is when “clean” money is withdrawn from the financial system.

Some of the most important acts and organizations for AML include the Bank Secrecy Act (BSA), the Financial Crimes Enforcement Network (FinCEN), the Financial Action Task Force (FATF), and the International Monetary Fund (IMF).

For financial institutions, following AML compliance involves extensive processes, from KYC customer due diligence to filing reports such as Suspicious Activity Report (SAR) and Currency Transaction Report (CTF). By utilizing an AI-based RegTech compliance platform like Siron One, you can automate resource- and data-intensive tasks and achieve a high level of accuracy with AML processes like transaction sanctions and monitoring.

To fight money laundering and counter terrorist financing, the European Commision conducts risk assessments and constructs AML legislation. The first Anti Money Laundering Directive was adopted in the EU in 1990. Since then, AMLD has become essential to regulatory compliance.

AMLD focuses on building traceability of financial information to maintain the integrity of the financial system and ensure global financial security. AMLD also applies to digital assets and crowdfunding.

A critical part of AMLD compliance is conducting customer due diligence during onboarding, monitoring all transactions, and reporting suspicious activity.

The European Commission periodically reviews the AMLD standards to address changes in the financial system, such as including regulation on the Traceability of Transfers of Funds (TFR) to ensure the traceability of cryptocurrency.

Siron®One helps financial institutions keep up with the changing regulations under AMLD and remain compliant in the jurisdiction of operations.

A company’s AML policies include a framework for risk appetite and tolerance, the definition of high-risk and unacceptable customer types, prohibited actions, employee responsibilities and rights, and more.

These measures help companies follow the regulations set by AML policymakers worldwide, such as the Financial Action Task Force (FATF), Financial Industry Regulatory Authority (FINRA), the European Commission’s AML Directive, Germany’s Federal Financial Supervisory Authority (BaFin), Canada’s Financial Transactions and Reports Analysis Centre of Canada (FINTRAC), Singapore’s Monetary Authority of Singapore (MAS), and others.

AML programs always include KYC customer due diligence, checking sanctions, watchlists, and politically exposed people (PEP) lists, monitoring transactions and reporting suspicious activities, training employees, and sharing relevant information with regulators.

As money laundering is becoming more complex, businesses need to keep improving their AML policies to stay ahead of new kinds of criminal activities, such as with AI- and ML-based compliance platforms like Siron®One.

An Application Programming Interface (API) is a middle layer between two different applications that makes it possible to securely access data or a feature from one software (client) to another (server) so that disparate apps can work together to execute a task. Through APIs, software or a platform can add to its capabilities and feature set to serve the user seamlessly.

Siron®One Compliance Platform can connect to any third-party software through public (open) or private APIs, including CRMs, enhancing its capabilities and better serving the customer.

An audit log records all the information related to user activities, including who accessed a company’s IT system, what information they looked at and what actions they took. Audit logs are essential in compliance as a source of evidence of activity in forensic investigations and in pinpointing suspicious behavior. These records are key in creating an audit trail.

An audit trail is a date—and time-stamped verifiable record of all details pertaining to a transaction. It provides the validity of an action, the integrity of the checks and controls in place, and valuable evidence in financial crime investigations.

A chronological and airtight audit trail helps investigators detect fraud and data breaches while maintaining compliance in financial reporting.

Auditing in compliance is a comprehensive review of an institution’s regulatory compliance posture, security policies, risk management measures, and user access controls.

A company can conduct periodic internal audits throughout the year and, depending on its business, be subjected to external auditing. Credit card companies, for instance, must follow the Payment Card Industry Data Security Standard (PCI DSS) standards for auditing.

Regulators use audit reports to assess noncompliance and whether any fines will be levied.

Autorité des Marchés Financiers (AMF) is the Financial Markets Authority in France responsible for increasing financial transparency, fighting money laundering and terror funding, and safeguarding investments. AMF sets the rules for compliance and implements directives like the EU’s MiFID II within France.

AMF oversees financial institutions, including brokers, private wealth managers, and digital asset issuers. Under the Climate and Sustainable Finance Commission (CSFC), it promotes socially responsible investing (SRI) and oversees ESG-related financial instruments to prevent greenwashing.

Backtesting in predictive analytics is a way to test whether a machine learning model can make predictions that align with historical or realized data. It’s a way to test the performance and effectiveness of an ML model before using it in production.
Compliance software that uses AI and ML needs to conduct back-testing to verify the accuracy of the output. In the first phase of deployment, Siron®One uses real-world data to prove the validity of the ML model within the business context, and in the second phase, the ML model is retrained to always provide accurate results.

The Bundesanstalt für Finanzdienstleistungsaufsicht (BaFin), or the Federal Financial Supervisory Authority, is Germany’s integrated financial regulatory authority. An autonomous federal institution, BaFin oversees the entire German financial market, including banks, insurance companies, financial services institutions, and securities trading.

BaFin’s roles include banking, insurance, securities supervision, AML/CTF, financial stability, and crisis management.

Some BaFin guidelines include Minimum Requirements for Risk Management (MaRisk), Minimum Requirements for Compliance (MaComp), the German Banking Act (Kreditwesengesetz, KWG), the Securities Trading Act (Wertpapierhandelsgesetz, WpHG), the Solvency II Directive, and the German Money Laundering Act (Geldwäschegesetz, GwG).

Bank Secrecy Act (BSA) or BSA/AML is a set of regulations geared towards preventing money laundering and financing terrorism. BSA/AML aims to make financial processes transparent and detect and prevent transactions related to fraud, money laundering, and financing terrorism. All financial institutions are required to implement a BSA/AML program that complies with the BSA regulations and maintains traceable records for auditing.

BSA authorizes the US Department of Treasury to hold financial institutions responsible for following BSA/AML regulations, including regulatory reporting and recordkeeping.

Batch processing is a method where data is collected over a specific time and processed simultaneously. It is generally executed for large volumes of data during off-peak hours to optimize system resources and increase throughput. This method is ideal for transactions that don’t require real-time processing.

Depending on operational requirements, Siron®One lets you process transaction data in real-time or in batches. For instance, credit card payments require real-time processing whereas insurance payments are more suitable for batch processing.

For other processes, such as risk calculations for customers, accounts or client groups, Siron®One also runs batches at night, although you could trigger processing ad hoc.

Batch screening in compliance is checking a large list of records against sanctions, embargoes, PEPs, and adverse media databases to mitigate and score the risk of a client relationship. Screening a large amount of data in one batch instead of searching for an entity one by one saves time and resources.

Siron®Oneautomates the batch screening process and usually reserves it for off-peak hours to better manage workload and system resources.

Behavioral analytics combines data analytics with AI/ML to detect patterns, trends, deviations, and anomalies in an entity or customer data. It’s also known as user and entity behavior analytics (UEBA) and has become a meaningful way to reveal customer insights across different industries, including compliance and cybersecurity.

In compliance, unsupervised machine learning algorithms are used in behavioral analytics for customer segmentation and clustering, which predict the habits and behavior of a group of customers based on past data. Siron®One tracks and measures the deviations in customer behaviors from their cluster to generate dynamic risk scores and alerts.

ML-based behavioral clustering is when a machine learning model categorizes data into subgroups based on the group’s similarities and behavioral patterns.

It is utilized in identifying patterns in unsupervised learning algorithms, particularly when the matches don’t need to be exact. The primary goal is to find how closely an element is related to a group and store information in a way that can be searched and identified quickly.

The closeness function, similarity metric, or distance measure in ML clustering shows close two entities are. Measuring this deviation is critical in AI-based compliance to understand whether an entity is behaving differently from its cluster or group and whether it warrants an investigation.

Siron®One uses ML-based behavioral clustering and deviation scores, among other metrics, to generate alerts when an individual or entity’s behavior changes from its cluster and baseline information.

In general, a blacklist is a record of entities that are denied access to systems or assets. In AML compliance, a blacklist refers to countries that the Financial Action Task Force (FATF) finds are not implementing rigorous anti-financial crime measures.

Blacklisted countries are considered high-risk because they don’t have financial crime-fighting systems or the existing systems are well below the FATF’s standards, and the countries are not planning on improving in the future.

In contrast, greylist refers to those geographies under FATF supervision that may have low standards in financial crime fighting but are implementing improved systems.

Checking entities against the FATF blacklist is integral to AML compliance, customer due diligence, and risk scoring. Since FATF updates its backlist thrice a year, compliance officers must check the blacklist and greylist every quarter or use a compliance platform that has an automatic blacklist checker like Siron®One.

Blockchain is a way of recording information in a distributed ledger shared across a network. The data is recorded in a block and is impossible to alter, making the digital ledger immutable. Blockchain transactions are entirely transparent. Hence, distributed ledgers have gained popularity for applications like sending money or keeping an irrefutable record of sensitive information.

Information is transmitted through peer-to-peer nodes (such as a computer). Who has access to the blockchain depends on the type of network. There are four main types of blockchains based on networks: public, private, consortium or federated, and hybrid.

One blockchain application is a smart contract, which uses logic to automate workflow, such as automatically paying an invoice once there’s proof of goods delivered.

While blockchain creates trust (or does away with the need to trust), in applications like cryptocurrency, it can facilitate illicit activities, and hence, in compliance, taking necessary crypto AML measures is vital.

Beneficial ownership identifies information about the entity or individual who benefits directly or indirectly from an asset or controls it, such as company ownership. Collecting and verifying beneficial ownership is essential to prevent bad actors from hiding or channeling money from criminal activities into shell companies or obscure ownership schemes.

Compliance bodies, like FinCEN, mandate financial institutes conduct beneficial ownership verifications during onboarding and record the information for reporting, audit, and supervisory purposes.

Beneficial ownership structures are purposefully complex when intended for illicit activities to obfuscate relationships. It’s nearly impossible to manually determine ultimate beneficial ownership without using enormous resources. Siron One uses ML-based advanced network analysis (link analysis) to determine hidden relationships, streamlining the compliance process.

Business rules help lay the groundwork to automate workflows in compliance software. They set the framework for what actions to take when certain conditions are met or not met. Business rules are usually governed by logical statements such as IF, ONLY IF, or WHEN a particular event occurs, THEN respond in a pre-determined way or ELSE take another action.

Having these pre-determined conditions customized to specific business needs can go a long way in automating work, reducing redundant or duplicate work, increasing the quality of work, and freeing up compliance officers for more valuable roles.

Siron®One includes a Rules Editor that allows you to customize business rules based on company requirements, specific client cases, risk profiles, customer due diligence and other factors.

In compliance software, a Case Manager is a feature that generally gathers all the concurrent and relevant information about a client in one place for easy access and contextual understanding.

In an advanced compliance platform such as Siron®One, the Case Manager digitizes a client’s end-to-end relationship across the entire lifecycle, from onboarding and KYC to dynamic risk scoring, behavioral clustering and analytics, historical transactions and alerts, work priorities, and more to present a customer 360 view. All related data on Siron®One Case Manager can be represented graphically using Smart View, which makes the data even more accessible.

Siron®One Case Manager is the platform’s central hub, connecting data, alerts, modules, tracking changes, and enabling workbenches, rules editing, and collaboration for a comprehensive, integrated approach to regulatory compliance.

A Central Bank Digital Currency (CBDC) is a digital fiat currency. It’s not decentralized like crypto, works alongside paper money, and is backed by governments. CBDCs operate under the same regulations as fiat, and institutions must comply with BSA/AML, CTF, and data security frameworks.

Various governments have initiated CBDCs, like China’s Digital Yuan, the European Union’s Digital Euro, the USA’s Digital Dollar, and the Bahamas’ Sand Dollar.

Customer due diligence (CDD) is a mandatory part of regulatory compliance for financial institutions and regulated business. It involves collecting relevant customer information, verifying it, and recording it at the start of a new relationship. CDD aims to mitigate the risk of doing business with a high-risk or politically involved entity by evaluating customer information against sanctions lists, PEP and watchlists, adverse media and public data sources like company listings.

Many financial institutes take a risk-based approach to CDD: basic, standard, and enhanced due diligence (EDD). For customers posing a higher risk, businesses conduct EDD to reduce the risks related to money laundering, terrorist financing, and fraud.

FinCEN has CDD Rule amended to the Bank Secrecy Act regulations that require financial institutions to identify and verify customers and beneficial owners of companies, clarify the purpose of the account to develop risk profiles, and conduct ongoing monitoring and report suspicious activity.

A central bank is a financial institution responsible for managing a country’s (or a group of countries like the Eurozone’s) currency and maintaining price stability. Central banks define monetary policies related to macroeconomics that reduce inflation and ensure stability and growth. These policies include setting interest rates and affecting the cost of money. Central banks are also responsible for regulating the money in circulation, overseeing the interbank market, and providing advisory services.

Central banks produce research studies and directives for government and private financial organizations in their advisory role.

Individuals cannot open accounts with central banks, but commercial banks can seek their assistance with solvency issues.

