Banking's Not Getting "Uberized" But Analytics Do Matter

Credit unions should get together to tackle data, overcome challenges, and compete.

 
 

In a November Snarketing post, author Ron Shevlin took the “Uberization of Banking” threat head-on and knocked it down.

Good work.

In doing so, the Cornerstone Advisors research director raised some interesting questions and framed significant challenges that credit unions — individually and almost certainly as a system — need to figure out fast.

If you consider the notion of a “rebundled bank,” and its impact on the average consumer, you run into two serious problems:  trust and risk management.

1. You have to overcome the entirely rational fear on the part of consumers that a financial institution will effectively “punish” them for having given the institution so much information about their financial lives that the institution is both empowered and incentivized to

a) Compromise their interests by restricting service and/or credit, and
b) Leverage the stickiness of a bundled relationship to suck them dry for profit.

In theory, credit unions should be well-positioned to overcome (b), at least, but (a) brings us to this challenge:

2. You have to overcome the fear of risk that limits lending and drives consumers to do business with multiple credit providers even when doing so can be riskier and more expensive than it would be by staying with one true financial partner.

One might argue that credit unions should be well positioned to overcome this, too, but in the current regulatory and management environment, credit unions are seen to be — and not inaccurately so — more risk averse and more conservative as lenders than for-profit institutions. 

In other words, not a good choice as a bundled financial services provider for a credit-hungry young person or young family just starting out.

One approach to manage both these challenges is the use of modern data analytics. Correlative analysis can be a powerful risk management tool, both improving underwriting accuracy and — perhaps more important — empowering lenders to better manage risk in their portfolio and therefore take on more of it. 

Better use of data analytics can also drive an ability to anticipate and prepare to meet the needs and expectations of each individual consumer in ways never before imaginable. Both applications — active risk management and what I’d call Member Intimacy — are areas where credit unions should — and I’d like to think will — excel.  But the time to start acting is now.

Major banks are already investing hundreds of millions of dollars each, annually, in pursuing the Holy Grail of Big Data to do this more efficiently and universally, more profitably, and on a larger scale than any but a handful of credit unions could even imagine.

Of course, once again, one would think that credit unions — cooperatives — are institutionally and attitudinally well-positioned to answer this challenge. Unfortunately, the current environment of CUSOs running competing, closed-system solutions targeting narrow verticals militates against success at large-scale collaboration.

As institutions that view their owner-members as people and not just numbers, credit unions have a natural advantage over mega-banks.  Successfully exploiting that advantage in the years to come will increasingly depend on powerful data analytics.  That requires a scale that can only be achieved if credit unions find ways to cooperate more broadly than they do today.

 
 

Nov. 30, 2015


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