Commercial Intelligence

During a panel at Fair Isaac’s Interact conference last week, a banker from Abbey National in the UK suggested that part of the credit crunch was due to the use of the FICO score.  Unlike other panelists, who were former Fair Isaac employees, this gentleman was formerly of Experian!  So there was perhaps some friendly rivalry, but his point was a good one.  He cited an earlier presentation by the founder of Strategic Analytics that touched on the divergence between FICO scores and the probability of default.  The panelist’s key point was that some part of the mortgage crisis could be blamed on credit scores, a point that was first raised in the media last fall.

The FICO score is not a probability. 

Fair Isaac people describe the FICO score as a ranking of creditworthiness.  And banks rely on the FICO score for pricing and qualification for mortgages.  The ratio of the loan to value is also critical, but for any two applicants seeking a loan with the same LTV, the one with the better FICO score is more likely to qualify and receive the better price.

Ideally, a bank’s pricing and qualification criteria would accurately reflect the likelihood of default.  The mortgage crisis demonstrates that their assessment, expressed with the FICO score, was wrong.  Their probabilities were off. (more…)

Ian Ayres, the author of Super Crunchers, gave a keynote at Fair Isaac’s Interact conference in San Francisco this morning.   He made a number of interesting points related to his thesis that intuitive decision making is doomed.   I found his points on random trials much more interesting, however.

In one of his examples on “The End of Intuition”, a computer program using six variables did a better job of predicting Supreme Court decisions than a team of experts.  He focused on the fact that the program “discovered” that one justice would most likely vote against an appeal if it was labeled a liberal decision.    By discovered we mean that a decision tree for this justice’s vote had a top level decision as to whether the decision was liberal, in which case the program had no further concern for any other information.  (more…)

In this article I hope you learn the future of predictive analytics in decision management and how tighter integration between rules and learning are being developed that will  adaptively improve diagnostic capabilities, especially in maximizing profitability and detecting adversarial conduct, such as fraud, money laundering and terrorism.

Business Intelligence

Visualizing business performance is obviously important, but improving business performance is even more important.  A good view of operations, such as this nice dashboard^[1], helps management see the forest (and, with good drill-down, some interesting trees). 

With good visualization, management can gain insights into how to improve business processes, but if the view does include a focus on outcomes, improvement in operational decision making will be relatively slow in coming.

Whether or not you use business intelligence software to produce your reports or present dashboards, however, you can improve your operational decision management by applying statistics and other predictive analytic techniques to discover hidden correlations between what you know before a decision and what you learn afterwards to improve your decision making over time.  (more…)