Terrorists need money to sustain their activities, and they abuse legitimate financial systems to garner funds. Combating the financing of terrorism (CFT) is a concerted effort among many regulatory and supervisory regimes, financial institutions, judiciary systems and individuals.

Banks and payment providers/processors are the first line of defense against CFT, considering terrorists use these financial systems to launder money. Hence, regimes like FATF, FinCEN, IMF, World Bank, UN, the EU, and others set mandatory regulatory compliance to prevent terrorist financing across the globe.

CFT is integral to AML compliance for financial institutions and includes complying with regulations like the FAFT8 or the FATF Recommendations.

Challenger banks are digital-first banks that focus on customer-centric service, innovative financial products, and low fees – all meant to “challenge” traditional banks.

Challenger banks leverage technology like AI and friendly UI to customize financial solutions, shorten onboarding, and provide personalized customer service.

These banks hold their own banking licenses and operate under the same regulatory framework as traditional banks.

Client onboarding is a necessary first step in client relationship and client life cycle management for all regulated businesses like financial institutions and virtual asset service providers (VASPs).

In this process, organizations verify essential client information, such as name, DOB, address, citizenship, and more, to mitigate risks, prevent fraud, and comply with AML regulations. Further, during client onboarding, organizations need to verify sources of funds, beneficial ownerships, and customer risk profiles.

Businesses are also liable to securely store the collected client information, following data security and privacy regulations.

One oft-neglected aspect of client onboarding is the customer experience. Most banks lose a high percentage of customers during a long and cumbersome client onboarding process.

A web—or mobile-based digital client onboarding system, such as Siron®One, helps automate, streamline and speed up client onboarding for regulatory compliance.

In compliance, customer lifecycle management software helps manage customer relationships from onboarding to offboarding. Siron®One CLM can manage end-to-end client relationships across all compliance use cases during a client’s lifetime, including onboarding, KYC, customer due diligence, and creating risk profiles.

As risk profiles change, Siron®One CLM dynamically scores risks, conducts perpetual KYC and screens adverse media and sanctions. It also guides users when Enhanced Due Diligence is required for a customer.

Siron®One has a user-friendly, fully digital onboarding that guides users on what documents it requires based on customer type and risk profiles. Further, it creates all necessary logs for audit trails and investigations.

AI-based clustering is when a machine learning model categorizes data into subgroups based on the group’s similarities. It is utilized in identifying patterns in unsupervised learning algorithms, particularly when the matches don’t need to be exact. The primary goal is to find how closely an element is related to a group and store information in a way that can be searched and identified quickly.

The closeness function, similarity metric, or distance measure in AI clustering shows close two entities are. Measuring this deviation is critical in AI-based compliance to understand whether an entity is behaving differently from its cluster or group and whether it warrants an investigation.

Siron®One uses AI clustering and deviation scores, among other metrics, to generate alerts when an individual or entity’s behavior changes from its cluster and baseline information.

Commercial banks provide banking services to businesses, government agencies, and education institutes. Their primary financial product is loans and earning interest from the loans.
Other commercial bank products include checking/savings accounts, lines of credit and credit letters, payment processing, forex transactions, and advisory.

Artificial Intelligence’s ability to sift through and analyze large volumes of data, detect hidden patterns, and catch changes has a massive impact on regulatory compliance. AI can reduce manual, error-prone, data- and labor-intensive work and produce higher-quality work in a fraction of the time.

AI can automate routine tasks with the proper business rules, result in more accurate reporting, and create transparency in compliance.

Perhaps more importantly, AI-based compliance can be more effective for real-time cases, such as fraud detection and prevention, transaction monitoring, transaction sanction screening, and intelligent name detection for immediate decision-making. AI is also critical in keeping up with new financial crimes and regulatory changes. That’s why AI compliance is the new standard in compliance software.

All Siron One modules are powered by AI, ML, and predictive analytics to automate work and reduce costs.

Core banking system or core bank, an acronym for Centralized Online Real-time Environment, refers to the back-end system responsible for processing everyday banking transactions, including deposits and withdrawals, interest calculation, loan issuing, and even customer service.

Core banking systems integrate with other systems and applications to provide all necessary solutions, such as accounting, the bank’s general ledger and CRM.

Siron®One compliance platform can connect with any core banking system via API for seamless integration and real-time risk mitigation.

Corporate banks, business banks, and institutional banks are responsible for lending to large corporations, financial institutions and governments. They differ from commercial banks, which lend to individuals and small businesses.

The two primary corporate banking products are revolving credits and term loans. Revolving credits act like credit cards; the customer can withdraw or repay a pre-set amount, and the corporate bank charges a utilization fee.

Other corporate bank products may include bridge finance and letters of credit.

Corporate compliance entails all the internal and external processes, standards, policies, and training involved in following local, state, national, and/or international regulations and mitigating risks. All businesses, regardless of size, need corporate compliance, but the regulations they need to follow depend on industry, channels, jurisdictions, and business ecosystems.

Numerous regulatory bodies, such as the Federal Trade Commission, the US Securities and Exchange Commission, the European Commission, and many more, set the laws and policies for compliance.

Whatever regulatory regime a business is liable to comply with, its compliance processes must include mitigating third-party risks, customer due diligence, knowing your customer and your business, and anti-money laundering efforts.

Siron®One enables businesses to comply with (as well as keep pace with changes in) all the relevant corporate compliance regulations based on jurisdiction and areas of operations.

Correspondent banks are third-party banks that provide banking services to other banks (known as respondent banks), enabling the latter to provide banking services to regions outside their operations, like foreign countries. Correspondent banks are trusted third parties between two counterparties who may not be familiar with each other.

For regional and Tier 2 and 3 banks without an expansive partner network, correspondent banks facilitate various services, such as international payments, trade and investments, and forex and cross-border transactions.

Credit unions are members-only non-profit organizations that provide financial services to their members, including loans and deposits. Members are selected to join through specific groups, like employers or countries.

Credit unions are managed by a volunteer board of directors who are also members. Any profit they generate is returned to members through lower fees, interest rates, and higher savings.

Customer Relationship Management is a solution that helps businesses track and analyze all customer information and interactions. It acts as the source of truth for all departments, from marketing and sales to legal and regulatory.

CRMs collect and securely store customer information and analyze customer metrics based on transaction history, behavior patterns, and preferences, providing businesses with a deeper understanding of their customers.

Siron®One easily integrates with any CRM through API and can flag suspicious behavior or transactions in real-time to prevent financial loss and safeguard customers.

The Common Reporting Standard (CRS) is a method of disclosing/exchanging financial information set by the Organization for Economic Cooperation and Development (OECD). It is similar to the Foreign Account Tax Compliance Act (FATCA) and aims to prevent tax evasion.

Financial institutions in the 100+ jurisdictions that have adopted CRS must develop due diligence, document and identify accounts, and file reports for tax compliance.

CRS differs from FATCA in that the former is based on tax residency, not citizenship, and hence is much broader in scope.

Siron®One helps financial institutions automate the workflows related to both CRS and FATCA reporting to save time and increase efficiency.

In cryptocurrency’s decentralized environment, it’s easier to hide identities and bypass jurisdictions or sanctions, which has aided terrorists and criminals in converting digital assets into fiat currency.

To combat the rise of money laundering using cryptocurrency, regulators like FinCEN and Commodity Futures Trading Commission (CFTC) classified crypto companies as financial institutions (FI) liable to comply with the same AML rules established by the Bank Secrecy Act (BSA) for traditional FIs.

Crypto AML requires crypto companies to conduct customer due diligence and KYC, monitor all transactions, flag and report suspicious activities, and follow requirements such as the Travel Rule and cross-border transactions.

Siron®One Crypto AML ensures security, reliability, and stability for all users as well as the crypto companies.

Cryptocurrencies are alternate digital currencies not backed by a centralized entity like a central bank.

Cryptocurrencies are built and run on a decentralized network, blockchain, which provides a transparent and immutable record of all transactions. They are transferred peer-to-peer (or node-to-node) without any intermediaries like banks.

Cryptocurrencies are governed by encrypted code and public and private keys. During a crypto transaction, nodes on the blockchain (users) verify the transaction is possible through mathematical computation and execute it. The nodes, called miners, are paid a sum (gas fee) for their work. The receiver of the crypto accesses it through their private key.

Crypto acquires value through supply and demand, and real-world events. Some crypto may be pegged to a real-world asset, like stablecoins are pegged to fiat currencies like the US dollar. When a central institution issues a crypto, it’s known as central bank digital currency (CBDC).

Crypto exchanges are platforms where users can buy and sell crypto. They essentially function like stock or commodities exchanges. Some cryptocurrency exchanges allow fiat for buying and selling, while others only trade digital assets in pairs (selling one digital asset to buy another simultaneously).

There are two main types of crypto exchanges: centralized and decentralized. The first is very similar to traditional stock exchanges in that it is governed by a central authority and must comply with KYC and CDD rules.

Decentralized exchanges (DEX) are autonomous, decentralized networks that run on a public distributed ledger. DEXs are anonymous and don’t require KYC verifications. DEX can be on-chain books, off-chain books, or automated market makers based on where the transaction takes place and what kind of algorithm facilitates the trading.

Under the Financial Crimes Enforcement Network’s (FinCEN) AML rules, financial institutions must file an electronic Currency Transaction Report (CTR) for transactions that exceed USD 10,000.

The transactions can be deposits, withdrawals, exchanges of currency, or other payments or transfers. The CTR applies to all customers except those marked as exempt persons or groups, such as commercial customers, withdrawals related to payroll, or customers who frequently engage in transactions exceeding USD 10,000.

To file a CTR, the bank must verify and record customer details, account number, identification, and taxpayer number.

A 360-degree customer view is a holistic view of a customer across all touchpoints compiled into a single view to better understand their history, interactions, alerts, risks, and changes in behavior.

Customer 360 is becoming an essential concept in compliance management to quickly access relevant information to make well-informed decisions, serve customers better while mitigating any financial risks, and increase operational efficiency.

Siron®One offers Customer 360 along with features like Smart View that allow users to see graphical representations of customer data for even easier access to relevant information.

Customer acquisition cost is the cost a company incurs to acquire a new customer. Knowing the CAC is crucial in understanding the approach, financial planning, budget, marketing, and other resources a company needs to allocate to remain profitable.

CAC is calculated by dividing the total cost of resources spent in marketing and sales by the number of customers acquired. Insurance and finance have two of the five highest CACs.

Customer Risk Assessment is a risk-based evaluation conducted during onboarding to determine a new customer’s risk rating that will indicate the level of Customer Due Diligence (CDD) required. High-risk customers require Enhanced CDD, while low-risk customers require Simplified CDD.

Financial institutions must assess each customer’s risk and assign a rating based on money laundering risks. The process includes identifying customer details, citizenship, business details, beneficial owner, purpose of the account and relationship, reviewing insurance policy beneficiaries and assessing related financial services and transactions.

Siron®One assigns a risk rating based on the information collected during onboarding but dynamically calculates risks throughout the customer’s lifecycle.

All financial institutions and regulated businesses must conduct Customer Screening and Monitoring for AML to detect and prevent financial crimes, fight money laundering, prevent terrorist financing and mitigate ongoing risks.
Customer screening during KYC and onboarding includes checking against PEP, watchlists, and sanctions lists to calculate risk profiles.

Customer monitoring is an ongoing process involving real-time monitoring transactions, conducting perpetual KYC, calculating dynamic risk scores, flagging deviations from baseline information, and reporting suspicious activity.

Darknet is a part of the Internet that’s purposefully hidden from the mainstream and accessible only through special software, authorization, or configurations.

Darknet is anonymous to protect users and can be accessed through the Tor browser and I2P (Invisible Internet Project), which masks internet traffic to obscure identity.

While it provides security and privacy for whistleblowers, it’s also used for nefarious activities. Due to its anonymity, the darknet often hosts illegal content and is a marketplace for trading drugs and weapons.

A dataset is (usually) an extensive collection of data used to train, validate, and test an AI/ML model. The data is typically labeled to allow the ML to learn how to categorize the information, which can then work with unlabeled data.

For the ML model to render accurate and precise results, the dataset must be clean and accurate, so the model learns correct patterns and identifications quickly. It must also be fair so that the results are bias-free and ethical.

To ensure training datasets are helpful, accurate, and efficient, data needs to be pre-processed, including correcting errors in labeling, normalizing data, and handling missing values. Datasets must also be large and diverse enough that the results can account for different situations and the ML model is not skewed.

Decentralized Autonomous Organizations (DAOs) are fully managed by smart contracts on the blockchain, which enables centralized governance without centralized control. All DAO members have tokens that grant them the right to vote, propose, and make changes.

Although their legal status varies depending on jurisdiction, DAOs are subjected to compliance rules like AML/KYC, governance standards, security laws, and taxation.

A decentralized network doesn’t have a central entity controlling it; instead, decision-making is distributed across many nodes, making them more secure, transparent, and resilient by reducing the points of failure and distributing power among many users. Blockchain and its applications like Bitcoin or Ethereum cryptocurrencies or smart contracts run on decentralized networks.

