A lot of businesses nowadays already have a fraud prevention program in place. In some circumstances, the fraud program may be highly advanced, while in others, it may still be in its early stages. There are steps that could be made to increase the efficiency and efficacy of a fraud program, regardless of its maturity.
While a variety of metrics can measure a fraud program, the amount/percentage of fraud discovered and mitigated and the potential fraud loss saved are two of the most important ones. There are certain steps businesses can take to strengthen their fraud programs to face attackers and fraudsters that are always adapting and evolving.
Following are some ways to improve a fraud program, regardless of its maturity level:
Augment the intelligence:
As attackers and fraudsters change and evolve, so do their tactics and strategies. While individual businesses may be able to keep up with some of these developments, achieving the breadth required to resist the continually changing threat landscape is practically difficult. Fraud teams can increase their reach, visibility, and capacity by combining resources and seeking out vendors who specialize in remaining current. Finding ways to integrate that intelligence into the fraud team’s day-to-day activities smoothly and efficiently is preferable to merely enhancing the team’s intelligence.
Supplement the telemetry data:
The fraud team may examine individual transactions or groups of transactions. Alternatively, perhaps the team examines log data for established patterns of activity. Alternatively, perhaps there are a collection of rules, signatures, and thresholds that run across one or more data sets and are ready to trigger when a match is struck. Businesses should look at the end-user path through the application and the end-behavior users inside that trip. Telemetry data can be incredibly significant, providing unique insight and context into a wide range of events, requests, and transactions. This knowledge and context work together to assist in better decision-making. To put it another way, they lead to more accurate and reliable fraud detection.
Deciding whether or not a specific behavior is fraudulent is rarely a simple issue. Rather, the possibility of anything being fraudulent is a probability depending on a variety of criteria. The quality and accuracy of this judgment, like any probability-based decision, are determined by a variety of criteria, including the input data’s quality and accuracy, as well as the data’s breadth and coverage. As a result, refining, augmenting, and supplementing the data used to determine which behaviors are potentially fraudulent, can help firms detect and mitigate fraud more accurately. A higher number of real positives can be detected more easily, while the number of false positives and false negatives will be reduced. All of this bodes well for the anti-fraud program.
Examining individual transactions or activities within the application is insufficient. Rather, a more comprehensive picture of what is happening in the session as a whole is required. Simply put, actual consumers don’t always live inside the confines of thresholds or a well-defined set of rules. Only by examining sessions and all of the essential context they supply can fraud teams break free from a never-ending diet of false positives and enhance their performance.