Building a better banking world The benefits of a unified approach to fighting fraud

There's a reason why many industry analyst firms such as Chartis Research and Frost & Sullivan are evaluating antifraud technologies based on their ability to provide an integrated, platform-based approach: It's simply the best way to get the most accurate, complete and cost-effective picture of fraud within an organization. Yet the norm is still to have multiple anti-fraud and anti-money laundering systems across different business units. Ellen Joyner-Roberson, Financial Services Marketing Manager at SAS, explains that a unified framework for handling financial crimes allows an organization to manage fewer vendors, enhance operational efficiency and ultimately reduce fraud. "In a perfect world, everything must be handled within an enterprise framework where the right information is reported to the right people at the right time," Joyner-Roberson says. As banking evolves with new business channels, these channels can pose new risks. The first concern, Joyner-Roberson points out, is to know and authenticate customers so you know whom you're doing business with. This is easier said than done, which is why a layered defense should be used. Banks must take a 360-degree view of their customer using all available information. And then, when it is time to roll out new products, fraud risks must be incorporated before going to market. "Fraud isn't always top of mind and needs a seat at the table," Joyner-Roberson says. "Some are moving into this process and addressing mitigating factors, but it's been a slow process." Joyner-Roberson provided the example of no-doc loans. "There was tremendous risk here, but the revenue outweighed the risks." Banks will continue to build service-oriented architectures to reduce application redundancy, ensure data integrity, facilitate data sharing and lower overall maintenance costs. Including all available data, along with predictive analytics, will be essential for the effective evolution of fraud management. An enterprise data model that understands cross-channel products, lines of business and industry-specific items to better manage operational needs should push some significant improvements in scoring customers and reducing financial crime risk. "You should be able to go back post- event and use rich information to build better models, generate trends and forecasts, and determine how new products and lines of business will impact financial crimes and the operational environment," Joyner-Roberson says. "You also should be able to incorporate all available data types - customer, household, merchant download