Risk-Based Pricing: Why Lenders Do It and How the Rate Is Built
You price a personal loan at one rate. A competitor offers your strongest applicants less, and they take it. The applications you still win come from people that competitor priced higher or turned down. Price is how you choose which customers you win. The rate each one needs comes from the costs that customer brings to your book.
Why price by risk
When every applicant gets the same price, stronger applicants can find better terms elsewhere. That can leave a larger share of higher-risk applicants in the pool, and raising the single rate may make the selection problem worse.
Risk-based pricing gives you a way to offer a better price to applicants you want to attract, instead of charging the same rate across differing credit risks. A study of a subprime auto lender that moved away from uniform pricing found that credit scoring appeared to increase profits by roughly a thousand dollars per loan. In that case, scoring affected minimum down payments and which cars could be financed, not the interest rate.
The opportunity is especially clear when you choose whom to approach. You may already have customers in your portfolio, such as loan customers you could offer a credit card. Reaching those customers costs less than acquiring a new customer, so the offer can support a different price.
What each customer costs you
Your pricing equation is profit = (interest income + fee income) - (interest expense + risk costs + acquisition costs + admin costs). Admin costs and fee income are the same across customers in this example, and fee income lowers the rate a loan needs point for point. An insurance premium is built from its costs the same way.
Risk
Expected loss is PD × LGD × EAD: probability of default multiplied by loss given default and exposure at default. The Basel Committee describes expected losses as a cost of doing business that lenders manage in part through credit pricing. The score behind PD comes from your scorecard, which groups applicant characteristics into a score used in the lending decision.
Funding
Funding cost can differ by segment. Loans to good customers may be securitised and fund at a lower cost of money. Credit enhancement protects senior notes against losses, and rating releases for a prime auto pool and a subprime auto pool show different protection levels: the prime pool’s Class A notes required 7.45%, compared with 59.85% for the subprime pool’s Class A notes.
Acquisition
A customer already in your portfolio costs less to reach than a new customer. If you offer that customer another product, such as a card, the lower acquisition cost reduces the rate needed to meet your target margin.
If capital, rather than margin, is the hurdle, the rate is the one that makes the return on the capital allocated to the loan meet your hurdle rate. That is the RAROC approach, or risk-adjusted return on capital.
From cost to rate: four bands
At one flat rate, bands A and B pay for C and D, but a competitor can price A and B lower and still make its margin.
Solving the profit equation for the rate in each band gives this grid.
| Band | PD | Funding | Risk cost | Rate | Own customer |
|---|---|---|---|---|---|
| A | 1% | 3.5 | 0.6 | 8.6% | 7.6% |
| B | 3% | 3.5 | 1.8 | 9.8% | 8.8% |
| C | 6% | 5.0 | 3.6 | 13.1% | 12.1% |
| D | 12% | 5.0 | 7.2 | 16.7% | 15.7% |
Funding accounts for 1.5 points of the difference between A and D in this demo case, and a customer from your own portfolio needs a rate one point lower than a new customer in the same band.
What the law does to your grid
A rate cap sets a ceiling for your top band. If a band’s costs call for a rate above that ceiling, you cannot price it at the rate the costs require. Examples include the UK high-cost short-term credit cap, which sets an initial cost cap of 0.8% per day, caps default fees at £15 and limits total cost to the amount borrowed, and the US Military Lending Act’s 36% MAPR limit for covered consumer credit.
In the US, a risk-based pricing notice can be required when the terms you offer are materially less favorable than the most favorable terms available to a substantial proportion of your customers, and the price is based at least partly on a consumer report. That test changes what your process must provide for an applicant whose offer meets it. Regulation V also lists exceptions.
A prescreened offer to selected customers is a firm offer of credit if you will honor it for anyone who meets the specific criteria used to select them, based on information in a consumer report.
Putting the grid live and testing a change
Your pricing team can represent score bands and rates in a decision table, editing rows directly or pasting a block of cells from a spreadsheet. A function can calculate the rate, with a floor or cap expressed through min or max. The lender’s team defines the grid and formula. The pricing decision sits alongside your underwriting policy, which decides whether an application is approved.
To test a changed grid against past decisions, run two revisions over the same historical rows and compare the decisions that differ. You can join outcomes to those rows to see the realized bad rate for each group.
For a live comparison, a branch in the decision flow can route applications using a split value your own system sends. If a decision archive is connected, each decision is written to your database with that value, so you can compare the two groups against your own outcomes.
A release starts deciding once you deploy it to an endpoint. An endpoint can carry a sign-off sequence, and each response carries the release name, so the version used for a decision can be identified.
Frequently asked questions
What rate does an applicant with no score get?
In a decision table, a missing numeric input is treated as zero unless a row catches the missing value. A missing score can therefore fall into a band that starts at zero. Fannie Mae’s published loan-level price adjustment matrix charges a loan delivered with no credit score under its lowest score range.
How do I test a new grid before it reaches the book?
Run the revised grid and the current grid on the same past decisions, then join outcomes to compare the groups. For a live test, route applications using a split value from your own system and compare the results against your own outcomes.
