Important Metrics Needed When Analyzing Credit Union Loans
November 2017

Relatively speaking, intensive data analysis by financial institutions to determine loan portfolio health is a new phenomenon.

But a volatile decade marked by a massive real estate bubble, the worst economic crisis in 80 years, and a snowballing recovery has provided an ideal trial environment that crystallized the value and accuracy of certain factors as they relate to loan yields.

Most often, these calculations are performed at the portfolio level or significant chunks thereof, such as segments, pools, or other aggregations. That approach is invaluable, providing the best assessment of the overall health of a financial institution’s lending operation and its impact on the bottom line.

However, loan-level analysis also should play a key role in your evaluations. Think of it as providing an extra dimension to your understanding of the portfolio — depth, to complement the length and width discerned through broader strokes.

Consider that the average or median calculation in a given category can disguise the spread across a spectrum. Is your loan portfolio truly diversified, with loans representing a wide array of risk? Or might you actually have an unstable “barbell” arrangement of very low-risk loans and very high-risk loans, with few falling into the middle ground?

According to “The valuation applications of loan-level data,” a 2010 study of United Kingdom loan portfolio analysis, “Loan-level data allows us to view the effects of risk-layering, or the non-linear increase in risk when a loan contains a combination of risk factors, on the probability of default.”

The majority of the most impactful metrics are old standbys, like the five Cs of credit — character, capacity, capital, collateral, and conditions — but simply probe more deeply and continuously.

These include:

Credit score migration. No longer does the use of credit scores end at the loan decisioning and pricing stage. This time-honored snapshot of probability of default over a 24-month period now is viewed as a rolling variable, and downward movement in credit grade has become the most prominent and trusted indicator of loan instability.

Loan to income (LTI). Another stalwart for obvious reasons: If you’re making a substantial amount of money in relation to your debts, you’re likely to stay current on your obligations. But this factor has been influenced by societal changes. As the workforce has become more transient — does anyone still get a gold watch for decades of service? — and more entrepreneurial in nature, especially among young adults, income fluctuates and merits closer ongoing attention. That also doesn’t take into account the skyrocketing medical costs that sabotage many households in the event of a catastrophic incident or illness. Also, take into account the raw dollar amount of the loan in combination with LTI. As the aforementioned study notes, although default risk for high- and low-risk loans can be similar, borrowers with larger loan balances have much less flexibility in the event of a disruption to their income.

Loan to value (LTV). Long a key risk factor, LTV also has become a factor in flux due to the housing bubble crash and subsequent uneven rebound.

Interest-rate risk. Sooner or later, the Federal Reserve will decide to raise interest rates. That’s likely to occur gradually, for fear of disrupting the steady but fragile economic rally. But it will happen. Holding long-term, fixed-rate mortgages harbors loss potential for financial institutions. Assess whether you can take measures to better insulate against that risk.

Variations such as prepayments or partial payments, which affect loan yield. If a financial institution doesn’t have a large enough pool of data to determine the parameters for risk on an aggregate level, you can estimate the impact of prepayment speeds with calculative models maintained by the national deposit insurance entities.

Loan origination date. Be aware of variations in pricing or asset valuation linked to underwriting changes or flaws, and the impact of extreme market conditions.

Delinquency. Clearly, the most telling factor of loan distress. Fortunately, in the wake of the financial crisis, most banks and credit unions strengthened their safety nets and oriented their lending and collections departments toward proactive policies and measures that better salvage troubled loans.

Related Blog Posts
Further Your Education