SFR Tenant Underwriting

Tenant underwriting for SFRs (& multi-family residentials) used to be straightforward just a few years ago. Ensuring three basic checks would be enough - credit, income & criminal. A tenant who could afford a $2000 rent per month would automatically be considered low risk.

But the situation today is very different. Rents everywhere are $2000 or above, and tenants seem to afford them & yet SFRs have to clean up the non-performing portion of their portfolio from time to time.

The SFR (& multi-family residential) industry has been assuming tenant underwriting as a basic screening exercise rather than a key lever to control consumer risk in their portfolio. A big challenge here is that the data accumulates slower compared to credit products and there is no absolute store of the consumer rental track record which can enable better understanding for the industry.

Industry has been commonly using common credit scores like FICO or Vantage which were not built for rent. Past rental history has been ignored in the underwriting process as it has been hard (& costly) to get but it's the most useful piece there is to assess future rent payment activity. Fraud is a growing problem which is often understated due to the tendency or the belief that it's hard to execute fraud as in-person interactions are involved. Cash Flows are overlooked in budgeting often causing tenants who end up struggling & are always behind. Often insufficient reasoning is provided to the customers for application decisions. Finally, consumer & property quality are considered in silos when they are highly correlated.

Here we examine these common fallacies which the industry should be more aware of & try to address so that more expensive outcomes can be avoided later.

FICO: not for rent

FICO & Vantage scores were not built to predict rent payments. As a result these industry standard credit scores are not a good predictor of customer’s willingness to pay their rents in future. It does distinguish customers in terms of their risk on a broader scale but fails to show any distinction within smaller bands. Therefore a small shift in minimum score thresholds would hardly get any meaningful results.

Industry standard scores put a lot of weight on recent delinquencies on customer’s cards & loans but fail to recognize that under normal circumstances consumers prioritize their housing payments (rent or mortgage) in their payment hierarchy. A consumer which missed a payment on card or personal loan a few months ago doesn’t directly mean a high risk for their rent payments too. These scores also don’t consider all emergency options available for the customer during tough times in the form of available balances, liquid investments or even card limits.

Cashflows stability and assets do matter a lot as an additional source of data apart from credit history for identifying consumer risk. However, cashflow underwriting products and risk scores which are increasingly used in credit & lending underwriting also miss out on targeting to predict rent payments thereby neglecting the customer payment hierarchy.

Industry has been leveraging higher deposits for deep subprime customers as a measure to control risk which actually stems from lack of visibility into consumer’s cashflow stability & emergency options.

Rent predicts rent

Best predictor for willingness to pay future rent payments is past rent payments. However, there is no definitive store of rental payment history unlike credit history. Note that credit bureaus do not carry any significant rental payment history in their mainfiles. There are other options like Experian RentBureau & Trigo, but they are expensive & coverage is not great. With increasing focus on rent reporting & data sharing/furnishing by institutional landlords, this coverage should increase over time.

Negative rent history can also be verified through eviction filings & judgements. Background check providers include this historical eviction data. Note that, very old evictions tend to fade in their prediction power & the data may not be accurate due to eviction moratoriums & out of court settlements like cash for keys.

Customer’s banking data can also be used for verifying recent rent payments. But most cash flow underwriting products miss out on identifying rent as a key transaction category.

Budgeting matters

Industry has improved its ability to do rent pricing, but still operates on simple metrics for customer’s rent budgeting. It often causes customers to over budget for rent and makes them continuously struggle to pay rent month over month. Struggling tenants put a drag on the portfolio operationally and end up in vacancies one way or another. Either landlords budget the rent using rent to income (RTI) ratio, or debt (debt+rent) to income (DTI) ratio. Neither is a robust method of budgeting for rent. RTI doesn’t pay attention to other debts. Whereas applying only DTI for a customer assumes that those without debt payments now will never need anymore debt & can use all their disposable income on the rent.

With increasing rents, housing affordability in the US has come down significantly & a simple 30% (RTI) rule can not be applied these days. However, budgeting can be done in a smarter way. Following both RTI & DTI caps, budgets customers for all times & seasonality. Cash flow data matters a lot here too in addition to income verification. Income stability & expenses relative to the income levels ultimately dictate customers' rental budget appetite.

Growing Fraud, Squatters & Misuse

Background check matters to stop potential misuse by criminals & avoiding squatters. Checks should contain criminal history, sex offender registries & national terrorist watchlist. However, background checks often create a bias against underserved applicants & should not consider immaterial crimes which have not much to do with property misuse or rent payments. Instead of blanket application of all types of criminal records throughout history, a thoughtfully designed criminal check based on the seriousness of crimes & their recidivism rates for lookback periods is needed.

Due to decreasing affordability, eviction moratoriums & slow eviction proceedings, industry is observing an increasing level of all types of fraud. Tighter income & banking verification along with document fraud checks controls first party fraud to some extent. Verifying backgrounds of all adult residents instead of just earning applicants may control for second party fraud. However, the best approach is to be proactive & start using fraud data providers (e.g. Sentilink, Socure) & their scores for first, second & third party frauds. Fraud data vendors have been prominently used in consumer credit & lending but not so much in SFR tenant underwriting yet.

Lack of Explainability

Landlords most often use reason codes from credit bureaus to provide application decision reasoning. However, all reasons should be accurately shared with a customer about why an adverse action was taken. All data sources should be cited so that customers can contest them if in case inaccurate. Also, reasons should be provided for all adverse actions including approval with higher deposits. CFPB & FTC have taken several actions recently for incorrect data in tenant screening by traditional background check providers & credit reporting agencies. Note that providing accurate reasons doesn’t mean institutional landlords can not use custom scores & solutions. Custom scores & solutions can in fact be built to reduce bias & increase explainability with accurate adverse actions.

Consumer-Property Correlation

Most institutional landlords consider asset risk/quality & consumer risk/quality in silos. However, they are both highly correlated. Low quality assets may look attractive with higher yields & cap rates, however they also attract low quality tenants. Asset quality here is multi-dimensional & considers neighbourhood, maintenance, structure etc & not just market value related. Property’s quality & its market rent can provide a good enough idea of the kind of tenants which it will attract. This correlation doesn’t mean that landlords should buy only high quality assets/properties, but a smart landlord will bake this correlation into their market & asset selection upfront so that they can find the sweet spots to maximize their portfolio yield & minimize operational workload.

For more such in-depth articles on the industry, please sign-up to Fincepta blog.

Fincepta provides custom solutions for better asset & consumer underwriting for single & multi family landlords. Please connect with us at info@fincepta.com to learn more.