Risk Adjusted Loan Pricing – The Major Parts

by Guest Contributor 4 min read January 7, 2009

By: Tom Hannagan

I have referred to risk-adjusted commercial loan pricing (or the lack of it) in previous posts. At times, I’ve commented on aspects of risk-based pricing and risk-based bank performance measurement, but I haven’t discussed what risk-based pricing is — in a comprehensive manner. Perhaps I can begin to do that now and in my next posts.

Risk-based pricing analysis is a product-level microcosm of risk-based bank performance. It begins by looking at the financial implications of a product sale from a cost accounting perspective. This means calculating the revenues associated with a loan, including the interest income and any fee-based income.  These revenues need to be spread over the life of the loan, while taking into account the amortization characteristics of the balance (or average usage for a line of credit). To save effort (and to provide good client relationship management), we often download the balance and rate information for existing loans from a bank’s loan accounting system.

To “risk-adjust” the interest income, you need to apply a cost of funds that has the same implied market risk characteristics as the loan balance. This is not like the bank’s actual cost of funds for several reasons. Most importantly, there is usually no automatic risk-based matching between the manner in which the bank makes loans and the term characteristics of its deposits and/or borrowing. Once we establish a cost of funds approach that removes interest rate risk from the loan, we subtract the risk-adjusted interest expense from the revenues to arrive at risk-adjusted net interest income, or our risk-adjusted gross margin.

We then subtract two types of costs. One cost includes the administrative or overhead expenses associated with the product. Our best practice is to derive an approach to operating expense breakdowns that takes into account all of the bank’s non-interest expenses. This is a “full absorption” method of cost accounting. We want to know the marginal cost of doing business, but if we just apply the marginal cost to all loans, a large portion of real-life expenses won’t be covered by resulting pricing. As a result, the bank’s profits may suffer.

We fully understand the argument for marginal cost coverage, but have seen the unfortunate end. Using this lower cost factor can hurt a bank’s bottom line. Administrative cost does not normally require additional risk adjustment, as any risk-based operational expenses and costs of mitigating operation risk are already included in the bank’s general ledger for non-interest expenses.

The second expense subtracted from net interest income is credit risk cost. This is not the same as the bank’s provision expense, and is certainly not the same as the loss provision in any one accounting period.  The credit risk cost for pricing purposes should be risk adjusted based on both product type (usually loan collateral category) and the bank’s risk rating for the loan in question. This metric will calculate the relative probability of default for the borrower combined with the loss given default for the loan type in question.

We usually annualize the expected loss numbers by taking into account a multi-year history and a one- or two-year projection of net loan losses. These losses are broken down by loan type and risk rating based on the bank’s actual distribution of loan balances.

The risk costs by risk rating are then created using an up-sloping curve that is similar in shape to an industry default experience curve. This assures a realistic differentiation of losses by risk rating. Many banks have loss curves that are too flat in nature, resulting in little or no price differentiation based on credit quality. This leads to poor risk-based performance metrics and, ultimately, to poor overall financial performance. The loss expense curves are fine-tuned so that over a period of years the total credit risk costs, when applied to the entire portfolio, should cover the average annual expected loss experience of the bank.

By subtracting the operating expenses and credit risk loss from risk-adjusted net interest income, we arrive at risk-adjusted pre-tax income. In my next post I’ll expand this discussion further to risk-adjusted net income, capital allocation for unexpected loss and profit ratio considerations.