Decentralized networks are subjected to many of the same regulatory compliances as centralized networks, like GDPR, CCPA in California, securities laws, consumer protection, and taxation. Decentralized finance (DeFi) is also strictly governed by AML/KYC requirements.

Decentralized Finance (DeFi) is a financial system built on a decentralized network without any central or intermediaries controlling it. Using smart contracts, DeFi enables financial services like lending, borrowing, trading, and earning interest, giving users more transparency, control, and security.

Depending on the type of financial product and jurisdiction, DeFi may be subject to AML/KYC, GDPR, consumer protection laws, taxes, and regulatory reporting. Some DeFi issue tokens, and in jurisdictions that classify tokens as securities, DeFi is subject to securities laws.

Digital Assets or Virtual assets exist in digital format and have value, but they could also be pegged to a real-life asset as its digital representation, such as a tokenized real-life painting.

Some well-known digital assets include cryptocurrency and stablecoin, NFT (non-fungible token), and security tokens representing asset ownership.

Virtual assets are sometimes classified as securities and must comply with securities laws, including registration, disclosure, as well as tax regulations. Platforms trading virtual assets must also implement AML and KYC, data security and privacy, regulatory reporting, and consumer protection.

Distributed Ledger Technology (DLT) is a distributed database of ledgers that records transactions and stores them in multiple places simultaneously. DLT has no central data storage or administration. Its benefits are decentralization, transparency, security, and immutability. DLT works by a consensus mechanism like Proof of Work or Proof of Stake.

The most crucial use of DLT is blockchain, on which applications like NFT, crypto, and smart contracts are built. DLT has applications in virtually all industries, including financial services for cross-border payments, trade finance, clearing and settlement.

Compliance in DLT depends on the application. For example, DLT based financial applications require strict transactions, securities, and anti-fraud measures.

Document Management entails processing, categorizing, organizing, filing, giving permissions, and storing documents across their lifecycle to ensure a source of truth, collaboration, and workflow automation. It’s an important feature for advanced RegTech software like Siron One.

Siron®One’s document management also enables end-to-end digitalization, guiding customers through what documents are required during onboarding and providing one-click regulatory reporting.

It also ensures that audit logs are up to date, streamlines processes, optimizes resources, maintains integrity through version control, and adapts quickly to regulatory changes.

In AML, dormant accounts (accounts that remain dormant) pose a significant risk as they could have been created to carry out illegal activities. Inexplicable activity in a dormant account, such as a deposit, could signify money laundering.

FIs must periodically review and monitor these accounts and related KYCs to comply with AML regulations. Further, banks must set up internal policies, such as reduced thresholds, to mitigate risks.

Dynamic risk classification is becoming necessary in compliance as risk profiles change over customer lifecycles. AI and machine learning make dynamic risk classification possible by processing and analyzing large volumes of data, detecting patterns and anomalies, and learning on its own.

AI/ML monitors all transactions in real-time and detects changes in behavior through real-time data analysis and predictive analytics. ML can trigger automated CDD or enhanced DD depending on the dynamic risk rating. Using predictive analytics, it can analyze historical data to provide a more accurate risk classification. AI-based adverse media search in real-time is another way AI can calibrate risks.

Siron One uses AI and its subsets, ML, deep learning, NLP, predictive analytics, and GenAI to dynamically evaluate customer data at any given time to generate accurate and precise risk ratings.

Dynamic thresholds signify that the pre-set limits defined in the business rules are adjusted using real-time data and deviations in behavioral analytics to mitigate fraud and money laundering risks. Advanced ML-based compliance software, like Siron One, calculates dynamic thresholds using ML, predictive analytics and triggers events in real-time.

Dynamic thresholds make fighting financial crimes and mitigating risks more responsive to changing conditions and emerging threats. Through continuous monitoring and data collection, Siron®One can detect suspicious behavior to flag and reduce thresholds or normalize behavior over time to increase thresholds.

Economic sanctions are restrictive measures that countries or international organizations impose regarding trade and financial transactions on other countries that violate international laws (such as human rights). All businesses must comply with economic sanctions to avoid penalties and other damages.

Hence, businesses must conduct due diligence and screen all transactions and entities against sanctions lists to remain compliant. Since economic sanctions evolve, companies must keep abreast of changes from various regimes.

Siron®One automates screening for economic sanctions and keeps up with regulation changes.

eKYC or electronic Know Your Customer digitally performs KYC for greater efficiency. Manual KYC involves gathering documents and in-person verifications, which require a lot of resources.

However, advanced compliance software like Siron®One digitizes KYC processes end-to-end to streamline them and better serve customers. Web interfaces, user-friendly UI, and AI that guide users on what documents are required based on customer profile make Siron®One’s eKYC much simpler to use and more secure for data privacy and security.

In compliance, an embargo is a government-imposed restriction on trade and economic activity with certain countries, entities, or individuals that violate international laws, such as promoting nation-state cyber-attacks, violating human rights, or perpetrating genocide. Iran, North Korea, and Cuba have been on embargo lists imposed by the US and others, and trade, travel, or transactions are prohibited.

Businesses must carry out due diligence and screening to avoid engaging with embargoed countries or entities. They also need to keep updated with changes in embargo lists from different regimes. Non-compliance with embargo regulations can result in fines, sanctions, and reputational harm.

An entity deviation score reflects a customer’s deviation from their normal behavioral pattern. Predictive analytics learns the customer’s behavioral baseline. Based on pre-defined rules and thresholds, the ML model generates an alert when behavior surpasses the threshold limits.

The deviation alerts are scored based on how much they deviate from the baseline information, the frequency of deviation, the weight allotted to each action, the count or pattern anomaly, and other factors that trained the ML model.

Entity deviation scores are essential for taking timely actions for transaction prevention, fraud detection, and money laundering.

Entity screening refers to screening entities such as groups, companies, or any legal entity against sanctions lists, PEP lists, and watchlists. It is a mandatory part of regulatory compliance that helps mitigate risks.

Entity screening is part of customer onboarding related to KYC/CDD and Enhanced Due Diligence, and non-compliance can result in fines and sanctions.

The European Banking Authority (EBA) is the EU’s regulatory agency responsible for supervision in the European banking sector. It aims to maintain financial stability, protect consumers, and fight financial crimes. The EBA regulatory framework includes adherence to PSD2, MiFID II and MiFIR, AML/CTF, CRR and CRD IV, and the Bank Recovery and Resolution Directive (BRRD).

The European Financial and Economic Crime Centre (EFECC) is a Europol unit established to combat complex and cross-border financial and economic crimes. Their focus areas include money laundering, fraud, corruption, intellectual property crimes, financial market manipulation, and cybercrimes.

In addition to contributing to EU regulatory policies and advocacy, they are responsible for intelligence gathering and research, capacity building, coordination with other regulatory organizations, and regulatory enforcement in EU member states.

Explainable AI (XAI) provides a transparent and clear explanation of the decisions taken to arrive at a certain conclusion.

In compliance, XAI means the results are verifiable and auditable, follow anti-discrimination laws, comply with regulations like GDPR’s “right to explanation,” and enable clear, well-informed decisions. XAI also leads to more trust from all stakeholders, including in regulatory reporting and supervision.

ML-based compliance software generates alerts when it detects suspicious activity and changes in patterns. False positive and false negative alerts refer to the ML model’s ability to generate alerts accurately and speak to the software’s reliability.

False Positives occur when compliance software identifies a legitimate transaction as suspicious, which can lead to time wasted in manual investigations and increased workloads.

False Negative occurs when an ML-based software fails to detect a suspicious or non-compliant activity, which can lead to grave repercussions like facilitating financial crimes, compliance violations, and reputational damage.

Siron®One not only has the best alert generation accuracy of any compliance software, but through continuous model tuning, constant learning, risk-based approach, data quality and enrichment, and human oversight, the ML model keeps improving for more accuracy for a longer time.

The Foreign Account Tax Compliance Act, or FATCA, was enacted in the US to improve tax compliance, requiring foreign financial institutions (FFIs) to identify and report information about financial accounts held by US taxpayers to the US Internal Revenue Service (IRS). FFIs that fail to comply can be subjected to up to 30% tax withholding on US source income received by the entity.

FATCA works through intergovernmental agreements between the US and other countries. FFIs must agree to comply with FATCA and implement the required due diligence to identify and report US accounts or incur penalties.

FATF, or Financial Action Task Force, is an intergovernmental organization established to combat money laundering and terrorist financing and maintain the integrity of the international financial system. FATF regulations have been widely adopted worldwide and require stringent regulatory and enforcement systems.

Other than setting international regulatory standards and evaluating and monitoring compliance, FATF issues blacklists and sanctions lists with which all financial institutions under its jurisdiction must comply.

Financial Action Task Force (FATF) issues two types of lists to identify jurisdictions that lag in AML/CFT frameworks, the blacklist and the grey list.

The FATF blacklist includes jurisdictions that have significantly lax anti-financial crime regulations and pose a risk to the international financial system, and are not trying to strengthen it. Businesses working with blacklisted countries need to undertake EDD. Removal from the blacklist requires a demonstration of implementation or plans to implement a stricter regulatory AML/CFT framework.

The FATF grey list includes jurisdictions that implement AML/CFT but have substantial gaps. These jurisdictions remain committed to remedial measures to strengthen AML/CFT regulations. The FATF monitors grey-list jurisdictions periodically and can remove them if they significantly improve.

The Financial Conduct Authority (FCA) is a UK-based regulatory body responsible for protecting consumers, enhancing market integrity, and promoting competition within the financial services industry.

Its primary areas of focus are regulatory oversight, supervision and enforcement, promoting competition and innovation, education and guidance, policy and rule-making and investigation and penalties.

Financial crime refers to any activity that entails the illegal acquisition of financial resources through deceit, subterfuge, and breach of trust. It includes money laundering, fraud, corruption, terrorist financing, tax evasion, insider trading, and sanctions violations.

All financial and regulated businesses are mandated to take necessary measures that detect, prevent, and mitigate financial crime through KYC, AML programs, CDD/EDD, sanctions screening, transaction sanctions screening and transaction monitoring, auditing, training, implementing internal policies and controls, auditing, and reporting.

Financial Intelligence Units (FIUs) are entities responsible for gathering data, analyzing, and sharing intelligence to prevent financial crimes, including money laundering and terrorist financing, to ensure the integrity and stability of the financial system.

FIUs like FinCEN, TRACFIN (Traitement du Renseignement et Action contre les Circuits FINanciers clandestins), AUSTRAC (Australian Transaction Reports and Analysis Centre), and NCA (National Crime Agency) – UKFIU are responsible for the collection of financial data through SAR and CTR, analysis, sharing intelligence, developing regulations and policies, and education.

A financial intermediary acts as a middle person to facilitate transactions across the financial system. They play a crucial role by providing liquidity, maturity transformation, risk diversification, and information processing. Banks, investment firms, insurance companies, pension funds, and mutual funds are all financial intermediaries.

All financial intermediaries must comply with prudential regulations like capital and liquidity requirements, conduct regulations like consumer protection and market conduct, AML/CFT measures, sanctions compliance, reporting and public disclosure, corporate governance, and consumer data protection.

Depending on jurisdictions, financial intermediaries follow BCBS, FATF, IOSCO, IAIS, and FSB or other regulatory frameworks.

The Financial Stability Board (FSB) is an international organization that oversees the stability of the global financial system. Created by the G20 in response to the 2007 financial crisis, FSB aims to strengthen financial regulation and promote stability.

Some of its functions include surveillance and assessment of financial stability, developing standards like the Basel Committee on Banking Supervision (BCBS), the International Organization of Securities Commissions (IOSCO), and the International Association of Insurance Supervisors (IAIS), policy coordination with national authorities and cross-border resolution, developing macroprudential policies and crisis management, and ensuring resilience of financial markets infrastructures.

The United States Department of the Treasury’s Financial Crimes Enforcement Network (FinCEN) was formed to combat money laundering and the illicit use of the financial system. Their focus also includes stopping TBML and issuing crypto regulations.

Besides developing and enforcing regulations and policies, FinCEN is responsible for data collection and intelligence and collaborating with intergovernmental agencies.

All US financial institutions follow regulations set by FinCEN, some of which include complying with BSA/AML, SAR, CDD, Beneficial Ownership Rule, FBAR, and the US Patriot Act.

The Swiss Financial Market Supervisory Authority (FINMA) oversees financial markets, protects creditors, investors, and policyholders, and supervises banks, insurance companies, stock exchanges, securities dealers, and collective investment schemes. Their focus areas include ESG and sustainable finance, cybersecurity, and FinTech.
Their roles include supervision, issuing regulations, enforcement, licensing, managing crises, and maintaining stability. A few of the rules under FIMMA that financial institutions need to follow include Capital Adequacy Requirements, AML, Conduct of Business Rules, Corporate Governance, Market Conduct Regulations, and Liquidity Requirements.

