Assessing Risk Beyond the 5 C’s of Credit
When assessing the potential risks a borrower presents a bank’s portfolio, the typical starting point for most lenders is the “Five Cs of Credit” – capacity, character, capital, collateral and conditions. But as a younger generation, burdened with excess debt, becomes the prime demographic for commercial and consumer loans, community banks and credit unions may want to reconsider that approach if they want to capture this increasingly important segment.
Judging by the numbers, the American economy is on an uptick. The national unemployment rate sits at 3.9 percent, the lowest rate since 2000, the average FICO credit score is at its highest point ever – 704 – and the median household income is at $61,372, its highest mark in over 30 years. In addition, young borrowers’ share of the lending market is growing.
Despite the positive figures, young borrowers’, dominated by millennials, financial outlook are not on par with the national averages. The average FICO credit score for young borrowers (aged 21-34 years old) is 638, while the average income for millennials is $35,592.
It could be difficult for community institutions to grow revenue if metrics other than the five Cs of credit are not factored in when analyzing young borrowers. Let’s take a look at the five Cs of credit in consideration with the young borrower market.
Capacity – Young borrowers earn an average salary of $35,592 and owe an average of $25,000 in student loan debt alone, making for a poor debt-to-income (DTI) ratio.
Character – Young borrowers’ average credit score of 638 is considered fair or poor for most financial institutions that rely on credit scores as the only gauge of character.
Capital – Young borrowers are spending more on bills than previous generations, leaving less funds to put toward payments.
Conditions – Young borrowers are starting new businesses, which, due to their limited credit history and high debt burden, can be too risky of a loan for community banks and credit unions to offer.
Financial institutions hoping to gain substantial market share of the up-and-coming young borrower market could consider including supplemental factors, such as global cash flow, within their credit analysis and implementing technology to better evaluate credit risk.
Analyze young borrower’s entire relationship through global cash flow
Global cash flow refers to a lender or credit analyst’s ability to review a borrower’s financial relationships with his or her peers in the community and, more importantly, the financial institution. Rather than solely focusing on the borrower’s financial history as a key determinant of creditworthiness, financial institutions can determine how businesses, properties and family members connected to the young borrower will affect credit risk for the institution. For example, perhaps a loan application from young borrower Jack comes across your desk for a $5,000 commercial loan to pay equipment costs for a moving business. When analyzing his financial statements, you see that not only does Jack make a lower-than-average income of $29,000 per year, but he also owes a total of $25,000 in student loans. Your initial reaction is to deny the line of credit. However, upon reviewing the global cash flow analysis, you realize that his student loans have a guarantor on the account – Linda – his mother. Linda earns an income of $110,000 annually and has a credit score higher than 750. She co-owns two businesses with other prominent community members and has banked with your institution for 20 years. By considering relationships through global cash flow, you have more evidence to potentially justify the line of credit and offer the loan to Jack based on conditions that mitigate credit risk. By using global cash flow analysis, lenders can identify opportunities, increase defensibility of loan decisioning and take informed, calculated risks.
Use technology to determine credit worthiness
In an article published by the Wharton School of the University of Pennsylvania, Benjamin Keys, Wharton professor of real estate, and Richard K. Green, director of the University of Southern California’s Luck Center for Real Estate, both pointed to technology as a way for banks and credit unions to pull in other factors during credit analysis to provide supplemental evidence that borrowers can repay loans.
Implementing credit analysis technology allows lenders to identify portfolio risks based on internal factors, such as probability of default, and external factors, such as data from other financial institutions, through automated credit risk models and APIs.
An automated commercial credit risk model can determine credit worthiness using predictive financial factors and limited data entry from lenders or credit analysts. Furthermore, automated credit risk models can quickly compare probability of default with broader industry trends and examine the industry’s risk to the institution. For young adults with limited access to capital, better understanding industry trends can provide another factor to be taken into account when examining credit.
APIs layer on another source of bank data for lenders to include within credit analysis as well – third- party data. For example, Plaid, an API used in Abrigo’s Loan Application and Client Portal, collects real-time asset account data from over 9,000 financial institutions that can then be used as support during credit analysis. Rather than just focusing on the young borrower’s limited relationship with your bank, Plaid gives financial institutions another factor to incorporate in loan decisioning and increases defensibility for auditors and regulators.
As the demographics of financial institutions’ customers shifts to younger borrowers with less credit history and higher DTI than previous generations, it’s important for banks and credit unions to focus on more ways to help them find good risks that represent profitable growth from a core of young borrowers.