Profitability Analysis

by Victoria Soriano 4 min read September 30, 2020

Profitability analysis is one of the most powerful analytics tools in business and strategy development. Yet it’s underrated, deemed too complicated and often ignored.

A chief lending officer may state that the goal of strategy development is to increase approvals or to reduce losses. Each one of these goals has an impact generally inversely on each other. That impact may be consequential, and evaluating the effects requires deeper thought and discipline. I propose that the benefits of a profitability analysis in strategy development are worth the additional effort, time and cost.

Profitability analysis provides a disciplined framework for making business decisions. For financial companies, a simple profit and loss (P&L) statement will identify interest income, subtract losses and arrive at a risk-adjusted yield. A more robust P&L statement will include interest expense, loss reserves, recovery, fees and other income, operating expenses, other cost per account, and net income. Whether simplified or fully loaded, a P&L analysis used in strategy development must provide a clear and informative representation of key performance metrics and risks.

The most important benefit of a profitability analysis is its inherent ability to quantify the trade-offs between risk and rewards. In the P&L terminology, we mean the trade-off between expenses and revenue or losses and interest income. Understanding trade-offs allows companies to make informed decisions and explore serious alternatives.

The net income is a concise and elegant metric that captures the impact of various and sometimes competing business objectives. Consider different divisions within a financial organization. Each division has its own specific and measurable objective. Marketing’s goal is to increase loan approvals while Risk is tasked with managing losses. Operations looks to improve efficiencies while IT aims to provide stable, reliable and accurate systems infrastructure. Legal and Compliance ensure regulatory compliance across the entire organization. Each division working to achieve its objectives creates externalities — each division’s actions may not fully incorporate costs imposed on other divisions. For example, targeting highly responsive consumers for a loan product achieves higher loan approvals and may in turn lead to higher credit risk losses. A P&L analysis imposes the discipline for each division to internalize costs and lead to a favorable and efficient outcome for the organization.

The challenge with profitability analysis in strategy development is how to develop a good P&L statement. We look to historical data to define assumptions and calibrate inputs to the P&L. There will be uncertainty and concerns regarding the reliability and quality of such data. Organizations don’t regularly conduct test and control experiments or champion and challenger strategies that provide actual performance information on specific areas of studies. Though imperfect, historical data provides a starting foundation for profitability analysis. We augment historical data with predictive credit attributes, industry experience and understanding consumer behavior and incentives. For example, to estimate interest income we may utilize estimated interest rates combined with balance propensity behavior, such as a balance revolver or transactor. To estimate losses on declined population that may be considered for approval, we infer on-us performance using off-us performance with other lenders.

Defining assumptions is tedious, hard work and full of uncertainty. This exercise once again imposes the discipline required of organizations to know in detail the characteristics of their products and businesses that make them relevant to consumers. We generate P&L simulations using a set of assumptions, acknowledge the data limitations and evaluate recommendations.

A profitability analysis is useful in both times of economic expansion and contraction. A P&L analysis is valuable when evaluating strategies across the customer life cycle. Remember, we live in a world of trade-offs and choices are inevitable.

In the prospecting and acquisition life cycle, a P&L analysis provides insights on approval expansion and the consequences of higher credit losses. Alternatively, tighter lending criteria will have a direct impact on balance growth and interest income with lower losses. In account management, a P&L analysis provides estimates on expanded account authorization limits and the effect on activation and usage. In collections, a P&L analysis provides valuation on recoveries and operational costs. These various assessments are quantified in the P&L and allows the organization to identify other mechanisms such as marketing campaigns, customer services or technology investments in support of the organization’s goals and mission.

Organizations face a full spectrum of opportunities and risks. We propose a profitability analysis to evaluate business trade-offs, navigate the marketplace, and continue to provide relevant financial products and services to consumers and businesses.

Learn more

Related Posts

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
How to Deliver Data-Driven Customer Experiences

A data-driven credit customer experience offers personalization and low friction — it's a win-win for consumers and businesses.

November 5, 2026 by Zohreen Ismail

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