By: Mike Horrocks Have you ever been struck by a turtle or even better burnt by water skies that were on fire?  If you are like me, these are not accidents that I think will ever happen to me and I'm not concerned that my family doctor didn't do a rotation in medical school to specialize in treating them. On October 1, 2013, however, doctors and hospitals across the U.S. will have ability to identify, log, bill, and track those accidents and thousands of other very specific medical events.  In fact the list will jump from a current 18,000 medical codes to 140,000 medical codes.  Some people hail this as a great step toward the management of all types of medical conditions, whereas others view it as a introduction of noise in a medical system already over burdened.  What does this have to do with credit risk management you ask? When I look at the amount of financial and non-financial data that the credit industry has available to understand the risk of our consumer or business clients, I wonder where we are in the range of “take two aspirins and call me in the morning” to “[the accident] occurred inside a chicken coop” (code: Y9272).   Are we only identifying a risky consumer after they have defaulted on a loan?  Or are we trying to find a pattern in the consumer's purchases at a coffee house that would correlate with some other data point to indicate risk when the moon is full? The answer is somewhere in between and it will be different for each institution.  Let’s start with what is known to be predictable when it comes to monitoring our portfolios – data and analytics, coupled with portfolio risk monitoring to minimize risk exposure – and then expand that over time.  Click here for a recent case study that demonstrates this quite successfully with one of our clients. Next steps could include adding in analytics and/or triggers to identify certain risks more specifically. When it comes to risk, incorporating attributes or a solid set of triggers, for example, that will identify risk early on and can drill down to some of the specific events, combined with technology that streamlines portfolio management processes – whether you have an existing system in place or in search of a migration – will give you better insight to the risk profile of your consumers. Think about where your organization lies on the spectrum.    If you are already monitoring your portfolio with some of these solutions, consider what the next logical step to improve the process is – is it more data, or advanced analytics using that data, a combination of both, or perhaps it's a better system in place to monitoring the risk more closely. Wherever you are, don’t let your institution have the financial equivalent need for these new medical codes W2202XA, W2202XD, and W2202XS (injuries resulting from walking into a lamppost once, twice, and sequentially).

The rash of large-scale data breaches in the news begs many questions, one of which is this: how do hackers select their victims?

By: Mike Horrocks Let’s all admit it, who would not want to be Warren Buffet for a day?  While soaking in the tub, the “Sage of Omaha” came up with the idea to purchase shares of Bank of America and managed to close the deal in under 24 hours (and also make $357 million in one day thanks to an uptick in the stock). Clearly investor opinions differ when picking investments, so what did Buffet see that was worth taking that large of a risk? In interviews Buffet simply states that he saw the fundamentals of a good bank (once they fix a few things), that will return his investment many times over. He has also said that he came to this conclusion based on years of seeing opportunities where others only see risk. So what does that have to do with risk management? First, ask yourself as you look at your portfolio of customers what ones are you  “short-selling”  and risk losing and what customers are you investing into and expect Buffet-like returns on in the future? Second, ask yourself how are you making that “investment” decision on your customers? And lastly, ask yourself how confident you are in that decision? If you’re not employing some mode of segmentation today on your portfolio stop and make that happen as soon as you are done reading this blog. You know what a good customer looks like or looked like once upon a time. Admit to yourself that not every customer looks as good as they used to before 2008 and while you are not “settling”, be open minded on who you would want as a customer in the future. Amazingly, Buffet did not have Bank of America’s CEO Brian Moynihan’s phone number when he wanted to make the deal. This is where you are heads and shoulders above Garot’s Steak House’s favorite customer.  You have deposit information, loan activity and performance history, credit data, and even the phone number of your customers. This gives you plenty of data and solutions to build that profile of what a good customer looks like – thereby knowing who to invest in. The next part is the hardest. How confident are you in your decision that you will put your money on it? For example, my wife invested in Bank of America the day before Warren put in his $5 billion. She saw some of the same signs that he did in the bank. However, the fact that I am writing this blog is an indicator that she clearly did not invest to the scale that Warren did. But what is stopping you from going all in and investing in your customers’ future? If the fundamentals of your customer segmenting are sound, any investment today into your customers will come back to you in loyalty and profits in the future. So at the risk of conjuring up a mental image, take the last lesson from Warren Buffet’s tub soaking investment process and get up and invest in those perhaps risky today, yet sound tomorrow customers or run the risk of future profits going down the drain.