How to determine the overall net yield on assets

by Guest Contributor 5 min read June 12, 2013

By: Joel Pruis

So we know we need to determine the overall net yield on assets required to cover the cost of funds and the operating expenses but how?  In the movie Moneyball, the Oakland A’s develop a strategy to win 99 games by scoring 814 runs and only allowing 645 runs by the opposition.  In order to generate the necessary runs, Peter Brand boils down all the stats into one number, on base percentage.  By looking at the on-base percentage of all the players in the league, Brand is able to determine the likelihood of generating runs.

There are a few key phrases/quotes from this scene that need to be highlighted:

  • “it’s about getting things down to one number”
  • “People are overlooked for a variety of biased reasons and ‘perceived’ flaws.”
  • “Bill James and mathematics cut straight through that [biased reasons and perceived flaws].”

Getting things down to one number is the liberating element for the Oakland A’s and for banking.  We have already identified the one number for banking – Net Yield on Assets.  Let’s define this a bit further though.  For this exercise, net yield means the gross yield (interest income plus fee income) on assets less charge offs.  We are looking to see what is going to be the consistent return on the assets less what can be expected net charge off related to the assets.

When Billy Beane and Peter Brand got it down to the one number “On Base Percentage” it altered the player selection process and highlighted the biases of the scouts such as:

  • Giambi’s brother was “getting a little thick around the waist”
  • “Old Man” Justice
  • Justice will be “lucky if he hits his weight” in July and August
  • Justice’s “legs are gone
  • Hatteberg “can’t throw”
  • Hatteberg’s “best part of his career is over”
  • Hatteberg “walks a lot”

None of the above comments used any facts or data to disprove each player’s on base percentage.  Can you imagine if they were underwriters or lenders?  What type of compliance issues would we have on our hands with the above comments?  Biased against disabilities (Hatteberg with nerve damage); Age Discrimination (“Old Man” Justice), Physical Appearance (Giambi’s brother “getting a little thick around the waist”), these scouts would be a compliance liability let alone obstacles in any type of organizational change.

But one can readily see how focusing on one number liberates the thinking and removes the old constraints or ways of thinking.  One of the scouts commented that Hatteberg had a high on base percentage because he walks a lot, considering a walk as a negative while a hit is a positive but why? Why is getting on base by being walked a negative but getting on base with a hit is positive?  The result is the same as the movie points out.

How about in commercial lending?  If we focus on net yield on the portfolio as the one number, does that do anything to remove biases?  I believe that it does.  One example is the perception of charge offs in a portfolio.  To this day the notion of a charge off in a commercial portfolio, even in the small business portfolio, is frowned upon and can jeopardize one’s career.  Similar to the walk, the charge off is not desired but if we focus on the one number, net yield, it actually removes the stigma of the charge off!

If we need at minimum a 6% net asset yield and we are able to generate a gross yield of 9% with an expected loss rate of 2%, we actually exceed our “one number” of a targeted net yield of 6% with an expected net yield of 7%.  With that change that removes the biases and flawed perception, can we now start to find opportunities that provide us with the ability to step away from the norm; stop competing with the rest; and generate that higher return that is required?  What are the potential biases and flawed perceptions that will need to be addressed?

  • “High Risk” Industries?
  • “Undesired” Loan types?
  • Consumer vs. Commercial?
  • Real Estate Secured vs. Unsecured?
  • Loans vs. Treasuries or other earning asset types?

But just as in the movie, you need to be prepared for the response you may get from the traditional ‘seasoned’ lenders in your organization.  When Billy Beane puts the new strategy into place at the Oakland A’s, the lead scout responds with:

  • “You don’t put a team together with a computer”
  • “Baseball isn’t just numbers, it isn’t science.  If it was anybody could do what we do but they can’t.”
  • “They don’t know what we know.  They don’t have our experience and they don’t have our intuition.”

