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Alan, it would be great to hear your perspective on credit economics: small business loans, lines of credit, credit cards and leases all are showing lowest delinquency levels in years. What does this mean for predictive analytics and, ultimately, bank profitability?

With delinquency rates this low, there’s a tendency to take the eye off risk in favor of pure customer acquisition; the key is to remain centered, balanced, maximizing approval rates while remembering that times will not always be this good. Decisions made today will impact a long tail of future earnings, particularly for open-ended products. This requires using not only most current data, but also new data – innovative attributes that in some cases just recently came on stream - in predictive analytics. Speed and quick decisioning in using new and current data is more essential than ever before. Solely using data elements that existed 10 years ago or pre-recession is not going to work anymore. New attributes are the key to prudently and transparently maximizing those approval rates and growing profitably.

Thanks for offering your perspective on credit economics. On a related note, Dun & Bradstreet’s economists have said for more than a year that the “credit card boomlet” is coming, and they expect the US credit card industry to see increased business activity through 2018. How is this projection playing out?

Just as projected, we are absolutely seeing growth in credit cards, in terms of line size and utilization as well as in new accounts. The lending industry has turned up its marketing and personalized targeting from a card perspective, both in print and digitally, the latter of which has yielded a surge in demand for digital marketing and optimization solutions across a range of industries, particularly from financial institutions. There is an increasing sophistication in this digital revolution, and it is a dramatic and recent change: for a while post-recession, many were tentative to put their toes back in the water.