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In case you’ve never heard of it, a Babel fish is a small translator; that allows a carrier to understand anything said in any form of language. Alta Vista popularized the name but I believe Douglas Adams, author of The Hitchhiker’s Guide to the Galaxy, should be given credit for coining the term. So, what does a Babel fish have to do with Knowledge Based Authentication? Knowledge Based Authentication is always about the data – I have said this before. There is one universal truth: data doesn’t lie. However, that doesn’t mean it is easy to understand what the data is saying. It is a bit like a foreign language. You may have taken classes, and you can read the language or carry on a passable conversation, but that doesn’t mean it’s a good idea to enter into a contract – at least, not without an attorney who speaks the language, or your very own Babel fish. Setting up the best Knowledge Based Authentication configuration for risk management of your line of business can sometimes seem like that contract in a foreign language. There are many decisions to be made and the number of questions to present and which questions to ask is often the easy part. To truly get the most out of fraud models, it is necessary to consider where the score cuts that will be used with your Knowledge Based Authentication session will be set and what methodology will be used to invoke the Knowledge Based Authentication session: objective score performance, manual review and decision, etc. It is also important to consider the “kind of fraud” you might be seeing. This is where it is helpful to have your very own Babel fish – one designed specifically for fraud trends, fraud data, fraud models and Knowledge Based Authentication. If your vendor doesn’t offer you a Babel fish, ask for one. Yours could have one of many titles, but you will know this person when you speak with them, for their level of understanding of not only your business but, more importantly, your data and what it means. Sometimes the Babel fish will work in Consulting, sometimes in Product Management, sometimes in Analytics – the important thing is that there are fraud-specific experts available to you. Think about that for a minute. Business today is a delicate balance between customer experience/relationship management and risk management. If your vendor can’t offer you a Babel fish, tell them you have fish to fry – elsewhere.

By: Staci Baker With the increase in consumer behaviors such as ‘strategic default’, it has become increasingly difficult during the past few years for lenders to determine who the most creditworthy consumers are – defining consumers with the lowest credit risk. If you define risk as ‘the likelihood of [a consumer] becoming 90 days or more past due’, the findings are alarming. From June 2007 to June 2009, Super Prime consumers (those scoring 900 or higher) in the U.S. have gone from an average VantageScore® credit score* of 945 to 918, which increased their risk level from approx. 0.12% to 0.62% – an increase of 417% for this highly sought after population! Prime and near prime risk levels increased by 400% and 96% respectively. Whereas subprime consumers with few choices (stay subprime or improve their score), saw a slight decrease in risk, 8% – increasing their average VantageScore® credit score from 578 to 599. So how do lenders determine who to lend to, when the risk level for all credit tiers increases, or remain risky? In today’s dynamic economy, lenders need tools that will give them an edge, and allow them to identify consumer trends quickly. Incorporating analytic tools, like Premier Attributes, into lender’s origination models, will allow them to pinpoint specific consumer behavior, and provide segmentation through predefined attribute sets that are industry specific and target profitable accounts to improve acquisition strategies. As risk levels change, maintaining profitability becomes more difficult due to shrinking eligible consumer pools. By adding credit attributes, assessing credit risk both within an organization and for new accounts will be simplified and allow for more targeted prospects, thus maximizing prospecting strategies across the customer lifecycle and helping to increase profitability. * VantageScore®, LLC, May, 2010, “Finding Creditworthy Consumers in a Changing Economic Climate”

We've blogged about fraud alerts, fraud analytics, fraud models and fraud best practices. Sometimes, though, we delude ourselves into thinking that fraud prevention strategies we put into place today will be equally effective over time. Unfortunately, when a rat finds a dead-end in a previously-learned maze, it just keeps hunting for an exit. Fraudsters are no different. Ideally we want to seal off all the exits, and teach the rats to go and do something productive with their lives, but sadly that is not always the case. We also don't want to let too many good consumers get stuck either, so we cannot get too trigger-happy with our fraud best practices. Fraud behavior is dynamic, not static. Fraudsters learn and adapt to the feedback they receive through trial and error. That means when you plug a hole in your system today, there will be an increased push to seek out other holes tomorrow. This underscores the importance of keeping a close eye on your fraudsters' behavior trends. But there must be some theoretical breaking point where the fraudsters simply give up trying–at least with your company. This behavioral extinction may be idealistic in the general sense, but is nonetheless a worthy goal as related to your business. One of the best things you can do to prevent fraud is to gain a reputation amongst the fraudsters of, "Don't even try, it's not even worth it." And even if you don't succeed in getting them to stop trying altogether, it's still satisfying to know you are lowering their ROI while improving yours