Ah, just like the traditional baseball scout is the traditional commercial lender with the years of experience, judgment and intuition.  I used to be one and used almost word for word the same argument against credit scoring and small business before I truly understood what it was all about.  Don’t get me wrong.  Experience, judgment and intuition is valuable and necessary.  But that type of judgment  tends to get into trouble when it stops looking outside for data and only relies on past personal experience to assess the next moves.  Experience is always important but it has to continually review, assess and interpret the data.

So let’s start looking at the different types of data.

On deck – How do we know how many runs the opposition is going to score?  The use of external data.

Related Posts

Workflow Automation for Financial Services

Manual processes are quietly expensive. Every handoff between teams, every file transfer waiting in a queue and every decision that sits on someone's desk adds cost, introduces risk and slows the customer experience. For financial institutions, those delays translate directly into lost revenue and eroded margins. That’s why workflow automation is becoming critical for financial institutions looking to stay competitive. Done well, it doesn't just make existing tasks faster. It reshapes how decisions get made across the entire customer lifecycle, from the first marketing touch to account servicing and beyond. What is workflow automation? Workflow automation is the use of technology to run a sequence of tasks, decisions and handoffs with minimal manual intervention. Instead of a person moving work from one step to the next — pulling data, applying a rule, routing an account and sending a communication — software executes those steps automatically based on defined logic and real-time data. For financial institutions, workflow automation usually combines four ingredients: Data Connecting to the internal and external data sources that inform a decision. Analytics Scores, models and attributes that turn raw data into insights. Decisioning A rules engine that determines the right action for each customer or account. Execution The operational layer that carries out the action, whether that's an offer, a credit line change or outreach. The benefits of workflow automation The value of automation goes well beyond "doing the same thing faster." The benefits financial institutions consistently see include:Greater efficiency and lower operating costsAutomation frees underwriters, analysts and agents to focus on exceptions and high-value work rather than repetitive processing. Faster, more consistent decisionsA credit application that once waited in a queue can be assessed in real time against consistent, auditable policies, improving both the applicant's experience and portfolio quality. Better customer experiencesAutomation enables financial institutions to personalize communications at the point of interaction and offer the self-service options that many people now prefer. Improved compliance and governanceReduce the risk of costly compliance failures with built-in controls, audit trails and guided workflows. ScalabilityRespond to changing volumes without sacrificing speed, consistency or the customer experience. Where workflow automation makes the biggest difference Workflow automation tends to deliver the most value where decisions are frequent, repeatable and informed by data. In financial services, those opportunities exist across the customer lifecycle. Onboarding Onboarding is a customer's first experience of your organization, and it's also where friction can cause customers to abandon the process and turn to another provider. Forty percent of U.S. consumers have considered walking away from opening a new account when the process felt burdensome.1 An automated onboarding workflow can bring together document verification, device intelligence, behavioral analytics, credit attributes and more, then orchestrate them into a single decision. The result is a lower-friction experience for the customer and a consistent, auditable process. Once customers are on the books, serving them well means making continuous, high-volume decisions: credit line changes, cross-sell and up-sell opportunities, risk monitoring and retention actions. Automation makes it practical to run these recurring decisions consistently across an entire portfolio, using a holistic view of each customer that draws on multiple scores and attributes. Lending The underwriting process is a great example of how workflow automation can help prevent applicants from waiting days for an answer. Loan origination and credit decisioning capabilities are designed to create a seamless review process across consumer and commercial lending. After automating originations with our solutions, Michigan State University Federal Credit Union cut application processing time to under 24 hours. Fraud Financial institutions are checking fraud at every touchpoint, and the standard for AI fraud detection continues to rise as fraudsters use AI to slip under the thresholds of any single detection tool. Rather than running fraud checks in isolation, an automated workflow can run multiple fraud and identity verification services in parallel and weigh signals together. A fraud decisioning platform connects signals across internal systems, Experian data and third-party services, allowing teams to stay on top of evolving threats. Build a strong foundation for workflow automation Workflow automation can connect these stages, creating a consistent decisioning framework. What ultimately separates good automation from great automation is the quality of the data and decisioning software underneath it. An automated workflow is only as good as the information feeding it. That's where our comprehensive credit, alternative and identity data with the tools financial institutions need to act on it. Learn more here What is workflow automation in financial services? It's the use of software to execute sequences of data gathering, analysis, decisioning and action. How does automated decisioning improve credit decisions? Automated decisioning applies consistent logic to every account in real time or in bulk, enabling faster and more informed decisions, quicker responses to market and regulatory changes at the point of interaction. Does workflow automation replace human judgment? No. The goal is to automate routine, high-volume decisions so skilled staff can focus on the exceptions and complex cases that genuinely require human judgment. For example, a sensitive collections conversation or a nuanced underwriting call. Are we still compliant with regulations if we use an automated workflow process? Well-designed platforms include built-in governance, audit trails and compliance controls that help institutions align with requirements like the Fair Credit Reporting Act (FCRA) and other regulatory guidelines improving compliance compared with manual processes. How long does it take to implement? It varies by solution and scope, but modern cloud-based platforms are designed for fast onboarding and limited IT involvement. 1.Global Fraud Snapshot 2025: Opportunities and challenge in identity, fraud and financial crime

