“Too many dolphins are getting caught in the tuna net!”

During the 2008 “great recession”, I was working at American Express in consumer new accounts risk management. For an ambitious and analytical 25 year old, this was an awesome job, being responsible for the underwriting criteria used to approve or decline new credit card applications during a rapidly-escalating financial crisis. I literally had the customer lifetime value model on my laptop with now-frequently updating versions of our internal risk prediction models, running scenario analysis, sometimes until 2am, to determine how to adjust and optimize our ‘cutoffs’ to achieve a desired outcome and control our risk. I was in the chief risk officer’s conference room at least once a week and also spent a lot of time with colleagues in marketing, product, finance, and operations walking through our proposals, quantifying the estimated impact, and working to implement them, without errors, far more rapidly than would normally happen at a massive financial institution.

One person I’ll never forget was named Bob, the executive in charge of operations and customer service for global new accounts. He was a key stakeholder of ours, and we were frequently presenting new risk policy changes to get his feedback, buy-in, and ultimately, the cooperation of the couple thousand people in his organization. His most frequent piece of feedback: “too many dolphins are getting caught in the tuna net!” This of course was an analogy to tuna-fishing vessels that accidentally ensnare dolphins in their catch. He constantly sent us examples of ‘dolphins’, good customers who had a credit line decreased, a transaction declined, or an account closed because of our (well-intentioned and overall statistically sound) policies. While this was annoying at the time, and we were confident in the overall impact of our policies on our customer base as a whole as well as the financial health of the company, we respected Bob’s role in serving as the voice of the customer. In the years since, I’ve come to appreciate that perspective even more.

Lending is fundamentally a business of asymmetric risk and decision making under uncertainty. By asymmetry, I mean that the profit one makes on a borrower who pays as agreed is significantly less than the loss incurred from a customer who utilizes his full limit and then charges off. By uncertainty, I mean that it is impossible to know 100% of relevant information at the time of underwriting. The implication of these facts is that even with the most state-of-the-art predictive modeling, a lender needs to decline many applicants who’d likely perform well in order to avoid approving the comparatively fewer who would not.

We can explore some very oversimplified numbers to make the example extra clear. Let’s say that a lending product has an interest rate of 12%, cost of capital of 5%, acquisition cost of 1%, and other operating expenses of 1% (all annualized % of initial principal for simplicity). Since 12-5-1-1=5, this means that a loss rate of above 5% would make a cohort of borrowers unprofitable. If someone applies for this product, and you predict a 6% risk of default, you would decline this borrower due to negative expected value. If 100 borrowers were to apply, each with a predicted risk of 6%, you’d decline all of them, even though you expect 94% to pay as agreed. As mentioned, this example is incredibly oversimplified and not really how you’d do the math in real life*, but the general point holds. There are lending products where the right cutoff is 40%, and there are others where the right cutoff is 3%, but there always is a cutoff, and lenders need to decline a lot of likely good borrowers to avoid the losses from the riskiest ones.

Most people outside of the world of credit (and especially those outside of statistics) likely don’t appreciate how many dolphins need to be caught for any profitable lending business to operate. Perhaps ironically, the ‘better’ credit products with lower interest rates actually need to catch proportionally more dolphins than the ‘worse’ ones with higher pricing!** In addition, the ‘net’ of risk criteria is not only cast at the point of initial underwriting but across the customer life cycle. Examples include pricing, line/loan sizing, authorizations, cross/up-sell, collections, and more.

So, is the sea of consumer financial services doomed to be eternally unsafe for dolphins, or is there some better way? Responsible expansion of the availability of credit is overall good for people and businesses, and lenders certainly have a clear profit incentive to approve as many applicants as possible. 

There are many techniques that lenders have used for some time and are consistently tweaking for better results. One example is “low and grow”, where lenders approve marginally risker applicants, but for fairly small amounts, growing exposure over time only for the accounts who demonstrate a track record of repayment. Other strategies are too numerous/complex to discuss here and are probably a subject for a future post.

Often overlooked, however, is the fact that customer experience can be one of a lender’s greatest risk management assets. Lenders who provide a unique and differentiated experience for their borrowers can make responsible payment the ‘default’ behavior. They can build favorable brand associations and engender the kind of loyalty that makes customers more likely to want to maintain a positive relationship. For example, product experiences can be structured to be aware of a borrower’s financial situation, potentially adjusting credit availability and payment terms dynamically. Customers in a situation of financial stress usually owe money to multiple creditors. Lenders who identify the issue early, engage with the customer proactively with respect, and work to craft a repayment plan that works for both parties will find themselves at the top of the payment hierarchy***. Furthermore, customer experience is the one truly unbounded competitive advantage in lending, something that can always get better and better with no limit (whereas e.g. your operation can get more efficient, but your opex will never be zero). 

I’ll always appreciate the lesson of the dolphin in the tuna net. Putting customer considerations at the forefront allows lenders to build a strong brand, expand access to credit, and earn not just the qualitative loyalty but also the repayment behavior of your customers. Through providing customers with the right product, at the right time, with the right terms, and giving them an experience that treats them with respect, gratitude, and transparency, the best lenders can rise above the fray. 

Footnotes:

*Real-life credit policy development is a complex and somewhat fascinating exercise in constrained multivariate optimization and applied systems theory.

**There are plenty of lending businesses with a 25% loss rate that are highly profitable due to their high pricing. 

***Payment hierarchy refers to the order in which customers pay their bills, assuming a limited budget.