byMaud Vonlanthen on 01 Oct. 2021
Financial crime has increased in recent years and is constantly evolving. With total combined fraud losses reaching a record high of $56 billion in 2020, financial organisations around the world are facing a growing challenge from fraudsters who are becoming increasingly sophisticated and inventive in their approaches.
The Covid-19 pandemic has also proven to be a fertile environment for fraud: the increase in e-commerce and digital transactions, coupled with a heightened sense of consumer vulnerability and anxiety, has created new channels for fraudsters to exploit.
To combat fraud, financial organisations have to deal with a significant volume of data, which is extremely complex and time-consuming to analyse. This has created the need for automated real-time fraud detection and prevention techniques. With ongoing technological disruptions across various industries, RegTech solutions have expanded greatly to assist financial organizations in identifying and preventing all types of FinCrime.
A comprehensive fraud detection and prevention solution must cope with very different scenarios, fraud typologies and channels by combining multiple capabilities of detection analytics and assisted investigation, to ultimately identify and prevent such attacks. Traditional Fraud Detection systems often rely on hundreds of static rules that normally fail to detect new fraud patterns and create a large number of false positives alerts.
To make the difference and to be truly effective on an operational level, a fraud detection system must offer several key features:
The capacity to monitor all transactional and events from various channels in real-time, typically based on a smart combination of several technologies including dynamically updated profiles, advanced analytics and AI risk models
The capability to easily integrate and process non-transactional events from every stream and in every format (employee datapoints, phone calls, emails, …) and to score against a predefined, yet flexible, risk model
The integration of cutting-edge entity resolution (ID proofing) and AI-based matching algorithms
Efficient fraud operation thanks to investigation and case management tools, that do not negatively affect user experience
Efficiently setting up and managing a real-time fraud detection & prevention system requires a thoughtful strategy including all of the above features. Based on these principles and combining IMTF’s industry expertise, the IMTF RegTech fraud detection & prevention module helps to deliver outstanding performance in a wide range of fraud areas such as online, payment and internal fraud as well as many other real-time detections.
Our fraud use cases and best practices include:
Application & Claims fraud (integrity of the login process to prevent account takeover)
Enterprise Payment fraud
Internal fraud, employee collusion, policy violations or theft
Online & Mobile banking fraud
Debit and Credit Card fraud
The IMTF engine is a comprehensive offering based on a combination of advanced analytics, dynamic profiling, and machine learning including all necessary orchestration features. AI scores and risk models spot and identify in real-time fraud and fraud attempts on any channel. Suspicious transactions are blocked in real-time, and alerts are immediately available in our Adaptive Case Manager to the appropriate staff for swift and user-friendly resolution.
The key benefits of the IMTF RegTech fraud detection & prevention module are:
An integrative approach combining various real-time models for a very high-quality detection of a variety of fraud types
Unrivalled operational efficiency and customer experience: the greatly reduced number of false positives results in fewer legitimate transactions being blocked for verification with all the undesirable consequences!
What is your method to stay ahead of fraudsters?