September 9, 2026 by Zohreen Ismail
Expanding the Prescreen View with Alternative Credit Data

Start with a simple question Credit prescreen is an important tool in many lenders’ growth strategies. But the precision of any prescreen strategy depends on the data behind it. What financial behavior might traditional credit data alone not reveal? With Clarity data now available for Instant Prescreen decisioning, lenders can bring alternative credit insights into their targeting strategy, helping them identify prospects who may align with their established criteria, refine targeting strategies and explore additional acquisition opportunities while maintaining control over their risk thresholds. Additional insights alongside traditional credit data For many consumers, a traditional credit file tells a rich and reliable story. But it doesn't always tell the whole story. Consumers may also be using alternative financial products, such as small-dollar installment loans, single-payment loans, auto title loans or rent-to-own agreements and building payment histories that provide additional signals about their financial behavior. For lenders, those unseen signals can represent untapped opportunities. With more than 60 million unique subprime identities, Clarity's database helps lenders gain a more complete view of their applicant pool. Clarity data adds another dimension to that view, providing alternative credit insights that can help lenders better understand consumers whose financial behavior may not be fully represented by traditional credit data alone. How Clarity data sharpens instant prescreen decisioning Clarity provides specialty alternative credit data, with insights into subprime and near-prime consumer activity that may not appear in traditional credit files. And because Clarity is part of Experian, those insights can now be brought directly into Instant Prescreen decisioning. That means lenders can incorporate additional attributes and scores into their credit decisioning strategies without managing a separate data feed or stitching together disconnected sources. It has quickly become a visibility gap lenders can't ignore. Additional data may help support more granular segmentation and targeting strategies. Lenders remain in control of their criteria and risk thresholds while gaining additional information to inform their prescreen strategies. When considered alongside traditional credit data, alternative credit insights can support several aspects of prescreen decisioning: Identify more opportunities: Surface qualified prospects who may be harder to identify using traditional credit data alone. Refine targeting: Add alternative credit insights to help differentiate consumers with greater precision. Inform offer strategies: Use a broader view of financial behavior to help align consumers with appropriate offers. Expand intelligently: Explore incremental audience opportunities while maintaining control over your established risk criteria. Simplify execution: Access Experian and Clarity insights within a connected Instant Prescreen decisioning environment. See more opportunity in your prescreen strategy Growth doesn’t always require looking for an entirely new audience. Sometimes, it starts with seeing more in the audience already in front of you. By bringing Clarity data into Instant Prescreen, lenders can add another layer of insight to their decisioning, helping identify incremental opportunities, refine targeting and support acquisition decision processes across a broader range of consumers. Explore prescreen solutions

September 3, 2026 by Zohreen Ismail
Are Fraudsters Building Better Identities Than Your Customers?

