The Keys to Loan Segmentation Success
As any banker can appreciate, portfolio theory is worthy of a Nobel Prize, literally. In 1952, Harry Markowitz – all of 25 years old then – developed the paradigm that blew away Nobel judges and influenced countless financial services professionals. And who in turn influenced Markowitz? Turns out the Bard was on Markowitz’ reading list, as he quoted “The Merchant of Venice” in a 1999 paper: “My ventures are not in one bottom trusted, nor to one place.” “Clearly,” an admiring Markowitz wrote, “Shakespeare not only knew about diversification but, at an intuitive level, understood covariance.”
If Markowitz were to borrow from Shakespeare today, the question might well be “To segment, or not to segment?” Today more than ever, the former applies: Financial institutions need to double down on portfolio segmentation as they work to truly understand their business loans. But how can they do this? And what are the potential rewards?
Looking at Loan Portfolios
As the Current Expected Credit Loss standard (CECL) comes on line, banks must assess their loan portfolios with fresh eyes. CECL is the biggest change to financial accounting standards in generations and for some institutions, quite the intimidator. That’s because the new model requires U.S. financial institutions to estimate life-of-loan losses at origination or purchase.
Here, segmenting the loan portfolio comes into play: organizing it so that loans performing similarly through different economic cycles get grouped together. In tackling this formidable task, remember: Segmenting your existing portfolio will require in-depth analysis and powerful business logic to ensure that you make appropriate decisions.
Yet many financial institutions do not have the historical data in place to make those calculations. For starters, that means a movement away from the days of disparate data silos, spreadsheets and paper files. Put another way, smart segmentation begins with a comprehensive data assessment that creates a holistic view of your current data environment.
Segmentation Art and Science
Another term for loan segmentation is “pooling.” It involves organizing loans in terms of similar risk characteristics. It’s been said that with CECL-based solutions, “one size does not fit all.” So what does fit, then? To sum it up in a single directive: Be specific.
To get a meaningful jump on segmentation, make your loan pools as granular as possible – even as you maintain statistical significance. Pool sizes that strike a balance between granularity and significance will reduce friction and guide the process of future loan elections.
Here, the blend of art and science cannot be stressed enough. If you dig too deep into risk layers and make each successive pool smaller then statistical relevance vanishes, but if you make them too general or indistinct (for example, sorted by loan type and duration) and the result will more resemble a pile than a pool.
Here, the CECL standard as outlined by the Financial Accounting Standards Board (FASB) proves helpful: “Segmentations or pools should have similar risk characteristics. These pools should be as granular as possible while maintaining statistical significance.”
Why segmentation is smart
Institutions have commonly tinkered with loan pools over the years based on input and guidance from regulators and auditors (as in the financial crisis, for example). On the one hand, some banks could dismiss loan segmentation as just another task on the disclosure checklist. But for many, opportunities abound in the movement towards precise loan pooling.
Good loan portfolio segmentation enables institutions to identify underlying risk behaviors, making it a most effective risk management tool. Specifically, segmentation done right creates an effective, efficient process to approach Allowance for Loan and Lease Losses (ALLL), stress testing and other risk management requirements.
What emerges can then create a competitive edge for any size lending institution. Comprehensive loan portfolio segmentation gives credit departments the intelligence they need to quickly identify those underlying behaviors that drive credit risk.
Putting it together: Hit your segment stride
Depending on where your financial institution stands on its journey, loan segmentation will pose many challenges. Factors ranging from size to unique market characteristics will play a role in determining how to tackle the task. For all today’s talk of fintech wizardry and machine learning, no amount of money can purchase the shiny new toy that makes segmentation work at the click of the switch.
But thought of as a process that creates a robust structure supported by the right technology, loan segmentation moves beyond a simple requirement. It becomes an intelligent way to do business and manage loan risk, not just for current portfolios but those loans to come – in areas from tracing activity patterns to strategizing how you’ll store data going forward.
For anyone ready to pursue loan segmentation success, consider turning to Shakespeare, who sums it up well: “See first that the design is wise and just; that ascertained, pursue it resolutely.”
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Posted on December 13th, 2019 at 3:07 pm
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