$350 BN OF PPP LOANS WERE DISBURSED IN TWO-WEEKS: WHAT FAILED?

The PPP program was intended to provide immediate liquidity to small and medium-sized businesses unable to otherwise weather the economic effects of the Covid-19 pandemic. With evidence from the disbursement of the 1^st tranche of $350 billion, we can now ascertain that the program has systemic design flaws with significant implications:

– Lack of specificity of borrower base: The program does not differentiate between companies that are completely shut-down, and those operating at 50% or 100% capacity. The government did not provide guidelines to prevent profitable companies, able to weather the storm without the stimulus, from applying. Only one line in the PPP applications refers to the consequences of C-19: “Current economic uncertainty makes this loan request necessary to support the ongoing operations of the Applicant.” Some recipients were publicly traded companies that already had significant liabilities with big banks. Others were existing loan customers of banks that owed money back. Thousands more that lacked the right ties were not approved.

– Likelihood of moral hazard: As part of the program, borrowers have no incentive or obligation to pay back the money; if a business maintains the current payroll for 60 days, then the loan can be forgiven. This creates — even encourages — conduct that would normally be considered fraudulent and no wording in the application explicitly prohibits such behavior. The loans are intended to help small and medium businesses that are currently shut down or severely suffering, not major restaurant chains (e.g., Shake Shack) and conglomerates. When the federal government rolled out the program, more than 70 publicly traded companies were among the first in line. They secured a total of more than $260 million from the loan program, according to Securities and Exchange Commission filings. One analysis identified 83 public companies that had collectively borrowed more than $330m from the PPP, on average $4 million each, though the SBA has trumpeted that the average loan for the program was just $200,000 among all recipients.

– Payback to large lenders: In the absence of specific SBA guidelines, large lenders are acting in their self-interest favoring existing clients with outstanding loans. By doing so, banks are effectively issuing new SBA-guaranteed debt at no risk to existing debt holders which will use those funds to service pre-existing loans. To further support large lenders, the Fed established a secondary market for PPP loans, and where the end buyer will be the Fed itself. Therefore, despite its original intent, the PPP has mutated to a profitable handout to larger lenders. While the Fed buying the loans would certainly free up bank balance sheet space to issue more loans, a logical question arises: why are banks being allowed to charge regular loan origination fees to intermediate this process if all they are doing is convert government capital into loans and then sell it back to the Fed?

– Exclusion of Fintech lenders: Fintechs received the green light to become PPP lenders from the SBA as late as April 14th, 2020, effectively remaining outside of the 1^st tranche of PPP funding. The result was that dozens of Fintechs with existing relationships with small businesses were left-out of the program.

– Politics over economics: On a geographical basis, loan amounts for firms were approved at a very high percentage in Central, Midwest, Rust Belt, and Southern states, compared with lower numbers for coastal ones. Empirically, it appears that Republican states were favored to a higher degree than Democratic states (see Exhibit 2).

Exhibit 2: Politics vs. Economics

$320 BN RE-FILL HAS BEEN APPROVED: LIKELY NOT ENOUGH

On April 21^st, 2020, the government agreed on $484 billion of additional funding for small business. Approximately $320 billion is expected for PPP alone, of which $60 billion would be spent for firms that have struggled to receive loans from banks, including businesses without relationships with traditional lenders. The deal is also likely to provide $60 billion in new funding to a separate small business program, Economic Injury Disaster Loans.

As indicated in Exhibit 3 below, for most industries the 1^st tranche of $350 billion in PPP loans was insufficient to cover payroll cost alone for an 8-week period. In March 2020, economists Michael Strain and Glenn Hubbard proposed a $1.2 trillion fund, which according to their estimates is roughly equivalent to “replacing 80% of the revenue for 3-months of private-sector firms with fewer than 500 employees, excluding the manufacturing, health, education, and finance industries.” In other words, even considering the 2^nd tranche of PPP the US is still ~$500B short of protecting small business paychecks.

Therefore, depending on the duration of the lockdown, one can assume lawmakers will continue to consider additional relief measures for small businesses. If these were to come in the form of additional PPP loans, we recommend a few structural modifications to the program based on the lessons learned:

– Optimize fund allocation: First-come, first-served is a difficult process to manage, and yield improper allocations. Allocation of funding by SBA regions leveraging unemployment claims data will be a better approach.

– Restructure origination fees: Re-design fee structure based on the desired intent (i.e., more loans for the smallest businesses). The fee for originating a PPP loan in the highest tier is almost 10x the lowest level. Making the fee discrepancy relatively less punitive might reduce the incentive to gravitate toward the larger loans Or, more simply, allocate the new funding by tier.

– Transparency campaign: Vocalize that all businesses receiving PPP funding will be made public. As wisely argued by the National Venture Capital Association, this will be a disincentive for potential borrowers who apply when they have other viable funding options.

