Independent Banker - July 2018 - 27

Next: How reg relief became a reality
nity banks, according to a release last year from
the Office of the Comptroller of the Currency.
With the market trending in recent years
toward looser underwriting standards, many
lenders are pushing the credit risk boundaries
more than they have in a dozen years to win
business in high-growth loan products, remain
competitive with rival lenders and attract more
highly educated borrowers. The result: Community
banks that want to push forward need more
than just a credit score and a gut check to best
calculate how risky each loan may be.
lytics, has seen more community banks collecting
a broader array of borrower data and analyzing it
by group as well as by individual. In this way, they
can more easily see how certain financial signs
can link to specific credit events and better predict
which borrowers are likely to pay back their loans.
" Are there certain financial ratios that are linked
with past-dues or charge-offs? Of course there
are, " Henkel says.
While community banks do not always have
the resources to employ a full-time data scientist
Sources of data
Traditionally, community banks have used two
main information sources to evaluate credit risk,
according to Priyanka Prakash, a writer and
lending expert for Fundera. First, she says, they
have relied on traditional credit data, " similar
to what large national banks use in their underwriting
processes. It's almost impossible to find
a community bank that won't pull a prospective
borrower's credit report and check their credit
score, credit utilization and payment history. "
Secondly, they use their personal knowledge of
the borrower and the community.
" It's here that community banks really have a leg
up over the national bank chains, " says Prakash.
" Community banks have often been in the same
location for dozens of years and have a repository
of valuable knowledge about the neighborhood,
primary employers and businesses in the area,
the location of the most desirable schools and
residential areas. All of this can help a community
bank evaluate risk. "
However, the traditional community bank
approach, while effective in many ways, tends to
be broader and less analytical, and it can produce
uneven results, according to Jeff Hall, senior vice
president of quantitative products for CRMa.
" The biggest issue we see is an untapped potential
here to use risk grades, " Hall says, adding
that such grades, based on more holistic data
analysis, would allow community banks to more
accurately assess risk and price loan products
better. " In many cases, the pricing has been more
or less based on intuition, " he adds. " If you don't
differentiate clearly, you end up self-selecting the
lower-tier clients and drifting into riskier loans. "
Chris Henkel, senior director at Moody's Ana " In
many cases, the
pricing has been more or
less based on intuition.
If you don't differentiate
clearly, you end up selfselecting
the lower-tier
clients and drifting into
riskier loans. "
-Jeff Hall, CRMa
or analyst, bank service providers are stepping
up. Experian, for example, recently launched a
" tri-bureau leveled trended attributes " product
that blends data from all three credit bureaus to
help lenders create a picture of consumer risk
over time, rather than at a single moment.
In the past five or six years, Henkel adds that
banks have begun embracing a more analytical
and granular approach to credit risk in order to
comply with the Current Expected Credit Loss
(CECL) standard. In the wake of the financial
crisis and the flood of new (often risk-focused)
regulation to which they must now adhere,
many banks quickly realized that " if they had
to collect more data anyway, they could also
do more with it, " he says. " They wanted to do
things differently. "
Karen Epper Hoffman is a writer in Washington state.
independentbanker.org Q 27
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Independent Banker - July 2018

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