Financial Transactions and Reports Analysis Centre of Canada (FINTRAC) is Canada’s financial intelligence unit responsible for supervising AML/CTF regulations to detect, prevent, and mitigate money laundering and terrorist financing.

FINCTRAC oversees regulatory and transaction reporting, ensures reporting entities’ compliance, and produces intelligence related to AML/CTF, including trends in financial crimes.

Its Financial Intelligence Program is mandated by the Proceeds of Crime (Money Laundering) and Terrorist Financing Act (PCMLTFA) to produce actionable intelligence and collaborate with domestic and international agencies in fighting money laundering and terrorism financing.

FinTech (Financial Technology) is the inclusion of technology in financial services to improve delivery. It has a wide range of applications, from digital wallets to robo-advisors to P2P lending platforms.

FinTechs need to comply with regulations similar to those of traditional financial institutions, such as KYC, SAR and Real-Time Reporting, Transaction Monitoring, Consumer Protection and Fair Lending Practices, PSD2, the Dodd-Frank Act, AML and Anti-Fraud Measures, and Cybersecurity and Data Protection.

FRAML, or Fraud Risk and Anti-Money Laundering is a collaborative approach to fighting fraud detection and anti-money laundering (AML) in one framework to streamline processes and leverage the practices of fraud detection and AML for better outcomes. The purported benefits of FRAML are more responsive systems, better detection, cost savings, and improved compliance.

Some of the key components of FRAML are unified detection systems, shared intelligence, a risk-based approach, including prioritization of risk, CDD, KYC, EDD, real-time transaction monitoring, a unified reporting mechanism, the use of advanced tech, including advanced analytics and automation, governance and training.

Fraud prevention entails all the controls, technologies, policies, training, and strategies an organization employs to combat financial fraud and comply with regulations. Regulations like the Sarbanes-Oxley Act, GDPR, PSD2, and various anti-money laundering directives provide the legal and operational standards necessary to combat fraud on a global scale.

Establishing internal policies and controls, such as preventing unauthorized access to financial systems and data, creating a culture of compliance through education and raising awareness, using advanced compliance software for real-time transaction monitoring and analytics, complying with a fraud risk management framework, and establishing a reporting mechanism, all fall under a company’s fraud prevention program.

The Financial Services and Markets Authority (FSMA) is a Belgian regulatory regime that supervises entities and products in the financial sector, including banking, insurance, pensions, and financial products and services. It is responsible for the transparency, efficiency, and integrity of the financial markets.

A few of its responsibilities include issuing regulations and their enforcement, supervision of financial institutes, prudential supervision, corporate governance market oversight to prevent abuse and fraud, consumer protection, and education.

They ensure the implementation of regulations such as AML/CFT, Undertakings for Collective Investment in Transferable Securities (UCITS), and Markets in Financial Instruments Directive II (MiFID II) in Belgium.

Fuzzy logic is an approach in AI that utilizes degrees of truth instead of a binary true or false. It mimics human reasoning and works with imprecise data.

In compliance, fuzzy logic is required to make decisions using imprecise data or risk assessments for CDD where different factors have different weights. Fuzzy logic can help detect subtle changes in patterns or new patterns that lead to more precise fraud detection.

Generative AI (GenAI) is AI that uses deep learning models like Generative Adversarial Networks (GANs) and others to generate new text, data, music, or images based on the dataset it has been trained on. Gen AI has applications in chatbots, data augmentation, and data synthesis.

Siron®One uses natural language processing (NLP) to scan wide-ranging sources for adverse media screening and then GenAI to summarize the findings into a very short blurb for immediate understanding and quicker actions.

The goAML (go Anti-Money Laundering) application is a software solution developed by the United Nations Office on Drugs and Crime (UNODC) to assist Financial Intelligence Units (FIUs) in combating money laundering and terrorist financing. It collects data, analyzes and shares intelligence with FIUs, aiding them in processing large volumes of data and identifying and preventing financial crimes efficiently.

The goAML software has been adopted and implemented by FIUs in various countries, including Australia, Germany, UAE, Nigeria, South Africa, and Canada. In these jurisdictions, all entities responsible for reporting suspicious and large transactions to their respective FIUs use goAML, such as banks, credit unions, investment firms, insurance companies, money service businesses, casinos, crypto exchanges, payment providers, and others.

The quality of a machine learning model depends on three metrics: accuracy, precision, and recall. Each defines a specific characteristic and is more useful in certain use cases. In compliance, where it’s important to determine whether a generated alert is correct or wrong, precision plays a key role.

Precision in ML determines how frequently the model is correct when predicting a target class, that is, whether the alerts are true positive or negative or false positive or negative. A frequent problem with ML-based compliance is false positives; the model generates unimportant alerts that compliance investigators spend time and effort resolving.

High-precision scoring is critical when the cost of false positives is high. Precision is calculated by dividing the number of true positive predictions by the total number of predictions. The Siron®One ML model has an incredibly high precision of 90%.

The Hong Kong Monetary Authority (HKMA) is Hong Kong’s central banking institution responsible for maintaining monetary and banking stability in Hong Kong, managing the Exchange Fund, and promoting the integrity of the financial system.

HKMA maintains currency stability through the Exchange Rate Policy and Foreign Exchange Reserves. It’s also responsible for regulatory supervision and risk management of financial institutions, payment systems oversight, liquidity management and calculating interest rates, financial market and FinTech development, and consumer protection.

The HKMA also focuses on FinTech innovation, sustainable and green finance, and digital currency like Hong Kong’s CBDC e-HKD.

The HM Treasury Sanctions List is a collection of sanctions from the UK’s HM Treasury intending to combat terrorism, trade weapons of mass destruction, and punish offenders of international law such as human rights abuses.

The types of sanctions listed in the HM Treasury Sanctions List include asset freezes and financial restrictions, trade and travel restrictions. Transactions with these individuals, groups or entities are prohibited by UK residents and businesses.

All UK financial institutions, businesses, and individuals are responsible for complying with the sanctions list or being charged with civil and criminal penalties.

Businesses must implement controls to comply with the requirements of the HM Treasury Sanctions List, such as screening, monitoring, reporting, risk assessment and awareness.

Human in the Loop (HITL) means the AI model integrates human oversight into the AI-based decision, giving humans control. Humans can validate and correct the AI, leading to a feedback loop where the AI can learn and improve over time. Siron One employs a HITL approach to give humans ultimate power over decisions.

HITL combines AI’s efficiency with human expertise. Having humans in the loop is vital to gaining trust, ensuring decisions are bias-free, and interpreting complex regulatory rules with nuance and human acuity.

Accurate compliance platforms don’t simply rely on AI to generate results and make decisions, as that would be too risky and add to compliance risks.

Advanced platforms like Siron®One use AI for their indubitable capabilities and other systems to generate the most accurate and precise alerts. Siron®One uses a rules-based system and AI to generate and prioritize alerts. Human experts then look at the alerts and tackle them based on priorities.

In Siron®One, human users can edit business rules and reorder priorities to render more accurate and real-time results.

An Initial Coin Offering (ICO) is a type of fundraising for blockchain projects in which investors are issued tokens or coins that represent a stake in the project or some utility, like voting rights in a DAO. It’s an alternative to traditional venture capital.

In terms of compliance, it’s important to determine whether the token is classified as a security, which would then be subject to securities regulations.

ICO compliance rules vary with jurisdiction, but ICO projects need to implement AML/KYC, be transparent about project details, protect investors, and remain tax compliant.

Identity theft is a serious crime where a person illegally obtains and abuses another person’s data for financial crimes, leading to reputational and emotional damage and legal action. Companies are increasingly liable to take stringent measures to prevent identity theft.

Businesses need to employ internal controls such as data privacy, encryption, minimization, role-based access, real-time monitoring and audits, CDD, KYC, KYB, KYT, vendor screening, incident response planning, training, cultivating a culture of cyber security, complying with GDPR, CCPA, AML/CFT for businesses, and physical access security.

Identity Verification is the process of ensuring that the personal data shared by a customer or user is genuine and verified. It is crucial in fighting financial crimes, complying with regulations and improving customer trust. Identity verification is part of CDD, KYC, and AML/CFT.

Identity verification can be done through government documents, biometrics, 2FA, and other methods.

Businesses must also conduct periodic reviews and ongoing monitoring to prevent fraud and other financial crimes.

Insider trading is buying or selling publicly traded stocks by someone who has information about them that’s not known to the general public and gives the buyer/seller an unfair advantage.

Different countries have different consequences for illegal insider trading. In the US, the Securities and Exchange Commission (SEC) can impose 3X the profit gained or loss avoided. In the UK, the Financial Conduct Authority (FCA), the EU, and other entities also have severe consequences in their jurisdictions, including fines and imprisonment.

Businesses must take measures to prevent insider trading through corporate policies, monitoring and reporting, and whistleblowing programs.

Advanced compliance platforms like Siron®One take a multifaceted approach to reducing false positives and increasing precision and accuracy. The integrated scoring engine considers customer profiles, transactions, customer information, non-monetary events (adverse media), and watchlists (sanctions) to generate accurate alerts.

Siron®One integrates a risk-based approach with dynamic customer segmentations to reduce false positives further. By superposing the risk segments with the customer segments, the Integrated Scoring Engine makes it possible to give weight to the advanced analytics (ML) results and the pre-defined scenarios.

The Siron®One ML model uses supervised learning to train on millions of transactions and unsupervised learning to train on normal activity. It is pre-built with 200+ real-time profiles as relative comparisons to define scenarios. Besides, users can dynamically add risk segments and categories that are specific to them.

Customer risk-based profiles are built using static KYC data like wealth, citizenship, and PEP, dynamic criteria such as transaction volumes and frequency, and statistical criteria like sum turnovers and deviations.

When an application like Siron®One integrates with an enterprise system, it means that it can connect and work seamlessly with the company’s existing systems and software.

Integration with Enterprise System enables smooth data synchronization, mapping, and transformation across both apps, workflow integration and process automation, better interoperability and user experience leading to better collaboration and efficiency.

Name screening is an integral part of customer due diligence and know-your-customer (KYC) for financial institutions to comply with AML regulations. Name screening refers to checking an individual’s or entity’s name against known watchlists, sanctions lists, politically exposed persons (PEPs) lists, and adverse news sources to determine their risk profile. It’s an ongoing effort as customer risk profiles change during the lifecycle.

SSiron®One‘s Name Screening (INS) is an award-winning application that uses AI and machine learning to apply all available matching features, including syntactical, phonetic, multicultural, semantic, and alphabet matching across 15 languages.

Siron®One’s ML-based INS uses permeable pre-filtering to eliminate true negatives and high-precision scoring for higher quality and precision in name matching.

Investment banks are financial intermediaries that serve individuals, corporations, and governments through asset management and investment funds. They can also be responsible for underwriting and raising capital, IPOs, debt issuance, advisory services like M&A, proprietary trading, and equity and fixed income research.

Investment banks need to follow AML/CTF, KYC/CDD, and SAR. They are responsible for adhering to different regulations based on jurisdiction, such as MiFID II and Basel III in the EU and SEC Filings, Regulation D and S, and the Volcker Rule in the US.

ISO 20022 is an international standard for digital exchange of financial information in a standardized XML (Extensible Markup Language) format, aiding interoperability between financial institutions and systems and is used across payments, securities, foreign exchange, trade services, and others.

ISO 20022 helps standardize financial messaging, ensuring consistency and reducing ambiguity. It’s flexible, used across various financial products, and designed to accommodate new or changing regulations.

In the context of compliance, ISO 20022 helps combat money laundering, increases transparency and traceability, and reduces errors and disputes.

In compliance, jurisdiction refers to the regulatory body and government to which an entity is answerable and whose regulations and policies it must comply with.

Jurisdictions could be based on geography and indicate the national, state or local laws an entity needs to follow. It could also be based on functionality and industry, such as regulations for financial institutions. There could also be international jurisdictions, such as cross-border businesses, must follow the GDPR in the EU and the Sarbanes-Oxley Act in the US.

Know Your Business (KYB) is an essential part of due diligence for financial institutions, payment processors, and businesses that transact or partner with other companies to mitigate fraud, money laundering and terrorist financing.

While the basic KYB process is much the same as other due diligence like KYS, the important difference is establishing beneficial ownership, shareholder information, and checking against sanctions and PEP lists.

Know Your Customer (KYC) is a critical due diligence process and part of customer onboarding for financial institutions and other businesses to comply with AML/CFT and fraud prevention regulations.

The steps of KYC include customer identification through collecting basic information like government-issued documents and verifying the information received; conducting customer due diligence, including assessing risk profiles and conducting enhanced due diligence based on risk scores; and establishing sources of funds and verifying them through documents such as pay slips and tax returns.

Beyond these, KYC also involves sanctions screening, continuous monitoring and reporting, and recordkeeping.

Know Your Supplier (KYS) is a due diligence process businesses use to reduce the risks associated with supplier relationships, including financial, operational, regulatory, and reputational risks.

The process includes:

Collecting and verifying basic information and business profile for supplier identification, such as legal status, business registrations, and permits.

