Attempting to navigate safely through the uncharted territory of a pandemic-triggered recession for the first time, lenders are grappling with assessing the highly nuanced long and short-term effects on SMB credit risk. It is time to rethink credit risk analysis and move quickly to build far more robust, real-time data and analytics into SMB credit-decision models. Now more than ever before, the need to efficiently ingest and synthesize massive amounts of data from a wider array of available sources is critical.
This COVID-19 pandemic is a crisis that has affected human lives the world over. Local, state, regional, and even national economies were forced to effectively close for weeks if not months, causing existential challenges for many thousands of citizens and SMBs. And the pandemic remains dangerously active. According the the Johns Hopkins University, tragically we are starting the month of September in the United States alone with over 6 million confirmed cases of COVID-19 and over 180,000 deaths.
With shutdowns and stay-at-home orders now being gradually lifted to varying degrees throughout the country and businesses restarting, lenders are faced with a very unfamiliar and challenging mandate: quickly learn to evaluate and monitor credit risk in new ways as most of the old methods offer highly limited real-time visibility and little access to actionable data. The path forward requires the ability to understand the impact COVID-19 countermeasures have had as varied, based on the intersection of industry, geography, and each individual business. Additionally, new ways of quickly assessing and verifying the pre-COVID-19 and post-COVID-19 financial trends for each SMB relative to one another must be established.
Even more than before, robust data and analytics are at the center of the discussion. Accelerating digital transformation to facilitate the ingestion and synthesis of ever growing amounts of data and feeding it into today's more mature decision and monitoring models is the only prudent path forward for the majority of lenders.
Following are actionable recommendations to help lenders rethink credit risk analysis post COVID-19.
Not all industry-level economic shocks from COVID-19 are created equal. For example, whereas brick and mortar retail and automotive services industries may have experienced similarly intense initial economic impacts, it is highly likely that automotive services will recover much more quickly as the U.S. economy slowly reopens. People need to get their cars inspected and serviced, but they can buy most of their goods online.
Organizing your current portfolio this way and creating a matrix that combines results from a lender's industry-specific risk models mentioned above, will allow you to identify your greatest current portfolio risk areas and inform your response strategy and go-forward credit decisions for similar borrowers. Monitoring portfolio performance and adjusting as the recovery story evolves will help lenders spot and respond quickly to trends, protecting their portfolios from preventable deterioration.
Operating account bank data is a treasure trove of data. Looking at inflows, outflows, daily balances, number of NSFs, overdraft credit line usage, rent, utilities, payroll (etc.) payment inconsistencies, and evidence of additional borrowing activity with an eye for trends and material changes can often tell a lender most of what they need to know about the financial health of a borrower in real time. Compare that to looking at a tax return from 2019 as a proxy for a business's current financial health or interim financial statements which can be dubious. Both tell you something, but certainly not nearly enough in this environment.
There are myriad tools that are readily available that, when taken together, can provide key, nuanced insights when it comes to creditworthiness, current financial condition, and fraud prevention. Get up to speed on what tools others are using and how they are using them to generate a more complete borrower picture. The amount of data available today to help lenders assess credit risk and fraud is vast and easily integrated digitally to a lender's risk platform, especially if it is in the cloud.
Alternative data sources to the standard go-to sources are helping lenders paint a more complete and current picture of SMBs and personal guarantors' financial health and creditworthiness. In addition to the aforementioned business operating account transaction data analysis, cloud-based lending technology stacks have enabled modern lenders to crunch mountains of data from a vast number of sources quickly to establish baseline proprietary PD and fraud risk scoring and monitoring. This includes data such as social media and online sentiment analysis, comparative macro economic data, credit card processing data, and even virtual site inspections.
Lending technology has advanced greatly in the last decade. With the right technology platform, it should be very easy to answer questions such as this: "Had we adjusted our credit model in x way, would the result (y) have been lower losses during COVID?" Then do it again and again until statistically meaningful results emerge. With a few keystrokes, technology exists today to allow lenders to run scenarios and rescore existing portfolios to gain deep insights as to what might have been. These same insights help astute lenders make valuable presumptions about whom to lend to not only now during the COVID recovery period, but also as part of the normal course of business.
All of the above should arguably be general practice for lenders in 2020. Technology has made all of this easy and intuitive, and it does not have to be expensive and time-consuming to implement a highly powerful solution. The borrower, analyst, underwriter, processor, and chief risk officer's user experience should be frictionless and enable valuable risk management insights and tools in this day and age.
With the right platform, lenders can seamlessly integrate in the cloud to credit bureaus, alternative data sources, online banking data, and risk mitigation services. Additionally, more data can be ingested and synthesized faster and portfolio performance can be measured and risk models can be calibrated in real time, including advanced warning systems to give lenders a chance to take mitigating action and avoid being blindsided.
If anything positive comes out of the COVID-19 pandemic for SMB lenders, it will be that they were forced to accelerate their digital transformation plans. If implemented properly, the benefits as we come out of this crisis will be truly transformative.
Richard Henderson is an equipment leasing & finance industry veteran and fintech expert leading growth for Capiform, a SaaS-based, comprehensive, fully configurable digital lending application enabling financial institutions to embrace the digital lending age at their own pace.