RISK CALCULATION
Using a flexible risk calculation engine that takes input from the context of transaction and thresholds, a cumulative score is generated from the applicable rules.
Machine Learning
With the kind of technology available to even potential fraudsters today, machine learning has become an important component of any FRM engine. While a rule-based engine is a very good tool to detect known fraud patterns, it isn’t as efficient when it comes to detecting emerging fraud patterns, or fraud that is being conducted using sophisticated tools. This is where the importance of machine learning in the FRM space comes into being. Come make use of EPAPL’s machine learning based FRM engine.
Artificial Intelligence
Make use of EPAPL’s AI-driven FRM module to stay one step ahead of fraudsters. New fraud patterns emerging in your payment ecosystem? Thanks to our AI based FRM engine, you can ensure the solution will pick up these patterns and assist in ensuring your organizations customers are saved from Fraud.
REPORTING
Provides multiple detailed reports related to simulation history, risk calculation rules, number of frauds detected under each rule, list of suspicious holders, merchants and transactions.
MANAGEMENT OF FRAUD CASES AND THEIR ALERTS
Suspected fraud transactions for a cardholder or merchant are assigned to an investigator and are tracked with real-time alerts. The updates can be provided to concerned merchant, Branch Manager, Security Manager and the Consumer. If the fraud is proven then the findings can be shared with local and international law enforcement and anti-fraud networks.
MANAGEMENT OF AUTOMATED PROCESSES
Decision is taken by automated processing based on the cumulative risk score. Cardholder history of fraud, card cancellations and past due are taken in to consideration while taking a decision to approve transactions. The fraud detection engine can also interact with external modelling systems using API to get a risk score. The decisions are provided to the Authorization System for further action.
MANAGEMENT OF RISK RULES
A rule-based library can be created using various parameters from the transaction to generate a score. A simulator software tool is available to test any new rules for reliability, before deploying it.
BENEFITS
CARDHOLDER
The cardholder is ensured a high level of safety during any channel of transaction. Moreover, litigation cases are dealt with swiftly and transparently.
CLIENT
The client is able to reduce issuer and acquirer fraud altogether through real-time prevention, automated processing and alerts, behavior pattern analysis and tracking suspicious profiles. Also, the solution enables swift reactivity to new fraudulent methods by setting up new rules