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Monitoring risk factors – the distinction of risk analysis and data paralysis

September 19, 2011 by Guest Contributor

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).