It’s Not What You Know. It is What You Don’t Know!
A major chunk of my 40 years of experience, in companies large and small, has been in financial services risk management – on and off, strange as it may seem, with stints in marketing, finance, operations and executive (p & l) management. This gave me the opportunity to see risk management from many different perspectives: “holding me back”, when I was in marketing, a “like-minded but narrowly focused partner”, when I was in finance and operations, and as “a necessary evil”, when I was in executive management. From the inside, the perspective was like being the “high priest in a world of weak-minded parishioners, inclined to stray and commit sins”.
Along the way, I served on the advisory boards or organizations like Fair Isaac & Company, and Fannie Mae, helped create peer forums with fellow chief risk officers from other institutions, dealt with the challenge of asking line managers tasked with growth to pull back in advance of seeing the problem, and finally as the executive responsible for the bottom line, tried to balance risks that could hurt me in the long-run with revenue that could make me succeed in the short-run. My biggest reward was to see individuals on my team achieve success by ending up in senior risk management roles at some of the leading financial institutions in the country.
"We always drive the bus with one foot on the gas pedal and one foot on the brakes.” (S.A. Ibrahim as CEO, on an investor call)
A Common Misconception
Let me start with a question I often ask when trying to explain risk. Imagine two different programs, each involving lending a $1000 each to 1000 borrowers. Program A has expected losses of 4% over 5 years but the loss rate can vary from 1% to 7%. Program B has expected losses of 5% over 5 years but the loss rate can vary from 4% to 6%. Which program is riskier?
Most frequently my audience picks Program B as being riskier and the reason was that it had a higher projected loss rate. The correct answer, however, is Program A because the actual result can vary over a wider range. In designing a business strategy, I can more easily design or deal with the economics and p&l impact from a known but higher (as long as I can charge for it) loss. In the case of Program B, I need to be compensated for the likelihood of the higher-end losses. Of course, I grossly simplified the question and answer, because other factors such as the shape of the curve, the external environment, ancillary considerations, etc. may change the picture however at the expense of increasing the complexity of and the uncertainty associated with the decision because each of these factors by itself has a possible range of outcomes.
Transaction Risk & Portfolio Risk
Transaction risk is the risk associated with an individual transaction, for example, a loan. The lender evaluates the likelihood of the borrower making loan payments as agreed in order to achieve the target level of profitability. Today, the most common tool used to assess this likelihood is the borrower’s FICO score, originally developed in the 90s by Fair Isaac & Company. At that time, I was on their Advisory Board and recall that the FICO score was viewed more as a portfolio monitoring tool than an initial credit extension tool. Fair Isaac built custom scorecards, purpose built using the lender’s own experience to make more robust credit decisions. However, FICO scores took off because of their ease and simplicity and because reducing every transaction (and every borrower) to a single number is the easiest - even if not necessarily the most accurate - standardized measure of credit risk across the industry.
Essentially, a FICO score rank orders borrowers on a range from a high in the 800s to the 300s, with typically scores in the 700s and higher considered “good” and in the 500s or lower considered “bad”, keeping in mind that acceptable scores vary to some extent, based on each lender’s strategy. Ultimately, lenders are trying to achieve a target level of profitability that is only possible with a certain range of credit loss.
FICO scores measure the “borrower” risk associated with the transaction. Another factor used to assess the borrower risk is the capacity of the borrower to make the loan payments. Typically, lenders are concerned about the borrower’s income in relation to the borrower’s total debt or debt obligations. Lenders are also concerned with the borrower’s financial assets (savings and investments). Typically, the larger a loan, the more important the financial capacity assessment.
In the case of secured loans like automobile or home loans, the value of the collateral being used to secure the loan becomes an important consideration in assessing the transaction risk. Ultimately, the rigor in dealing with transaction risk is a function of the size of the transaction. Since collateral is a secondary source of repayment, collateral assessment evaluates the liquidation value of the collateral in the event of a loan default.
The larger the transaction, the more rigorous the evaluation and the more comprehensive and complex the loan agreement. For small consumer loans, the transaction risk remains important but it becomes impractical, both from a cost/time as well as from a competitive perspective to go beyond a certain point and the focus is more on managing rather than avoiding losses and relying on portfolio dynamics to achieve a loss level that optimizes profitability.
Portfolio risk is the risk associated with a large portfolio of many transactions. The statistical beauty of a portfolio is the ability to manage the risk based on offsetting or non-correlated risks. Firstly, the sheer number of different transactions means that unless there is a major external event, like a severe economic downturn, the loss incurred by some loans is, by design, offset by the profitability of the rest of the loans. Additionally, the goal is to diversify the portfolio as much as possible by geography, borrower demographics, and other factors. It is important to ensure that the concentration risk, associated with too many transactions having the same characteristics is managed carefully at the portfolio level.
“The objective of making loans is not to totally avoid losses but to manage losses at a level that maximizes profits.”
As a credit risk manager, I made it my business to help the business make as many good loans as possible, because the profitability of the business is driven by the ratio of the amount of unintentional bad loans (“numerator”) divided by the total amount of all loans, including the good loans that pay without any problems (“denominator”).
“Managing credit risk is about managing both the numerator and the denominator.”
Key Lessons Learnt
- Don’t just rely on statistical models, always worry about what could go wrong; it is too easy to believe that credit decisions are being made using FICO scores or other statistical tools. The more you know about these tools the more you know that they are far from perfect. Among other factors, the models are typically based on recent performance data which is, in turn, influenced heavily by external economic and other factors. Past behavior is not always an indicator of future performance.
- Shortly after the onset of the last economic downturn in 2008, I was initially surprised to see that certain home mortgages with high FICO scores in my portfolio seemed to default at disproportionately high rates. It turned out that these borrowers later labeled “strategic defaulters”, had taken advantage of their good scores and the availability of easy credit, to speculate on real estate. They walked away from their real estate and their loans when the value of the real estate declined and the loan balance exceeded the market value of the home.
- Conventional wisdom, until the last downturn, held that a borrower would default on other loans (automobile, credit card, etc.) before defaulting on their home mortgage. During the last downturn, some borrowers realized that the system had been so overwhelmed with the sheer number of defaulting mortgages that they could stay in their home for months before being evicted. However, they needed a credit card or two and needed their car, so they defaulted on their home loan and not on the other loans. Some borrowers maintained their excellent credit and took out another mortgage, to purchase a home similar to theirs at the much lower post downturn home price and then walked away from the home they had bought at the higher price before the downturn.
- Keep in mind, the majority of borrowers kept paying through the downturn and sound credit underwriting, including FICO scores, with exceptions like those above, proved to be valuable in ranking credit performance even if the overall profitability of the portfolio performed much worse than projected.
“It takes only a few more bad loans than expected to destroy profitability.”
- Use the best tools, including FICO scores, debt capacity, collateral evaluation as appropriate to make credit decisions but NEVER ever believe that your job is over. It is just beginning because it is not over until you get paid back.
- Use scenarios that conceptually or analytically model what could happen under different conditions. Knowing the top three to five things that could adversely impact your loan portfolio is critical to staying on top.
Disclosure: I/we have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours.
I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.