The rise of the digital channel lead to a rise in new types of fraud – like cryptocurrency and buy now, pay later scams. While the scams themselves are new, they’re based on tried-and-true schemes like account takeover and synthetic identity fraud that organizations have been working to thwart for years, once again driving home the need for a robust fraud solution. While the digital channel is extremely attractive to many consumers due to convenience, it represents a balancing act for organizations – especially those with outdated fraud programs who are at increased risk for fraud. As organizations look for ways to keep themselves and the consumers they serve safe, many turn to fraud risk mitigation. What are fraud risk management strategies? Fraud risk management is the process of identifying, understanding, and responding to fraud risks. Proper fraud risk management strategies involve creating a program that detects and prevents fraudulent activity and reduces the risks associated with fraud. Many fraud risk management strategies are built on five principles: Fraud Risk AssessmentFraud Risk GovernanceFraud PreventionFraud DetectionMonitoring and Reporting By understanding these principles, you can build an effective strategy that meets consumer expectations and protects your business. Fraud risk assessment Fraud protection begins with an understanding of your organization’s vulnerabilities. Review your top risk areas and consider the potential losses you could face. Then look at what controls you currently have in place and how you can dial those up or down to impact both risk and customer experience. Fraud risk governance Fraud risk governance generally takes the form of a program encompassing the structure of rules, practices, and processes that surround fraud risk management. This program should include the fraud risk assessment, the roles and responsibilities of various departments, procedures for fraud events, and the plan for on-going monitoring. Fraud prevention “An ounce of prevention is worth a pound of cure.” This adage certainly rings true when it comes to fraud risk management. Having the right controls and procedures in place can help organizations stop a multitude of fraud types before they even get a foot in the door. Account takeover fraud prevention is an ideal example of how organizations can keep themselves and consumers safe. Fraud detection The only way to stop 100% of fraud is to stop 100% of interactions. Since that’s not a sustainable way to run a business, it’s important to have tools in place to detect fraud that’s already entered your ecosystem so you can stop it before damage occurs. These tools should monitor your systems to look for anomalies and risky behaviors and have a way to flag and report suspicious activity. Monitoring and reporting Once your fraud detection system is in place, you need active monitoring and reporting set up. Some fraud detection tools may include automatic next steps for suspicious activity such as step-up authentication or another risk mitigation technique. In other cases, you’ll need to get a person involved. In these cases it’s critical to have documented procedure and routing in place to ensure that potential fraud is assessed and addressed in a timely fashion. How to implement fraud risk management By adhering to the principles above, you can gain a holistic view of your current risk level, determine where you want your risk level to be, and what changes you’ll need to make to get there. While you might already have some of the necessary tools in place, the right next step is usually finding a trusted partner who can help you review your current state and help you use the right fraud prevention services that fit your risk tolerance and customer experience goals. To learn more about how Experian can help you leverage fraud prevention solutions, visit us or request a call. Learn more
Part 3 in our series on Insights from the Vision 2016 fraud and identity track Our Vision 2016 fraud track session titled “Deployment Made Easy — solving new fraud problems by Adapting Legacy Solutions” offered insights into the future of analytics and the mechanisms for delivering them. The session included two case studies, the first of which highlighted a recently completed project in which an Experian client struggling with rising application fraud losses had to find a way to deploy advanced analytics without any IT resources. To assist the customer, data passing through an existing customer interface was reformatted and redirected to our Precise ID® platform. Upon arrival in Precise ID, a custom-built fraud scoring model was invoked. The results were then translated back into the format used by the legacy interface so that they could be ingested by the customer’s systems. This case study illustrates the key value proposition of Experian’s new CrossCoreTM fraud and identity platform. CrossCore features a similar “translation layer” for inquiries coming into Experian’s fraud and identity tools that will allow customers to define fraud-screening workflows that call a variety of services. The IT burden for connecting the inquiry to various Experian and non-Experian services will fall on Experian — sparing the customer from the challenge of financing and prioritizing IT resources. Similarly, the output from CrossCore will provide a ready-to-consume response that integrates directly with our customers’ host systems. The audience showed keen interest in the “here and now” illustration of what CrossCore will enable. Our second case study was provided by Eric Heikkila at Amazon Web Services™ and focused on the future of analytics. For an audience accustomed to the constraints of developing advanced analytics in a rigid data-structure, Amazon’s description of a “data lake” was a fascinating picture of what’s possible. The data lake offers the simultaneous ability to accommodate existing structured customer data along with new unstructured data in an infinitely scalable data set. Equally important is the data lake’s ability to accommodate an unlimited array of data mining and analytical tools. Amazon’s message was clear and simple — the fraud industry’s trepidation around the use of big data is misplaced. The fear of making the wrong choice of data storage and analytical tools is unnecessary. To illustrate this point, Eric shared an Amazon Web Services case study that used FINRA (Financial Industry Regulatory Authority). FINRA is responsible for overseeing U.S. securities markets to ensure that rules are followed and integrity is maintained. Amid a bewildering set of ever-changing regulations and peak volumes of 35 trillion per day — yes, trillion — Amazon’s data lake supports both the scale and analytical demands of a complex industry. As the delivery and access to fraud products is made easy by CrossCore, the data and analytics will expand through the use of services like Amazon’s data lake. As the participants will agree, the future of fraud technology is closer than you think!