Fraudsters are getting surprisingly good at onboarding. Sometimes, better than your customers. Legitimate customers treat onboarding like an errand. They start an application between other tasks, get distracted, forget a password, switch devices, upload a document or come back later to finish. Their digital lives aren’t always linear, because real life isn’t either. Fraudsters approach onboarding differently. For them, opening an account is the objective. Every interaction is designed to increase the odds of success. The difference raises an uncomfortable question hanging over onboarding: What exactly are we rewarding? When smooth becomes suspicious Digital onboarding has traditionally rewarded experiences that feel smooth, consistent and complete. The challenge is that legitimate customers rarely behave that way. Most people approach onboarding somewhere between mildly distracted and mildly annoyed. They pause halfway through because dinner is burning. They reopen an old account only to realize everything is attached to an email they made in college and, somehow, still use for airline receipts. Digital life accumulates history unevenly, because ordinary life does too. Fraudsters have every reason to eliminate those inconsistencies. Applications may be rehearsed. Identity attributes are assembled deliberately. Contact points are prepared in advance. Every interaction is optimized to make the application appear credible. Ironically, the qualities organizations often associate with confidence — clean submissions, steady progression and few corrections — can also describe applications that have been carefully engineered to pass inspection. The challenge isn't that smooth onboarding is meaningless. It's that smooth onboarding, by itself, doesn't tell the whole story. Context changes interpretation A smooth onboarding experience should be the beginning of the evaluation, not the end. Behavior provides important context. How someone moves through an application can reveal whether the experience feels naturally human or unusually orchestrated. Do they interact naturally? Do they hesitate, correct mistakes or navigate in ways that resemble ordinary human behavior? Or does the session appear unusually scripted, automated or repetitive? Identity verification adds another layer. Matching information across trusted sources, validating identity details and strengthening confidence in account creation remain important, particularly when onboarding decisions carry financial, fraud or customer experience consequences. But verification largely answers a point-in-time question: Does this information match right now? A third layer comes from digital history. An inbox attached to years of airline receipts, loyalty accounts, subscription renewals, account recovery, financial notifications and familiar digital routines introduces a different kind of confidence. Legitimate digital identities leave behind patterns of persistence and engagement that develop gradually over time. Fraudsters can assemble convincing identity attributes, but creating years of ordinary digital life is much harder. Building confidence in an identity requires more than verifying information submitted during a single onboarding session. It requires understanding whether the identity reflects a broader history that supports what the application suggests. A multilayered approach builds stronger identity confidence No single signal can provide a complete view of identity risk. Organizations need multiple sources of confidence that reinforce one another. That's the thinking behind our approach: combining behavioral intelligence, identity verification and digital identity continuity into a more complete view of risk. We bring these complementary layers together through: • NeuroID adds behavioral context during onboarding and account creation, helping identify interaction patterns that may indicate automation, manipulation or coordinated fraud. • Precise ID® strengthens identity verification and resolution by comparing applicant information with trusted identity data. • AtData, recently added to our portfolio, contributes email-centered intelligence based on persistence, engagement and long-term digital history. Together, these capabilities help organizations move beyond evaluating a single moment in time to understanding whether an identity is supported by consistent behavior, trusted identity data and an established digital history. The future of fraud prevention isn't about rewarding the smoothest application. It's about recognizing the most trustworthy identity. Fraudsters can rehearse an application. They can optimize an onboarding journey. They can even assemble convincing identity attributes. What they can't easily manufacture is years of ordinary digital life. That's why digital identity continuity has become an important layer of modern fraud prevention. Combined with identity verification and behavioral intelligence, it helps organizations distinguish between identities that simply look convincing and those supported by a history that is much harder to fake. Learn more Contact us

September 2, 2026 by Julie Lee

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