Related Posts

Rethinking Charged-Off Portfolio Prioritization

Experian’s new Recovery Scores model turns portfolio intelligence into more focused recovery strategies, helping organizations improve returns, direct effort and accelerate speed to cash. The challenge isn’t simply working more accounts. Whether a debt buyer is evaluating an acquisition, an agency is deciding where to assign collector time or a lender is managing its own post-charge-off accounts, the question is similar: How can limited capacity be directed toward accounts with the greatest potential for recovery? Prioritizing accounts mainly by age, balance or when they were last worked may not show which ones are most likely to generate a recovery. With the new Recovery Scores model, organizations can rank charged-off accounts by expected collectability, providing a consistent signal to inform placement strategy and treatment decisions across the recovery lifecycle. Make collector capacity a strategic resource Working every account with the same level of attention isn’t always practical. The more useful question is: Where should teams focus first to protect speed to cash? Our model performance analysis found: 80% of recovered dollars come from the top 40% of accounts worked. The value isn’t simply a better ranking. It’s how organizations can use it for collections optimization. Score bands can inform different strategies for placement, outsourcing, auction and legal channel treatment rather than applying the same approach across an entire portfolio. For debt buyers: The scores can inform acquisition pricing and how a newly purchased portfolio is divided across internal collections, legal channels and resale. Expected collectability can shape debt portfolio analysis, including how a portfolio is valued and segmented before collection work begins. For agencies: Score bands can help teams focus collector resources on accounts with stronger recovery potential. For first-party lenders: Managing recovery internally, the scores provide another signal to help structure decisions about which accounts to work and in what order. Look beyond collectability alone Prioritization rarely comes down to a single variable. Consider two accounts that both rank highly for expected collectability, but one has a substantially larger balance. Their recovery likelihood may be similar, but the potential dollars recovered are not. The Recovery Scores model uses debt collections analytics by combining Experian’s bureau-based score with current balance information. This helps organizations consider both the likelihood of recovery and the potential dollars at stake, while sensitive balance information remains within the organization’s working environment. Monitor accounts as they change The first decision about an account is rarely the last. Teams continually make choices about treatment, placement and resource allocation as accounts move through the recovery process. Recovery Scores is also available as a trigger. When underlying information changes, teams can receive an update and reconsider an account’s placement without waiting for the next portfolio-wide re-score. An account that shows lower recovery potential today may have a different recovery outlook later. Turn recovery potential into a portfolio strategy When portfolios contain more accounts than teams can work at once, the question isn’t simply, “How many accounts can we work?” It is, “Where can our resources have the greatest impact?” The latest Recovery Scores model helps organizations sharpen placement and treatment decisions. It gives debt buyers a way to price and segment portfolios with greater confidence and gives lenders another tool to direct limited collector time across their own post-charge-off portfolios. Learn more about Experian Recovery Scores

November 10, 2026 by Zohreen Ismail
What Is a Third-Party Breach? How to Prepare for and Respond to Vendor Incidents

Learn what a third-party breach is and steps to prepare, contain risk, and support affected customers. Read more!

November 9, 2026 by Laura Burrows
Mortgage Underwriting Moves from Modernization Talk to Action 

Mortgage underwriting is entering a new phase. In a recent conversation with HousingWire’s Allison LaForgia, Michele Bodda, Group President of Experian Housing, Verification Solutions, and Employer Services, discussed how modern credit scores, alternative data and verification tools are changing how lenders evaluate borrowers.  Lenders can now judge modernization by its results, Bodda said. “Now we’re actually letting more modern scores get into underwriting to help price loans and go all the way through to securitization,” she told HousingWire. “We’re letting the scores and the data actually speak for itself instead of just talking about it.”  The Right Data at the Right Time  Modernizing underwriting means providing useful information at the right stage, rather than giving lenders everything at once. “You don’t need everything all at once. You don’t need everything on initial pull,” Bodda said.  Alternative data, such as rental payments and buy now, pay later activity, can help show how consumers manage obligations, especially those with thinner credit files. A thin credit file does not necessarily mean someone has a thin financial life.  “It’s our responsibility as one of the primary data providers to make sure we can make all of that available, so that we’re best representing the consumer,” Bodda said. A fuller view of data may help lenders identify creditworthy applicants who might otherwise be difficult to assess.  Simplifying Verification and Reducing Friction  Bodda also shared how Experian is making credit information more easily accessible and reducing unnecessary costs during the originations process, explaining that new enhancements to Experian’s Power Profile Plus allow lenders to pull credit data at the start of underwriting and request another score later without repurchasing the data.  “You can pull it later and not pay for the credit data again,” Bodda said.   Experian is also investing in income and employment verification, including through a new partnership with Workday. Bodda explained that Experian will continue to focus on process improvement, competition and innovation across the mortgage ecosystem.  A Broader Path to Homeownership  As consumer expectations and underwriting capabilities evolve, borrowers want a process that reflects their financial lives, while lenders seek greater efficiency. Modern scores, relevant data, and streamlined verification can help lenders assess applications with more context—and may help more people pursue homeownership.  “If we as an industry can open this up and bring more people into the process, then we’re going to thrive,” Bodda said in the interview.   Watch the interview and hear all of Michele’s insights, and more here.  

November 6, 2026 by Caroline Basile

Subscribe to our Newsletter

Enter your name and email for the latest updates.

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Subscribe to our Newsletter

Don't miss out on the latest industry trends and insights!
Subscribe