Identifying and evaluating potential risks, such as financial stability, geopolitical situation, industry sector, and previous compliance issues.

Building a risk profile and reviewing financial statements and credit checks to assess financial health.

Beyond conducting KYS for regulatory and legal compliance, businesses also do ethical and social responsibility evaluations.

Businesses are required to keep records of KYS and continually monitor and periodically review to assess changes and risk profiles.

Know Your Transaction (KYT) is the process of monitoring and analyzing financial transactions to detect and prevent crimes in real time. It’s a critical part of AML/CFT.

KYT requires monitoring transactions in real-time to gather data and analyze it and recording the source and destination of the funds; creating a transaction profile based on customer risk profile and risk segmentations; and using technology to monitor transactions continually and flag those that deviate from known risk profiles and segmentations.

Behavioral analytics and trend monitoring are also critical for identifying patterns and trend analysis. Ideally, the software generates accurate alerts for suspicious behavior and ranks them based on priority.

After this, compliance officers follow up the alerts with investigation and case management based on priority and, where needed, send suspicious activity reports and escalate internally.

KYT is part of regulatory compliance, internal audits, training and awareness, and, most critically, risk management.

Large Language Models (LLMs) are advanced AI systems that use deep learning to comprehend, generate and manipulate human languages.

In compliance, LLMs can process and analyze documents, monitor regulatory changes, and automate reporting. They are also used in compliance software to increase efficiency, scalability, adaptability, and accuracy.

The Levenshtein Distance, or Edit Distance, measures how many steps or the number of single-character edits (counting additions, deletion, substitutions) are needed to change one string into another. For instance, the Edit Distance between John and Johnathan is 5.

Levenshtein Distance is very useful in Intelligent Name Screening because it can fuzzy match names based on error tolerance even with different spellings or spelling errors, recognize name variations, ensure a true match and reduce false positives.

On the other hand, in sanctions screening, Edit Distance can prevent the overlooking of names even when there are minor inaccuracies.

Lexicon-based mode is AI trained on lexicons (dictionaries) to analyze the text without a statistical algorithm. The AI can categorize words based on rule sets, such as topic or industry.

In compliance, it can be used to train the AI on specific regulatory words and other keywords to detect risk and identify potential issues.

Link Analysis or Advanced Economic Network Analysis is the process of tracking the relationship between entities to uncover hidden patterns, trends, and anomalies to detect fraud, money laundering, and other financial crimes. It presents data as an interactive visualization that’s used to investigate complex connections and event sequences, and expose money laundering activity. For example, link analysis can help provide a clear picture of business ownership and control structures of a complex multinational company.

Given the sophistication of financial crime today, link analysis relies extensively on advanced machine learning techniques.

Machine Learning (ML) is a subset of AI that can learn from data and make predictions or decisions without being programmed.

ML is becoming integral to risk profiling, KYC and customer due diligence, real-time AML and transaction monitoring, sanctions screening, fraud prevention, predictive analytics based on historical data, automated review and text extraction for audits.

Siron®One ML models are the most advanced ML used in compliance. They are deployed after being trained in real-world and customer-specific data, leading to even more accurate results.

The Markets in Financial Instruments Directive (MiFID) is a regulation for banking and investment services within the EU meant to improve transparency, investor protection, and competition. It applies to stocks, bonds, derivatives, and structured financial products.

Another key aspect of the MiFID is the Best Execution policy, where financial firms are required to do the best for their clients when making decisions about price, costs, speed, and whether to execute a trade or not.

Firms must also disclose trade information like price and volume before and after executing transactions. MiFID also mandates businesses have ample risk management and internal controls and protocols to comply with this regulatory framework.

Investment firms, credit institutions, trading platforms, market operators, and data service providers in the EU must comply with MiFID.

The Middle East and North Africa Financial Action Task Force (MENAFATF) is an organization in the Middle East and North Africa (MENA) region established to combat money laundering and the financing of terrorism.

It works with the Financial Action Task Force (FATF) to implement its protocols, assesses, monitors, and strengthens compliance execution within its jurisdiction, raises awareness of the risks and provides training to combat them.

Member countries of MENAFATF must follow FATF standards, including banks, insurance companies, and other financial institutions, as well as non-financial businesses like real estate agents, notaries, lawyers, and accountants.

In ML algorithms, Precision, Recall, and F-Score measure the quality of the ML model.

Precision measures how many true positives were correct. Recall measures how well the model identifies the positive instances, and F-Score is the harmonic mean of Precision and Recall.

In ML models used in compliance software, Precision reduces false positives, Recall identifies high-risk instances, and F-Score ensures the Recall and Precision output are reliable.

Siron®One reduces false positives by 90%, and a third-party test showed that its Recall is 99.9% accurate.

ML models can be trained using supervised, unsupervised, semi-supervised, or reinforcement learning.

In Supervised Learning, ML is trained on labeled data to predict outcomes based on input and is used in risk assessment and fraud detection.

Unsupervised learning uses pattern detection in unlabeled data and is used in anomaly detection and cluster segmentation.

Semi-supervised learning uses labeled and unlabeled data to give the ML model feedback and allow it to learn.

Lastly, reinforcement learning uses a reward-based approach where positive answers are rewarded and used in adaptive systems.

Machine learning capabilities are ideally suited for automatically screening customers against sanctions, watchlists, and PEP lists for regulatory compliance. ML can analyze the risk levels of customers and transactions based on baseline information, deviation from historical data, and risk factors.

ML screening can also detect patterns and anomalies, thus preventing fraud in real time through continuous monitoring and transaction sanctions screening.

The Monetary Authority of Singapore (MAS) is the central bank and integrated financial regulator, overseeing the sector in Singapore.

The MAS is responsible for implementing monetary policy and ensuring financial stability, regulating and supervising financial institutions, enforcing AML/CFT regulations, consumer protection, global engagements and collaboration, innovation and FinTech development.

Money laundering is the process of turning illegally obtained funds into legal money within the global financial system so that they become indistinguishable.

It takes place in three stages:

Placement: where the illicit money is introduced into the financial system through deposits in bank accounts, purchasing high-value assets, or using in legitimate businesses.

Layering: where the source of funds is concealed through a complex network of accounts and transactions using shell companies, making it difficult to detect the money trail.

Integration: where the funds are successfully laundered, indistinguishable from legitimate funds, and reinvested in the economy.

Globally, there are numerous compliance frameworks and standards to combat money laundering that financial institutions must follow, such as FATF 40 Recommendations, European AML Directives, Bank Secrecy Act (BSA) AML and US Patriot Act, IMF/World Bank, Basel AML Index, MENAFATF, and Egmont Group of FIUs, among others.

Regardless of the variations in regulations based on frameworks and jurisdictions, the implementation of key compliance measures is non-negotiable. Financial businesses must conduct CDD, file SAR, create an audit trail, monitor, assess risk, implement internal controls, and train employees to ensure compliance.

Money Service Businesses (MSBs) are financial institutions outside banks that provide services like currency exchange, check cashing, and issuing or redeeming money orders and traveler’s checks. They are critical service providers to the unbanked.

MSBs need to register and are answerable to regulatory regimes like FinCEN in the US, FCA in the UK, FINTRAC in Canada, and central banks in their countries.

They also need to implement all compliance protocols based on jurisdiction, such as AML, CDD, SAR, STR, transaction monitoring, and audit logs, have internal policies and controls, train employees, and periodically audit AML programs.

MONEYVAL, or the Committee of Experts on the Evaluation of Anti-Money Laundering Measures and the Financing of Terrorism, is an EU-based organization that assesses compliance with international standards to counter money laundering and the financing of terrorism and their effectiveness.

MONEYVAL member states are mostly members of the Council of Europe, some non-members, and observers of organizations like FATF, IMF, World Bank, and the European Commission.

It evaluates member states’ AML/CFT frameworks, the extent to which they follow FATF40 and the effectiveness of their implementation. It also calls for member states to submit progress reports and steps taken to address deficiencies identified during the evaluation.

Further, MONEYVAL researches money laundering and terrorist financing typologies to track new trends, risks, and techniques in terrorist financing.

Mortgage companies help individuals and businesses obtain financing to purchase real estate and can be independent companies or part of banks or credit unions.

Mortgage companies have a range of federal, state and local laws they have to follow, such as the Truth in Lending Act (TILA), Real Estate Settlement Procedures Act (RESPA), Equal Credit Opportunity Act (ECOA), Fair Credit Reporting Act (FCRA), Secure and Fair Enforcement for Mortgage Licensing Act (SAFE Act), and Dodd-Frank.
In addition, they must follow AML compliance, data privacy and security regulations, fair lending practices, and consumer complaint handling.

In cloud computing architecture, a multi-tenant cloud means many customers (tenants) share resources such as databases, servers, and storage, but each tenant’s data and applications are hidden and isolated from others. The benefits of a multi-tenant cloud are resource sharing and cost reduction, scalability, and no maintenance. It is ideal for small and medium-sized businesses.

A single-tenant cloud means the cloud environment is owned by one tenant with exclusive access to servers, storage, and databases. A single-tenant cloud provides greater control, customization, and isolation. But it also has a higher maintenance cost. It’s more suitable for large enterprises with special customization needs.

Name screening is an integral part of customer due diligence and know-your-customer (KYC) for financial institutions to comply with AML regulations. Name screening refers to checking an individual’s or entity’s name against known watchlists, sanctions lists, politically exposed persons (PEPs) lists, and adverse news sources to determine their risk profile. It’s an ongoing effort as customer risk profiles change during the lifecycle.

Siron®One‘s Name Screening (INS) is an award-winning application that uses AI and machine learning to apply all available matching features, including syntactical, phonetic, multicultural, semantic, and alphabet matching across 15 languages.

Siron One’s ML-based INS uses permeable pre-filtering to eliminate true negatives and high-precision scoring for higher quality and precision in name matching.

Natural Language Processing (NLP) is a subset of AI trained to comprehend and generate human languages.
NLP has many uses in compliance, from scanning through and processing adverse media or negative news to document guidance, data extraction, monitoring and alerting changes in regulatory policies, auto-filling standard regulatory forms, maintaining audit trails and intelligent name screening.

Natural Language Processing (NLP) is essential in adverse media or negative news screening for risk assessment.

NLP automatically collects news through web scrapping and RSS feeds, classifies text based on sentiment, and categorizes it based on relative risk. Through named entity recognition, the NLP algorithm extracts the names of entities or individuals and analyzes the context of mentions.

Based on relevance filtering, NLP matches keywords and returns accurate results by filtering for context. NLP can process adverse media in real time, generate alerts, and prioritize them based on filters.

Neobanks are online-only banks with no brick-and-mortar presence but offer a range of banking services, such as checking and savings accounts, payment services, and loans, using mobile apps and websites. They’re user-friendly, tech-forward, and have lower rates compared to traditional banks. They are focused on innovation, like providing budgeting tools, integrating with other financial apps/services, and offering robo-advisory.

Neobanks differ from challenger banks in that, typically, neobanks don’t have a physical presence, while some challenger banks do. More importantly, neobanks do not have banking licenses and instead partner with traditional banks to provide banking services, while challengers are fully licensed.

However, neobanks must follow and implement AML/CFT programs and are answerable to FCA, OCC, ECB, and others based on jurisdiction.

A no-code approach means making changes to an application can be accomplished without the need for coding. The no-code approach often uses pre-built templates and user-friendly tools to enable non-developers to customize an app quickly and without IT intervention.

Siron®One takes a no-code approach because it also means better workflow automation, integration with other apps, and easier deployment and maintenance.

Non-fungible tokens (NFTs) are unique digital assets usually stored on the blockchain that represent ownership. They can represent any virtual asset, like art, music, sports merchandise, or virtual real estate. Non-fungible signifies that NFTs can’t be exchanged on a one-to-one basis since no two NFTs are considered the same.

But NFTs can be fractionalized into different parts, and each part can have different ownership. NFTs are programmable, meaning they can include smart contracts that pay royalties to their creators. NFTs can also be updated, called dynamic NFTs, through an Oracle network when their metadata needs to be changed for applications like loyalty cards, baseball card stats, or property ownership.

NFTs must respect intellectual property rights and trademark laws, and NFT trading platforms must implement AML/KYC and consumer protection laws. If classified as securities, NFTs must comply with securities laws.

Optical Character Recognition (OCR) is a technology that can convert scanned paper documents, PDF files, or images captured by a digital camera into editable and searchable data. It is crucial in compliance because it can scan and convert volumes of compliance documents into machine-readable text, thus saving manual work and increasing efficiency and accuracy.

Siron®One uses OCR because it benefits compliance work processes by allowing quick access to data, improving organization and automation, improving record-keeping, and creating more efficient audit trails.

The Office of Foreign Assets Control (OFAC) is a financial intelligence and enforcement agency of the US Department of the Treasury that enforces economic and trade sanctions against targeted foreign countries, as well as regimes.

