Franchise Update Magazine Issue II, 2016 | Page 63

GROWING YOUR SYSTEM

Market
trends
The New Underwriting
As banks evolve, so must borrowers
BY DARRELL JOHNSON

B

ank lending cycles last about 7 to
10 years, and in every cycle bankers find some “out with the old,
in with the new” approaches to lending.
Sometimes that leads to a pivot in industry focus, such as a move in retail banking
away from housing toward autos, and in
commercial lending from commodities
toward healthcare.
Sometimes this leads to differences in
how underwriting is done, which is applied across industries. During the last
economic rodeo that ended in 2008, both
retail and commercial lenders became enamored with “low documentation” loans.
Essentially, they were betting that higher
loan volumes at lower underwriting costs
would balance an expected rise in underperforming loans. That didn’t end well.
After the predictable decline and then
slow rise in lending after 2009, lenders
searched for the next “new” approach to
loan underwriting.
As the economic recovery progressed,
banks came under greater pressure to
grow earnings, which meant closing more
loans. As one would expect, in the first
few years of economic recovery banks
began dipping their credit risk toe back
into business lending at the low end of
the risk spectrum. In franchising, that
meant multi-unit operators, and banks
were stumbling over one another to offer
them better terms. However, there wasn’t
enough loan volume of this type to go
around, so some banks started moving
up the loan risk curve. SBA lending, because of its guarantee structure, became
a darling of banks and volumes spiked.
Now we are seeing the “new normal”
phase of commercial lending, with loan
structuring and pricing becoming key
differentiators as banks move further out
on the risk curve.
All these trends are predictable behaviors during an economic recovery.
Lenders learn from what didn’t work

well during the last downturn and make
changes to how they underwrite. Before
I explain what bankers learned from the
last cycle that is changing franchise lending, I should mention two other trends
that are affecting where we are today.
The first is regulation. When an eco-

Loan underwriting
essentially is an
activity that tries to
understand the past
to predict the future.
nomic downturn is caused by a financial
crisis, as the 2008 recession was, you can
count on regulators to react strongly.
And, right on cue, we saw a litany of
new banking regulations. Two key results were much greater documentation
requirements for commercial loans and
greater bank portfolio stress testing requirements to determine capital reserve
adequacy. Both of these had implications
for franchise lending.
The second trend is technology. With
the onset of “big data” risk analysis and
easier access to more sources of information about an industry, a brand, and a
borrower, lenders began experimenting
with new ways to approach commercial
loan underwriting.
What does all this mean for franchising? The answer is a lot—with more
coming. To grow, franchising must have
continuing downstream access to capital.
It’s a basic tenet of the business model.
Adapting to the changes that banks are
starting to introduce is necessary to see
a continued flow of capital.
How underwriting is changing
Loan underwriting essentially is an activity that tries to understand the past
to predict the future. This means look-

ing at a borrower’s historical business
and personal results, including financial
statements, tax returns, and business and
personal behavior, often in the form of
FICO scores and personal interviews.
What lenders learned from the last lending cycle is that franchise lending has two
attributes that help banks improve loan
predictability: uniformity and conformity.
If the same potential borrower is considering two franchise brands, the underwriter should be able to predict which
brand has a higher likelihood of a successful franchisee and therefore a performing loan. Doing so requires better brand
underwriting due diligence. Technology,
especially in this era of “big data,” gives
underwriters more access to information.
The challenge they have is putting that
information into an underwriting model
that predicts loan outcomes. This need
is being accentuated as regulators put
more pressure on them to defend their
underwriting due diligence and stress test
their loan