Exhibit 3: PPP loans as a share of eligible expenses largely went to hard-hit sectors

OUR PERSPECTIVE: AN OPPORTUNITY FOR REGIONAL BANKS AND FINTECHS TO GAIN MARKET SHARE

In its current form, the PPP design is skewed in favor of larger lenders and larger borrowers. Under this regime, both smaller lenders – including Fintechs – and smaller borrowers have struggled to carve-out a share of the PPP loan market.

Replicating their efforts in the aftermath of the 2008-09 Great Recession, small lenders and Fintechs must capitalize on the customer frustration against large banks. Both have existing deep relationships with small businesses, including mom-and-pop shops and local operators, which are typically perceived as too insignificant and risky to borrow from traditional banks. In future tranches of PPP and outside the realm of the SBA-backed loan market, non-large lenders have the opportunity to further penetrate existing client segments and aggressively expand to all high credit-worthy prospects left out of PPP.

To capitalize on the upcoming opportunity, we identified four areas of opportunity for small lenders and fintechs:

01. Rationalize & modernize the PPP loan underwriting process

Banks’ approaches to due diligence for PPP run the gamut. Some are accepting internal payroll records from existing customers, while others want more from both new and existing customers, like proof of good standing.

In what will likely be a digitally-fueled recovery, small lenders can partner with Fintechs to rationalize and streamline processes across the loan disbursement value chain (see Exhibit 4). The pre-Covid SBA 7(a) loan timeline could take up to 90-days; with the technology available today this process should be reduced to hours.

Exhibit 4: Loan underwriting value chain

Below, we report a few notable initiatives for FIs from a few select Fintechs:

02. Capitalize on high credit-worthy SMBs that were ignored by self-interested banks

The Global Financial Crisis of 2008-09 exposed the fragility of credit reports, as well as the inadequacy of the underlying underwriting algorithms. No underwriting algorithm can factor in inherently unpredictable “black swan” events. Therefore, most underwriters simply ignore these rarities, instead basing creditworthiness on factors like payment history. When an exogenous economic shock causes an agent to miss a payment, the underwriting algorithms assume that such agent is suddenly and significantly less creditworthy, contributing to a lending pullback. This pullback creates large-scale inefficiency in the system, as otherwise creditworthy individuals are deemed liabilities by traditional lenders.

In 2008, companies like Lending Club, Prosper, and Money Lion converted that inefficiency into an opportunity by lending to miscategorized high-creditworthy customers. The same is true today as a result of the Covid-19 pandemic. Smaller lenders and Fintechs can further benefit from the fact that large lenders more focused on recuperating outstanding loans from their existing clients, missing out on high-credit rating businesses that maintained healthy leverage and coverage ratios.

03. Utilize non-conventional data sources as prediction indicators

An effective data strategy is already the key driver of growth for financial services firms. As an exemplary case, Live Oak (LOB), a $5 billion regional bank headquartered in North Carolina, having heavily invested in technology to expand its borrower base has become the largest SBA lender by total loan amount as of Q4 2019. However, in the new normal post Covid-19, relying on past years trends to forecast future trends using typical econometrics techniques is inadvisable.

Instead, smaller lenders will need to lean on non-traditional or alternative data sources, and quickly integrate them to be at the heart of a lender’s value proposition. These used to generally include payment history for electricity, gas and telecom bills, rent payments, repayments to payday lenders, etc. More recently, startups and others have provided access to internal databases which can be significantly more accurate in determining the health of a business, allowing to do so in quasi real-time.

As lenders look to assess which geographies and sectors are attractive enough to extend credit, they must utilize different datasets such as OpenTable Reservation data, Uber ride history data, Google Community mobility report, social media sentiment, etc. For e.g., being able to look which counties have continued to see high mobility based on anonymized cell phone tracking and car-sharing ride trips will be an invaluable insight.

04. Lead re-design of Federal assistance through technological ingenuity

Small businesses are heavily reliant on their technology ecosystem. Many are using Square, Clover, Stripe, QuickBooks, Gusto, DoorDash, Mindbody, Toast and other tools that runs their business and shows them sales, orders, customers, appointments, and expenses. Almost every one of these platforms has been granted permission to access—read and write—bank accounts and helps run the business. Despite this open ecosystem where financial data can be shared easily, if a small business needs to apply for a PPP loan, they still need to contact their local bank branch.

As proposed by Andreesen Horowitz, Fintechs need to lead the charge to build solutions that retrieve relevant financial data for each business – much of it unforgeable, like credit card receipts as validated by the credit card processor – and output an instant machine readable package for federal aid. These packages can then go out to any of the 3000+ SBA lenders which can authorize it the quickest. Loan officers, in person visits, scans and faxes can all be eliminated simply by allowing the bank to access the selected financial data. A very complex problem would be reduced to a simple, almost instantaneous process, aided by tools that nearly every small business in the United States uses.

The Covid pandemic has brought with it one of the largest disruptions faced by America’s Main Street. Small lenders and Fintechs must capitalize on their existing relationships and relative agility to cater to small and medium businesses. Firms who innovate quickly will be able to outrank competition and capitalize on customer loyalty for years to come.