OFAC issues and enforces sanctions programs against some geographies, including the Specially Designated Nationals and Blocked Persons List (SDN List), the Sectoral Sanctions Identifications (SSI) List, and other list-based sanctions.

All US citizens, residents, and US arms of foreign entities must follow OFAC regulations, including screening against OCAF sanctions lists, monitoring, reporting and recordkeeping, risk assessment, and training. Non-compliance carries civil and criminal penalties.

The Offshore Leaks Database is a publicly accessible digital database created and maintained by the International Consortium of Investigative Journalists (ICIJ). It contains information about offshore entities, including companies, trusts, foundations, and other ways individuals manage wealth cross-border.

The Offshore Leaks Database comes from several major financial information leaks, including the Panama Papers, Paradise Papers, Offshore Leaks, and Bahamas Leaks. During customer onboarding, financial institutions check against the Database to identify risks associated with offshore entities and subsequently conduct enhanced due diligence.

In compliance, customer onboarding is the process of collecting and verifying customer information before officially establishing the business relationship. It’s a mandatory process for most businesses but perhaps the most detailed for financial institutions.

Besides collecting and verifying personal data, onboarding entails KYC, CDD/EDD, risk profiling and scoring, AML screening for sanctions lists, PEP lists, and adverse media, and establishing ultimate beneficial ownership and ownership structure. Onboarding also includes setting up internal controls for transaction monitoring, ongoing sanctions screening, and perpetual KYC.

It’s a long and arduous process that advanced compliance platforms like Siron One can automate and digitize end-to-end.

Ongoing monitoring is critical to Anti-Money Laundering (AML) compliance to detect and prevent illicit activities after the initial customer onboarding.

It entails continuous monitoring of consumer behavior, transactions, sanctions, and adverse media to detect changes and anomalies in behavior, transactions or trigger-based events to reassess risk scores.

The compliance software then generates alerts based on deviations and prioritizes them so they can be investigated and resolved, thus preventing illicit activities in real time.

On-premise deployment is a traditional way of installing and running software from computers located on an organization’s premises rather than in a cloud environment.

While it may mean more control and better customization, it also means more upfront and maintenance costs and limited scalability and flexibility.

However, on-prem may be a better solution for some large enterprises or ones with legacy enterprise software.

Oracle networks are like APIs for blockchains and Web3 applications in that they act as the bridge between two dissimilar layer one blockchains and enable them to interact with data outside of their blockchain network/environment.

Oracle networks help retrieve real-world data used in smart contracts, such as stock values at a certain date or sports scores. For example, in DeFi applications, Oracle Networks can provide real-time price feeds. Oracles use encryption for data exchanges and multiple sources for reliability.

Peer-to-Peer (P2P) in a distributed network is a way for two nodes (peers) to interact directly with each other without the need for a central entity. P2P in a distributed network means all peers are equal, there’s no single point of failure, and the network can be scaled to add more peers. P2P is used for sharing assets, from files and messages to crypto.

P2P eliminates the need for expensive infrastructures like central servers, resilient, and more reliable.

Payment providers help transfer funds between different parties for transactions or exchanges of goods or services. They can refer to banks, FinTechs, payment gateways, mobile payment providers, payment processors, and acquiring banks.

Payment providers are responsible for complying with all regulatory requirements, such as AML/KYC, PCI DSS, data privacy, sanctions screening, and consumer protection.

Perpetual KYC (pKYC) or continuous KYC is ongoing monitoring and updating of customer information to ensure it’s always accurate. pKYC is different from traditional KYC, which is static and is conducted during onboarding and periodic reviews.

Continuous KYC allows dynamic risk assessment based on trigger events, enhanced risk management, and more accurate compliance.

Politically Exposed Person (PEP) refers to people who hold a public position and are considered at higher risk for bribery, corruption, money laundering, and offshore wealth due to their influence. Checking PEP lists is mandatory for onboarding, AML, and continuous monitoring.

PEPs can include government and military officials, public functionaries, people affiliated with or family members or close associates of influential political leaders, and state-owned enterprises.

PEP lists warrant enhanced due diligence and continuous monitoring.

In an ML-based compliance platform, Pre-Defined Scenarios and User-Defined Scenarios are two ways of configuring the ML model to detect and manage compliance risks.

Pre-defined scenarios are built into the platform based on industry standards, regulatory requirements, and common compliance issues and can address known risks and challenges. They follow standardized rules, are ready to use, are updated along with the compliance platform, and provide a strong base for compliance monitoring.

User-defined scenarios are custom configurations based on specific industry and company compliance requirements, considering unique aspects of a business.

Siron®One uses both Pre-Defined and User-Defined Scenarios for a more comprehensive compliance program and proactive risk mitigation.

Predictive analytics can augment fraud detection, AML efforts, reporting, due diligence, and sanctions screening.

Predictive analytics uses statistical algorithms and machine learning to analyze historical data and predict new outcomes. This application is crucial in identifying risks and making decisions in real time.

In fraud detection, predictive analytics detects and flags anomalies and high-risk activities. In AML, it can assess accurate customer risk and detect suspicious activity. In CDD, predictive analytics is used for behavioral analytics, deviation from cluster and enhanced DD. Sanctions Screening uses predictive analytics for entity matching to get an accurate match against sanctions risk and assess future risk.

Pre-Trade and Post-Trade Anti-TBML measures are implemented to combat Trade-Based Money Laundering (TBML) at different stages of a trade transaction.

TBML is complex and challenging to detect, so rigorous due diligence, counterparty screening, risk assessment, analytics, and trends detection are necessary both pre- and post-trade to make anti-TBML measures more effective.

Siron®One uses machine learning for continuous monitoring and analyzing trade data for predictive analytics as well as keeping abreast of regulatory changes to generate even more accurate results in TBML monitoring in the long term.

Compliance software assesses and pre-calculates profiles based on historical client data, behavioral patterns, and transactions to provide a reference point for risk assessment. Each profile is assigned a risk score based on factors like transaction volume, frequency, geography, and type of business.

Profile scores and alerts from continuous monitoring are used to generate alert priorities.

By using historical data, advanced analytics, and continuous updates, profiles provide a customer 360 view, help take actions promptly where needed, and mitigate risks.

A Proof of Concept (POC) in ML verifies the accuracy of the ML model and that it’s ready for full-scale deployment.

POC in ML consists of defining the problem and what success means, collecting data, choosing a model, building and training the model on the data and evaluating its performance.

Based on how the ML model performs, it’s retrained with new data to improve performance. Siron One uses customer data for retraining to ensure the model is accurate.

POC and retraining the ML model is robust and continues to perform accurately in the long term.

PSD2, or the Revised Payment Services Directive, is a European Union directive that aims to regulate European and European Economic Area (EEA) payment services and payment service providers for enhanced consumer protection, payment security, and innovation.

PSD2 warrants strict security requirements for electronic payments and the protection of consumers’ financial data, including implementing strong customer authentication (SCA). It also promotes open banking, transparency, and increased competition.

PSD2 applies to banks and other financial institutes as well as payment services, such as account information services (AIS) and payment initiation services (PIS), third-party providers, and businesses.

Real-time payment screening entails using advanced technologies like ML and predictive analytics to monitor, analyze, and evaluate transactions as they occur. It is aimed at detecting and preventing fraud.

ML models process and analyze transaction data, detect patterns and behavioral analytics anomalies, generate risk scores, and evaluate them against historical data to create accurate alerts with priorities. Predictive analytics recognizes emerging trends in financial crimes and regulations to future-proof fraud detection.

Real-Time Payments Screening with ML enhances the accuracy, speed, and efficiency of fraud detection.

AI-based real-time decisions involve quickly evaluating and responding to a situation as it occurs.

AI can process and analyze volumes of structured and unstructured data in seconds. This capability is critical in responding to situations where decisions must be made as close to the event as possible.

In compliance, real-time decisions are non-optional in some instances, such as preventing transactions so consumers don’t lose money to bad actors or preventing fraud. But it’s virtually impossible to stop illicit transactions in real time manually. AI can not only collect, process, and analyze the data; ML models can recognize patterns, trends, and anomalies, helping users make decisions in real time.

Siron®One uses advanced machine learning, predictive analytics, and natural language processing to analyze data as it’s generated or received. It detects anomalies in patterns and renders alerts based on business rules and deviation thresholds, resulting in quick and well-informed real-time decisions.

Real-time processing refers to continuous and immediate analysis of data collected from transactions and trigger events, typically with machine learning, to detect anomalies and prevent fraud. It uses AI/ML to generate instant insights and enables quick action to stop financial crimes.

AI/ML continually gathers data from transaction records, customer profiles, communication logs, adverse media, and sanctions lists. The ML model analyzes the data instantaneously to identify patterns, correlations, and anomalies, leading to better real-time fraud prevention.

Real-time processing is also used in trade surveillance, anti-TBML, sanctions screening, AML, and KYC.

A red flag indicates an anomaly and possibly risk. It could signify illegal or unethical behavior, regulatory violations, or other misconduct. Reg flags warn compliance officers and other stakeholders to act to mitigate risk, adhere to laws, and take measures to remain compliant.

A red flag requires investigation to understand and contextualize it, escalation of the issue to the appropriate authorities, such as filing a goAML, corrective actions internally, documentation, training, and monitoring.

Reference List refers to the guidelines, laws, regulations, standards, protocols, and authoritative documents companies use to adhere to rules and regulatory compliance.

Reference lists include regulatory documents such as SEC regulations, ISO standards, and GDPR. Additionally, it contains internal policies and procedures, industry standards and best practices, sanctions and watchlists, risk management frameworks, and auditing and monitoring tools.

All businesses must file regulatory reports to disclose financial and operational information to regulatory bodies to maintain transparency and protect stakeholders. Financial institutions must file various regulatory reports to meet compliance and legal obligations, transparency and accountability towards stakeholders, investors, and customers, help regulators maintain market stability, manage risks, and generate investor confidence.

Some of the standard regulatory reports for financial institutions include AML/CFT-related reports like SAR and CTR, risk reports like Basel III and Solvency II Reports, market conduct reports like Best Execution Reports, consumer protection reports like Fair Lending Reports, and ESG reports like CSR and Sustainability Reports.

Reputational risk means the lack of trust and credibility that businesses can face due to non-compliance, unmitigated risks, and, most critically, involvement in illicit activity or unethical behavior. Reputational damage can have long-term repercussions, like loss of customer trust and investor confidence, increased regulatory scrutiny, and financial impact.

Managing reputational risk requires robust compliance programs, internal controls and policies, employee training, and continuous monitoring and updating.

Respondent banks are similar to correspondent banks, and together, they provide financial services to other banks, particularly cross-border. Respondent banks facilitate international banking operations and global trade. Their services include international wire transfers, conducting trade finance, offering access to foreign exchange markets, liquidity management, clearing, and settlement.

Respondent banks must follow all the regulations imposed on financial institutions to prevent money laundering, terrorist financing, and sanctions evasion, such as KYC, CDD/EDD, FATF Recommendations, Transaction Monitoring, Recordkeeping, Sanctions Checks, and Reporting.

Retail banking, or consumer banking, serves individuals and small businesses. Its services include deposit accounts, lending services like personal and auto loans, credit cards and mortgages, investment and wealth management, financial planning, and mobile banking.

Retail banks must comply with a wide range of regulations under AML/CTF, consumer protection, data privacy, financial reporting, fair lending and anti-discrimination, and cybersecurity rules.

Risk assessment identifies, analyzes, evaluates, prioritizes, and mitigates risks to remain compliant with laws, regulations, and internal policies. Proactive risk assessment helps avoid legal penalties, financial losses, and reputational damage.

Risk assessment entails identifying and analyzing risks, evaluating and prioritizing them, developing controls, implementing corrective actions, monitoring, reviewing, and updating.

A Risk-Based Approach (RBA) indicates a compliance strategy centered on identifying, assessing, and managing risks based on their severity and likelihood of occurrence. This contrasts with a rules-based approach, where uniform controls are applied across all areas. RBA is more efficient and resource-efficient by prioritizing the highest risks.

A risk-based approach includes a risk assessment framework, tailoring controls, allocating resources, monitoring and updating.

Regulators have started favoring a risk-based approach to compliance instead of a rigid rules-based one, as it allows more flexibility and control in mitigating risks.

Risk mitigation involves all the strategies, controls, and actions taken to identify and reduce the probability of compliance risk. It aims to protect an organization from potential legal, financial, operational, and reputational damage due to non-compliance with laws, regulations, and internal policies.

The risk mitigation process includes preventive, detective, and corrective controls, strategies, tools, and training. In regulatory compliance for financial institutions, the critical areas of risk mitigation are AML/CFT, which include KYC/CDD, transaction monitoring, and AML training, as well as data privacy and security.

Risk scoring quantifies and prioritizes organizational risks based on their potential likelihood and impact. Risk scoring helps prioritize risks, allocate resources, make timely decisions, and proactively manage risks.

Likelihood refers to the probability of each risk occurring, and it can be qualitative, such as low, medium, or high, or quantitative, like percentage probability.

