In today's dynamic fraud detection landscape, combining AI-driven techniques with a well-structured rules strategy is crucial. While AI excels at identifying complex fraud patterns, rule-based strategies offer a targeted approach to manage both clear-cut and subtle fraudulent activities. This guide will help you develop a balanced fraud risk management strategy by aligning rules with your specific business objectives and industry demands, ensuring a comprehensive defense against fraud. Whether you're building from scratch or refining an existing system, this resource provides essential insights to enhance your fraud prevention efforts.
Before implementing any rules, it is important to clearly define a solid Fraud Risk Management Strategy. It involves defining and managing the risks associated with fraudulent activities by evaluating the risk levels of transactions, clients, and segments. This strategy should align with key stakeholders, such as Finance and Marketing, to ensure an integrated approach.
The main components and goals of a Fraud Risk Management Strategy include:
By focusing on these areas, you can develop a comprehensive approach that safeguards your business, enhances profitability, and maintains customer trust.
When evaluating your risk, it is essential to have clear KPIs and to know your profit margins:
KPI’s and Monitoring
As a business you need to realize what KPI’s are important to you and set up reporting to have clear visibility to be able to pinpoint where fraud is coming from. Generally the Fraud Rate and Chargeback rate are the most critical KPIs, however when you start to decline transactions for risk its very important that you are not declining too many good customers. Therefore monitoring your decline rates and analyzing false positives becomes very important, it can be detrimental to your business if you start turning away good customers as they are likely to not come back.
At the bare minimum you should be monitoring the following: