In my 20 or so years in banking, I have seen consumers impacted by horrible, unfair, life-altering events, such as job or home loss or the inability to get health insurance coverage because (wait for it) a consumer could get really sick. Other examples include vicious credit collectors/agencies/law firms, mortgage and HELOC fraud, predatory teaser and adjustable interest rates, automobile title lenders and payday lenders from whom consumers cannot escape, roofing and aluminum siding salesmen pushing loans on the elderly, and on and on.
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Since July 13, when announcements of the proposed Visa and MasterCard US$7.25 billion lawsuit settlement first started to appear over news wires, there has been significant market and press discussion about the implications of such a settlement. Numerous articles have been written on how the settlement may affect businesses and consumers making purchases at the point of sale. Analysts, including myself, have been quoted in articles about the likelihood of merchants to surcharge (or not) on transactions paid for with a credit card.
The long-fought battle over credit card swipe-fee price fixing may be coming to an end as a settlement was proposed in federal court on Friday, July 13, 2012. Visa and MasterCard have agreed to a US$7.25 billion settlement (the largest anti-trust settlement in U.S. history), which comes, according to Visa’s chairman, Joe Saunders, as a result of “being in the best interest for all parties.”
On Tuesday, July 10, The Federal Financial Institutions Examination Council released a four-page statement that highlights key elements financial institutions need to address when deciding whether to outsource cloud computing services. In this document, the FFIEC continues to follow the same guidelines outlined in its FFIEC Information Technology Examination Handbook (specifically the Outsourcing Technology Services Booklet) and recommends that financial institutions perform thorough due diligence of cloud services providers and a detailed risk assessment of the key elements specific to the services they seek.
Predictive analytics is a fairly mature technology, and the use cases for this technology abound. Insurance companies are examining their claims databases to detect whether an inbound claim to a call center is likely to result in fraud, and bankers use the technology to both build marketing programs and predict which product to cross-sell to a given customer. Unfortunately, the commercial loan portfolio manager appears to be absent from the growing crowd of predictive analytics users.