Impact means the potential consequences of each risk. On qualitative scales, it could be minor, moderate, or severe and in quantitative measures, it could be the amount of financial loss.

At its simplest, Risk Scores are calculated by multiplying likelihood and impact. However, advanced ML models can render a more accurate score by considering more nuanced factors.

Robotic Process Automation (RPA) technology automates repetitive, rule-based tasks by interacting directly with a system or software. RPA improves efficiency, accuracy, and productivity by automating high-volume, routine tasks, allowing human workers to focus on more complex and value-added activities.

In compliance, RPA can automate many different workflows, such as data collection, integration, retrieval, data entry and validation, automated monitoring and report generation, KYC onboarding and continuous monitoring, document management, compliance training and others.

Advanced and user-friendly compliance platforms like Siron®One have a Rule Editor feature that allows users to define, modify, and manage the rules and policies that the platform enforces. The feature also provides guides for how data is processed and monitored to ensure compliance and mitigate risks.

Rule editors contain user-friendly interfaces that allow drag and drop, a variety of in-built templates and easy-to-change logic, conditions, and operators like if-then statements and AND, OR, or NOT that allow users to fine-tune rules based on needs.

Other than flexibility, rule editors offer workflow automation and efficiency.

Software as a Service (SaaS) is a cloud-based service in which the software is accessed via a browser rather than downloaded onto a device.

SaaS has numerous benefits, such as reduced deployment time, instant access, no infrastructure setup, lower costs, ease of maintenance and automatic updates, scalability and flexibility, real-time access and better collaboration, improved security, and easy integration with other software.

Sanctions are restrictive measures imposed on specific countries, entities, individuals, or sectors for violations, aggressions, or rights abuses. They aim to influence behavior by restricting trade, financial transactions, and other engagements. Sanctions can be economic, diplomatic, military, or even sectoral.
Sanction Lists contain information about specific entities and are issued by governments, regulatory bodies, and other organizations. Some important sanctions lists include OFAC, UNSC, the EU Sanctions List, and the HM Sanctions List.
Sanction compliance refers to the measures an organization must undertake to abide by sanctions and not engage with sanctioned parties to mitigate risks and compliance violations. These measures include screening sanctions lists during onboarding/KYC and continuous transaction sanctions screening during customer lifecycle.

A Suspicious Activity Report (SAR) is a report that financial institutions and other businesses, such as gaming companies, need to file when they detect activities that could signify money laundering, fraud, terrorist financing, or other financial crimes.

The SAR includes all relevant information, including the people involved, the type of transactions and why the activity was considered suspicious. Filing SARs is a mandatory part of AML and helps FIUs conduct investigations into similar suspicious activities to detect more significant trends and emerging risks.

Machine learning in transaction screening and monitoring serves two purposes: first, it processes large volumes of data in seconds to enable real-time action, and second, it detects links and new or anomalous patterns in the data. Both lead to increased productivity, but even more importantly, they mitigate risks by spotting hidden links and stopping illicit activities.

In transaction monitoring for fraud detection and AML, ML can analyze every transaction and behavioral data to detect payment or credit card fraud, thus reducing financial loss and reputational harm.

ML-based transaction screening makes intelligent name screening (INS), network analysis (link analysis), and sanctions list screening much easier. In Siron®One’s award-winning INS, for instance, machine learning can detect matches for names in different languages or alphabets or catch a hidden connection in a complex network of shell companies to find the ultimate beneficial owner.

A shell company is a business entity without business operations, activities or assets. While shell companies can be legitimate ways to carry out activities like holding assets, managing estate planning, or facilitating business transactions, they are primarily used for illicit activities like money laundering, tax evasion, hiding beneficial ownership, and other financial crimes.

Illegitimate shell companies have complex and obscure ownership structures to hide beneficial owners. They can carry out high-volume transactions without a clear business purpose and are frequently registered in jurisdictions that lack financial transparency.

Machine learning-based compliance software like Siron®One can conduct link analysis, analyze large datasets, and recognize patterns to detect shell companies and ultimate beneficial owners, enabling more accurate compliance processes.

Simplified Due Diligence (SDD) is a basic customer due diligence used for customer profiles or types of transactions that present a low risk, such as from a low-risk jurisdiction or a pre-established relationship with a customer.

SDDs require less documentation, and information is collected without extensive background checks. However, these profiles are also monitored and reviewed regularly.

Advanced compliance software like Siron One has a Simulation feature that allows users to run alternative scenarios to identify and understand risk, evaluate the effectiveness of current policies and programs, and develop better strategies and internal controls.

Using ML, predictive learning, and a no-code approach, Siron®One enables users to simulate realistic training scenarios, get hands-on experience without real-world consequences, stress tests, and improve compliance decision-making skills.

In the legacy Siron platform, Siron ACM is the alert and case management module that collects data from all relevant source systems, such as Siron AML and KYC and shows all alerts in a single environment for easy decision-making and reporting. It integrates with other compliance workflows and enables task queuing for seamless function.   

These capabilities exist in the new Siron®One platform but have been fine-tuned to provide more accuracy, better alert prioritization capability, and easy-to-understand visual representations. Alert and Case Management in the new Siron®One also enables alert hibernation and auto-complete based on defined business rules.   

In the legacy Siron platform, Siron AML is the anti-money laundering module, which receives several awards as the best-in-class AML solution. Siron AML uses advanced analytics to identify and report suspicious activities to better understand customers, relationships, and behavioral changes.

These capabilities have only been dialed up in the new Siron®One platform with the help of advanced machine learning algorithms and robotic process automation (RPA), which results in more accuracy, efficiency, and reduced costs. In the new platform, the AML feature can generate alerts with 90% accuracy.

In the legacy Siron platform, Siron Embargo is the sanction screening module that checks against real-time data for SWIFT, SEPA, watchlists such as OFAC, BoE, UN, World-Check, and other PEP lists, ensuring embargoed individuals, groups, and organizations on the list couldn’t access financial services, resources or instruments. It complies with the latest FATF recommendations.

In the new Siron®One platform, transaction sanction screening is a robust feature integrated with new-generation business rules and a multi-algorithm matching engine that not only prevents illegitimate transactions in real-time but also renders the lowest rate of false positives.

In the legacy Siron platform, Siron KYC is the know-your-customer module that also provides business partners’ due diligence and a complete lifecycle assessment of customer risk as part of the client onboarding process and ongoing customer monitoring. Dynamic data capturing, ongoing checks, risk rating, sanction, PEP checks, integration with all standard watchlist databases, and easy workflow-based case management have made Siron KYC an award-winning product.   

In the new Siron®Oneplatform, these capabilities are made even better by AI, RPA, document management, and end-to-end digital processes, which lead to increased automation and seamless customer experience, even for complex onboarding processes.   

In the legacy Siron platform, Siron RAS is the risk assessment feature that creates institution-specific risk analysis, taking into account the business environment, products, processes, and other applicable variables. It’s aligned with European regulatory authorities’ “guideline for generating a threat/risk analysis,” and supports complete and continuous threat analysis and management.

In the new Siron®One platform, dynamic risk scoring is a highly advanced feature that works continuously throughout the client lifecycle and is calculated based on AI clustering, deviations, client’s baseline information, historical transaction data, and dynamic data, including adverse media and sanctions. The risk scores in the new Siron®One platform help compliance officers prioritize investigations, enabling real-time decision making with speed and accuracy.

In the legacy Siron platform, Siron RCC or Reporting Compliance Cockpit provides a consolidated and visualized company-wide overview of all compliance related information in one place. It helped determine the status of tasks, showed pending actions, and enabled users to determine specific key performance indicators, monitor them, and show the effectiveness of the measures.  

In the new Siron®Oneplatform, in addition to the Siron RCC capabilities, the Case Manager provides a complete overview of compliance functions in one place, including one-click compliance reporting. Further, it’s integrated with the Customer 360 feature that pulls all relevant information about any case, historical data, risk scores, and alerts. The Smart View feature represents all the information visually, allows users to change views and generate graphs for better context and decision making.   

In the legacy Siron platform, Siron TCR is the Tax Compliance & Reporting module that makes FATCA and OECD CRS tax reporting fast and simple for banks, insurance companies, and businesses. This innovative module not only integrates seamlessly with the client’s IT environments and complied with tax regulations, but also ensures secure data transfer to IRS & national tax authorities during reporting.   

Siron®One’s AI-based automation, Optical Character Recognition (OCR) data capturing, document filing, and document management have enhanced its tax compliance capabilities, helping clients remain compliant across multiple jurisdictions with ease.   

Smurfing is a kind of money laundering technique where large sums are broken down into smaller amounts to avoid detection by regulatory authorities. The process of smurfing involves breaking down a large sum ideally structured to stay below $10,000 to avoid detection, carry out multiple transactions, either deposits or transfers across multiple banks or payment systems or accounts. Afterward, illicit money can be further layered to obscure transactions before it’s finally part of the legitimate economy.

Advanced AML and compliance tools like Siron®One can check for transaction volumes and patterns to detect and prevent smurfing.

In natural language processing (NLP) and text analysis, stopwords are common words that are typically filtered out during text processing, such as “and,” “the,” or “is.” Compliance software uses stopwords to streamline the analysis of textual data, reduce noise, and improve performance.

Stopwords enable more focus on keywords and better contextual understanding. When conducting adverse media searches using NLP, for example, compliance software can use a pre-defined list or a custom stopword list to render better results and enforce regulatory policies more effectively.

A Suspicious Transaction Report (STR), also known as a Suspicious Activity Report (SAR), is a part of AML/CFT compliance. All financial institutes and regulated businesses need to file an STR when they detect suspicious transactions or unusual activities.

The reports must be filed within 30 days of activity. STRs hold a nondisclosure clause where the contents of the report cannot be mentioned to any third party, and tipping off is punishable.

Filing STR helps financial institutes and FIUs work together to prevent money laundering, terrorist financing, and other crimes and hence is critical to any compliance program.

Suspicious activity refers to any transaction or behavior that deviates from the norm and could potentially indicate financial crime.

Suspicious activity is characterized by unusual transaction patterns, such as high-value or high-volume transactions, smurfing or frequent transactions. It could also be unusual behavior, like inconsistent use or layering a simple transaction to obscure funds.

Outside of deviations, suspicious activity could also stem from higher-risk jurisdictions or cross-border transactions.

Sustainable finance means considering ESG when investing to enable economic growth without adding pressure on the environment or contributing to social inequities.

Numerous regulatory frameworks for sustainable finance ensure adherence to ESG principles, such as the EU’s Sustainable Finance Disclosure Regulation (SFDR) and the Corporate Sustainability Reporting Directive (CSRD), the Equator Principles, the Task Force on Climate-related Financial Disclosures (TCFD) and more.

Swarm Learning is a method in which many ML models work together to train on specific data sets and periodically exchange their insights through encryption with other ML models or a central server. Swarm intelligence is used in Optical Character Recognition (OCR) to augment OCR capabilities.

Swarm Learning-based OCR allows data sharing while preserving privacy. It learns from multiple, diverse data sets at once, and the data can be deleted, but the learning can be retained for more efficiency and security.

Society for Worldwide Interbank Financial Telecommunication, or SWIFT, is a worldwide messaging network that provides a platform for transmitting messages about financial transactions. Financial institutions use SWIFT to safely and securely send and receive information about financial transactions, such as cross-border payments.

SWIFT connects 11,000 financial institutions in 200+ countries and regions and enables international trade by providing a common communication platform. It uses standardized messages for consistency and accuracy and codes what type of message for different financial transactions, such as payments, securities, trade finance, and treasury transactions.

SWIFT implements robust security measures, including encryption, authentication, and integrity checks, to protect data and it ensures high availability and reliability of the network, minimizing downtime and disruptions.

SWIFT Code or BIC Code is a unique identifier used in the international financial system to specify which financial institution is conducting the transaction. It’s primarily used for international wire transfers and exchanging other messages between banks.

The SWIFT/BIC code consists of 8-11 characters. The first 4 are the bank code, followed by the 2-letter country code, 2-letter location, and 3-letter branch code, which is optional.

Tax fraud is purposefully falsifying tax return information to avoid paying taxes owed. It can include such practices as under-reporting income, inflating deductions, hiding assets, claiming false exemptions, and submitting false documents.

Authorities such as the US Internal Revenue Service (IRS) actively investigate and prosecute such practices.

Trade-based money Laundering (TBML) is a complex and sophisticated way to launder money. It exploits international trade to transfer money/value while hiding its origins. TBML includes various techniques, such as over- or under-invoicing, multiple invoicing, over- or under-shipment, phantom shipping, payments to parties not involved in the trade, and mixing illegal and legal funds, making it difficult to differentiate the two.

TBML involves robust compliance processes, including KYC, CDD, trade monitoring, EDD for high-risk goods and geographies, intelligence sharing, reporting, recordkeeping for audits and investigations, collaboration, training, and assessments.

The Egmont Group facilitates intelligence sharing among FIUs globally to enhance the effort to fight financial crimes.

