By: Heather Grover In past client and industry talks, I’ve discussed the increasing importance of retail branches to the growth strategy of the bank. Branches are the most utilized channel of the bank and they tend to be the primary tool for relationship expansion. Given the face-to-face nature, the branch historically has been viewed to be a relatively low-risk channel needing little (if any) identity verification – there are less uses of robust risk-based authentication or out of wallet questions. However, a now well-established fraud best practice is the process of doing proper identity verification and fraud prevention at the point of DDA account opening. In the current environment of declining credit application volumes and approval across the enterprise, there is an increased focus on organic growth through deposits.  Doing proper vetting during DDA account openings helps bring your retail process closer in line with the rest of your organization’s identity theft prevention program. It also provides assurance and confidence that the customer can now be cross-sold and up-sold to other products. A key industry challenge is that many of the current tools used in DDA are less mature than in other areas of the organization. We see few clients in retail that are using advanced fraud analytics or fraud models to minimize fraud – and even fewer clients are using them to automate manual processes – even though more than 90 percent of DDA accounts are opened manually. A relatively simple way to improve your branch operations is to streamline your existing ID verification and fraud prevention tool set: 1. Are you using separate tools to verify identity and minimize fraud? Many providers offer solutions that can do both, which can help minimize the number of steps required to process a new account; 2. Is the solution realtime? To the extent that you can provide your new account holders with an immediate and final decision, the less time and effort you’ll spend after they leave the branch finalizing the decision; 3. Does the solution provide detail data for manual review? This can help save valuable analyst time and provider costs by limiting the need to do additional searches. In my next post, we’ll discuss how fraud prevention in DDA impacts the customer experience.

By: Amanda Roth The final level of validation for your risk-based pricing program is to validate for profitability.  Not only will this analysis build on the two previous analyses, but it will factor in the cost of making a loan based on the risk associated with that applicant.  Many organizations do not complete this crucial step.  Therefore, they may have the applicants grouped together correctly, but still find themselves unprofitable. The premise of risk-based pricing is that we are pricing to cover the cost associated with an applicant.  If an applicant has a higher probability of delinquency, we can assume there will be additional collection costs, reporting costs, and servicing costs associated with keeping this applicant in good standing.  We must understand what these cost may be, though, before we can price accordingly.  Information of this type can be difficult to determine based on the resources available to your organization.  If you aren’t able to determine the exact amount of time and costs associated with the different loans at different risk levels, there are industry best practices that can be applied. Of primary importance is to factor in the cost to originate, service and terminate a loan based on varying risk levels.  This is the only true way to validate that your pricing program is working to provide profitability to your loan portfolio.  

The definition of account management authentication is:  Keep your customers happy, but don’t lose sight of fraud risks and effective tools to combat those risks. In my previous posting, I discussed some unique fraud risks facing institutions during the account management phase of their customer lifecycles.  As a follow up, I want to review a couple of effective tools that allow you to efficiently minimize fraud losses during post-application: Knowledge Based Authentication (KBA) — this process involves the use of challenge/response questions beyond "secret" or "traditional" internally derived questions (such as mother's maiden name or last transaction amount). This tool allows for measurably effective use of questions based on more broad-reaching data (credit and noncredit) and consistent delivery of those questions without subjective question creation and grading by call center agents. KBA questions sourced from information not easily accessible by call center agents or fraudsters provide an additional layer of security that is more impenetrable by social engineering. From a process efficiency standpoint, the use of automated KBA also can reduce online sessions for consumers, and call times as agents spend less time self-selecting questions, self-grading responses and subjectively determining next steps. Delivery of KBA questions via consumer-facing online platforms or via interactive voice response (IVR) systems can further reduce operational costs since the entire KBA process can be accommodated without call center agent involvement. Negative file and fraud database – performing checks against known fraudulent and abuse records affords institutions an opportunity to, in batch or real time, check elements such as address, phone, and SSN for prior fraudulent use or victimization.  These checks are a critical element in supplementing traditional consumer authentication processes, particularly in an account management procedure in which consumer and/or account information may have been compromised.  Transaction requests such as address or phone changes to an account are particularly low-hanging fruit as far as running negative file checks are concerned.