Fraud experts at many financial institutions know they need to do more to deter and detect fraud. But many have already spent tremendously on simple solutions. Unable to accurately measure success of their existing efforts, they find it difficult to explain to executives where their institution stands now and what it needs to do next.
Fortunately, today’s advanced analytics provide a means for organizations to sift through volumes of data and transactions to make intelligent, real-time decisions as to whether a transaction is fraudulent and what steps should be taken. In a world where fraud schemes have spread across the enterprise, data management and analytics are core to stopping fraud while avoiding over-zealous false alarms that annoy customers.
Banks have deep data about customer banking behavior to support their fraud detection efforts. This is crucial, because banks must know and authenticate their legitimate customers to avoid being tricked by fraudsters. This is not as easy to do as it sounds, because it requires banks to capture a 360-degree customer view using all available information.
To identify and stop an array of fraud attacks quickly and accurately – while improving customer experiences – banks must:
- Capture and unify all available data types from across channels, – customer, household, merchant, third-party and issuer-specific data, authorizations, deposits and non-monetary transactions – and incorporate it into the analytical process.
- Continually monitor transactions and apply behavioral analytics to enable real-time decision making.
- Employ layered security techniques.
An enterprise fraud management solution must have rules for routing and case management, as well as the ability to capture fraud, enforce anti-money laundering policies and flag transactions that need review. Analytics underlies any effective solution – and the fraud management technology that banks choose should be able to learn from complex data patterns and use sophisticated decision models to better manage false positives.
With these techniques in place, banks should be able to use rich information after the event to build better models, generate trends and forecasts, and determine how new products and lines of business will affect financial crimes and the operational environment.
Read the latest research from the Fraud Management Institute.