They are responsible for international collaboration among FIUs, training, establishing best practices, enforcing regulatory compliance, and leveraging technology in regulation.

Third-party verification is a method of assessment by independent organizations that a product or service meets standards, requirements, and claims. In the case of software, third-party verifications also ensure the product meets quality, safety, industry compliance, performance, and reliability standards.

The Three Lines of Defense (3LOD) is a regulatory compliance framework many organizations adopt for a comprehensive risk management system.

The 3LOD framework is optimal because it ensures the separation of responsibilities, roles are defined and appropriately allocated, and there is an unbiased review of compliance effectiveness and internal controls.

It consists of:

First Line of Defense: focused on daily operational management and control. It identifies and manages risk, implements and maintains internal controls, ensures compliance with applicable laws, regulations, and policies, and reports on risks and control effectiveness when needed.

Second Line of Defense: focused on providing oversight and support for risk management and compliance functions. It entails developing a comprehensive risk management framework, monitoring laws, regulations and internal policies, and providing guidance to the first LOD. The second LOD also conducts risk assessments and reporting and ensures compliance with regulatory and ethical standards.

Third Line of Defense: focused on internal audit and independent assurance. It provides an independent assessment of the effectiveness of internal controls, risk management, and governance processes as well as that of the first and second LODs, reports findings and recommendations, and ensures corrective actions are implemented.

Thresholds in compliance software are predefined limits that trigger specific actions or alerts when certain conditions are met. They help automate compliance workflows in processes like transaction monitoring.

Siron®One lets users define thresholds using the Rules Editor, as well as set the limits. Thresholds vary based on monetary value, frequency, customer risk score, historical data, patterns, and deviations, and geography.

Thresholds can help automate tasks in real-time monitoring, alert generation, prioritizing, escalating, or hibernating alerts, reducing false positives, and generating compliance reports.

Tokenization of Real-World Assets transfers ownership rights of a physical asset (like art, collectibles, securities, commodities) into a digital token stored on a blockchain. These tokens represent the whole or part of the asset, making it easier to divide, transfer, and manage. Tokenization allows fractional ownership, transparency due to immutable records, and faster transactions.

Tokenized assets need to comply with regulations, such as securities laws, and platforms that enable tokenization need to conduct AML/KYC.

Trade compliance relates to following all the laws, regulations, and policies governing international trade to ensure legal and ethical cross-border transactions.

Trade compliance is governed by export rules like the US International Traffic in Arms Regulations (ITAR) and the Export Administration Regulations (EAR), import regulations, sanctions and embargoes, such as from OFAC, custom compliance, trade agreements, documenting and recordkeeping of correct licenses and permits for audits and investigations, classifying products under the Harmonized System (HS) code and accurately determining their value for customs purposes, audits, and training and awareness.

Trade finance includes all financial instruments provided by banks and other institutions used by companies to conduct international trade, such as letters of credit, trade credit insurance, shipping and payment documents in compliance with the Uniform Rules for Collections (URC), supply chain financing, factoring and invoice discounting, and export and import loans.

Trade finance requires comprehensive compliance practices like AML/CFT, KYC, CDD/EDD, KYV/KYB, sanctions screening, transaction monitoring, fraud prevention, regulatory reporting, and customs and tax compliance.

Trade surveillance entails monitoring and analyzing trading activities to detect and prevent abuse, fraud, and criminal activities to protect investors and market integrity and ensure compliance.

Trade surveillance requires real-time, pre- and post-trade monitoring and analysis, using technology to comply with regulations from the SEC, FINRA, ESMA, and others. It is crucial for maintaining market integrity, protecting investors, and ensuring compliance with regulatory requirements.

Monitoring all transactions and detecting anomalies for transaction prevention, investigation, and reporting are mandatory practices in AML compliance.

Machine learning is helpful in each step, but particularly in detecting incongruence in transaction-related data or transaction deviation. Advanced predictive learning can adapt to and recognize new patterns and learn about emerging financial crimes and frauds to prevent them in real-time.

Siron®One uses advanced machine learning in addition to a rules-based system, behavioral analytics and clustering, and risk scoring to generate accurate alerts and fill out standard regulatory reports.

Transaction laundering is a form of money laundering where the origin and nature of funds are disguised by routing them through seemingly legitimate transactions, often using online storefronts or payment accounts.

Some of the known mechanisms of transaction laundering include hidden merchant accounts via shell companies or fake merchants, pass-through transactions where stores process both legitimate and illegitimate transactions, affiliate marketing schemes selling illicit products, or triangulation fraud, where criminals exploit legitimate businesses to sell illicit products unknown to the seller.

Transaction laundering red flags include:

• Unusual transaction or shipping patterns.
• Multiple accounts.
• Discrepancies in goods and services.
• Use of personal accounts.

The goal of transaction monitoring is to identify suspicious activity as close to the time it occurs to prevent fraud and other financial crimes, safeguard customers, and uphold the company’s reputation. All financial institutions are required to monitor customer transactions like money transfers, deposits, and withdrawals as part of their AML regulatory compliance program.

Transaction monitoring software flags suspicious activity based on pre-determined business rules and trigger events. Compliance officers assess the alerts to determine whether they’re a true positive and require filing a mandatory suspicious activity report.

Siron®One transaction monitoring combines a rules-based approach with advanced AI to generate accurate alerts in real-time. Transaction monitoring factors in customer risk profile, transaction deviation score, perpetual KYC, adverse media, and real-time trigger events to generate accurate alerts, reducing false positives.

Payment data and instructions for transactions made via SWIFT (Society for Worldwide Interbank Financial Telecommunication) are scrutinized to detect and prevent illegal activities such as money laundering, terrorist financing, and sanctions violations, as well as to ensure compliance with regulatory requirements.

Transaction screening in SWIFT involves sanctions screening, AML, CFT, and KYC, automated screening systems for real-time monitoring and a risk-based approach where alerts are managed according to priority.

A trigger event in compliance software is a specific occurrence that automatically activates a set of actions predefined within the system. Trigger events could include exceeding transaction thresholds, unusual transaction patterns, adverse media alerts, changes in customer profiles, changes in sanctions lists and regulations, and more.

Which process is triggered within the system depends on the event; for example, for exceeding the transaction threshold, the compliance software may trigger an EDD, or a negative news alert can trigger an adverse media screening process.

Trigger events help compliance accuracy and efficiency, better risk management, and resource allocation.

ML-based compliance software like Siron One generates alerts based on anomalies. In this context, true positives refer to alerts that the software correctly identifies as compliance risks and prioritizes alerts based on importance. Hence, true positive alerts are genuine risks that warrant investigation.

Especially in processes like real-time AML or transaction monitoring, true positives mean more efficient risk management and preventing crimes in real time.

An Ultimate Beneficial Owner (UBO) is the individual who ultimately owns or controls (and ultimately benefits from) a company or legal entity, even if it is indirect. UBOs can have indirect control and not be listed as a stakeholder but rather controls through intermediaries, such as holding companies or trusts.

Their position affords them economic benefits like dividends, profits, or assets, even if they are directed through a complex ownership structure.

Identifying UBOs is a mandatory part of compliance processes for the FATF, the EU’s Anti-Money Laundering Directives (AMLD), the US Patriot Act, and more.

Virtual Asset Service Providers (VASPs) are platforms that enable the exchange, transfer, safekeeping, administration, or issuance of virtual assets, such as NFTs, crypto exchanges or crypto wallet providers.

VASPs enable the exchange of virtual assets with other digital assets or fiat currency. They can also perform custodial services, such as safekeeping digital assets, and issuing services, such as Initial Coin Offerings (ICOs).

VASPs need to conduct AML/KYC and monitor and report suspicious transactions.

Vendor Due Diligence (VDD) is the due diligence process of vetting current or potential vendors to mitigate risk, regulatory compliance, operational continuity, and financial stability.
VDD includes financial evaluation, legal and regulatory compliance, operational assessment, data protection practices, insurance, and ESG reviews.

Public and commercial watchlists are databases containing information about individuals, entities, and countries under scrutiny, sanctions, or restrictions. It’s mandatory to check customers against these watchlists for compliance processes like KYC, CDD/EDD, and transaction monitoring for initial and dynamic risk assessment.

Public watchlists are government issued and include sanctions lists from agencies like the United Nations Security Council sanctions list, the U.S. Office of Foreign Assets Control (OFAC) Specially Designated Nationals (SDN) list, and the European Union sanctions list, Politically Exposed Persons (PEP) Lists, and Terrorist Watchlists including the U.S. Terrorist Screening Database (TSDB) and the European Union Terrorist List.

Commercial watchlists are put together and updated by private organizations and include Credit Watchlists, AML, Watchlists Fraud Watchlists, and Compliance Watchlists.

In watchlist screening, individuals, entities, and transactions are checked against various watchlists to identify and prevent engaging with sanctioned or high-risk entities. Watchlists can include sanction lists, PEPs, and lists of entities involved in terrorism, money laundering, fraud, and other illegal activities.

Watchlist screening complements other compliance processes like KYC and transaction monitoring for regulatory compliance.

Wealth management and private banking include personalized investment advice, financial planning, asset management, and other financial services tailored specifically for high-net-worth individuals (HNWIs) and ultra-high-net-worth individuals (UHNWIs).

Wealth management encompasses investment management, tax planning, estate planning, retirement planning, holistic financial advice and strategies to help clients grow, preserve, and transfer their wealth.

Private banking services include bespoke investment solutions, lending services, personalized banking products, exclusive access to financial markets and investment opportunities personalized for HNWIs.

Web3 is the next evolution of the Internet, powered by decentralized technologies like blockchain. It is meant to be more open, secure, and user centric. Web3 uses P2P networks and decentralized applications (dApps) to give users more control over their data and interactions.

Some of Web3’s applications are DeFi, NFT, DAO, and dApps. Due to its transparency, inclusivity, and data ownership capabilities, Web3 represents a tectonic shift in the way people use the Internet.

In compliance, a whitelist is a list of individuals, companies, or IP addresses deemed safe and trustworthy and allowed to carry out certain activities without scrutiny. It’s a proactive security measure to streamline compliance. A whitelist can be used for CDD, KYV, access control, and transaction monitoring.

However, it requires rigorous initial vetting and approval to ensure only trustworthy entities are whitelisted.

Wire fraud entails transmitting false or misleading information through email or phone to carry out fraudulent scams. Common wire frauds include phishing, business email compromise, investment fraud, online auction fraud, and advance fee scams.

Wire frauds have civil and criminal penalties, and preventative measures like multi-factor authentication are important to stopping them.

Wire stripping involves removing or altering information in wire transfer messages to hide the involvement of sanctioned entities or countries to evade regulatory sanctions.

Wire stripping can include complicity or negligence on the part of financial institutions that allow transactions to go through without detecting tampering.

Wire stripping is a severe crime and can have legal and financial penalties.

The Wolfsberg Group is a group of banks that collaborate to develop and promote industry standards for AML and CTF, understand and implement KYC principles, and provide guidance for managing financial crime risks.

The banks, initially 11, now include 13 global banks: Bank of America, Bank of Tokyo-Mitsubishi UFJ, Barclays, Citigroup, Credit Suisse, Deutsche Bank, Goldman Sachs, HSBC, JPMorgan Chase, Morgan Stanley, Société Générale, Standard Chartered, and UBS.

The Wolfsberg Group publishes a series of Principles for AML, CFT, Correspondent Banking, and Trade Finance.

AI workflow automation streamlines entire processes or steps within a business process that are data-, labor-, resource-intensive and often error-prone, thus improving efficiency and productivity and enabling humans to focus on more complex and strategic work.

Various kinds of AI process automation use subsets of AI, including machine learning and predictive analytics. Rules-based automation has widespread application in compliance because by defining business rules, limits, and deviations, AI models can autocomplete a task such as hibernating an alert, extracting data and filling up reports, guiding users on the types of documents required for onboarding, and more.

AI workflow automation is also invaluable to monitoring all transactions and creating audit logs, a time-consuming and repetitive process critical to compliance.

Siron®One uses RPA to automate workflows, reduce costs, and increase efficiency while ensuring data quality and integrating with existing systems.

Zero-knowledge proof (ZKP) is a cryptographic method where one party can prove certain information without revealing the actual information, allowing interactions to occur privately and securely.

Zero-knowledge refers to the fact that the person seeking the verification learns nothing about it other than that it’s true. ZKP is ideal in a trustless environment (where information exchange doesn’t depend on trust), such as crypto, data sharing, decentralized voting, and other authentication requirements.

ZV/2 is a state-of-the-art payment processing recognition and orchestration engine that helps financial institutions automate and digitize time-critical processes. ZV/2 can handle a broad spectrum of payment types and is ready to handle QR-code-based payment slips.  

ZV/2 can easily handle incoming and outgoing payments, forms and non-standardized documents, Post Finance EGA-B/EGA-V, automation for pay way, correspondent and correspondent banking, and integrates with core banking and archiving systems as well as all IMTF modules.