Description

Description

Idea
Open Lending (OL) is a software & analytics provider to auto lenders. Despite its name, it is not a lender. It offers a compelling value proposition for all the players within its ecosystem, customers love the product and churn very rarely, and there appears to be limited competition in what we believe to be a very large TAM. There is also minimal capital intensity and high incremental margins, and the company is run by its founders who own significant equity. Given the end market (auto lending) and revenue model (fee per loan issued and a profit share vs a pure subscription model), it is certainly not immune to cyclicality, but through the cycle we believe OL can grow its revenue at a ~25% CAGR and earn a mid to high teens IRR over the next five years. We believe the market is generally unaware of the business (OL recently became publicly traded via a SPAC in June and is only covered by four sell-side analysts), is skeptical of anything that smells like a tech-enabled lending b-model (see Green Sky, Lending Club, Open Deck) or dismissive of the fact it came public via a SPAC, and likely questions the sustainability of OL’s margins. Our work has given us comfort on all of these potential issues.

Business Background

OL’s software enables lenders that finance vehicles (credit unions, regional banks, and captive OEM lenders) to broaden their loan portfolio to the near-prime market, offer more competitive rates, and reduce credit risk. OL’s data & analytics offering is focused on borrowers with a credit score between 560 and 669 (Non-Prime and Upper Sub-Prime customers). Since inception in 2000, OL has facilitated >$7.5B in auto loans, accumulating 20 years of proprietary data and developed >2M unique risk profiles. The company currently has 300 customers and has tripled its customer base since 2013.

Open Lending was founded in 2000 by John Flynn (current CEO), Ross Jessup (current COO & President), and Sandy Watkins and is based in Austin, TX. Until 2003, Open Lending worked on developing their software and analytics model, and in December 2003, it partnered with CUNA (Credit Union National Association), who invested for a 50% share of the business, and launched the Lender Protection Program. After an 18 month pilot (March 2006), the product was rolled out to credit unions in all 50 states. In 2009, OL bought out CUNA’s interest. In 2010, OL reached an agreement with AmTrust to become the insurance provider for LPP.

In 2016, Bregal Sagemount, a New York based growth private equity firm, invested in OL for a minority stake. During 2017, the company significantly re-architected its software platform, and added a second insurance partner, CNA. In January 2020, Nebula, a SPAC sponsored by True Wind Capital (former KKR partners), announced the acquisition of OL. The transaction closed on June 10th, 2020, and OL became a publicly traded company.

Business Overview

The auto lending market is generally bifurcated into two broad buckets: 1) Traditional lenders (JPM, BoA, etc.) that focus on prime borrowers. This market is characterized by very low default rates and very low interest rates (3.5%); 2) Subprime lenders (Credit Acceptance Corp, Exeter Finance, Westlake Financial) that focus on sub-prime borrowers. This market is characterized by much higher default rates and much higher interest rates (20-25%).

As a result, the “mid-market” tends to see far less efficient loan pricing as the traditional lenders do not want to deal with the risk of this customer base and the operational intensity of servicing it, while the sub-prime lenders are geared towards higher risk and need a higher return to support their more expensive sources of funding. Consequently, the near-prime customer is often serviced at a more expensive rate than their credit profile would merit. This is the area that OL focuses on.

Open Lending offers two services to lenders (but is sold as a packaged offering).

1)      A software & analytics tool that OL has developed (along with 20 years of lending data and >2M+ unique risk profiles) that helps identify which near-prime customers are credit-worthy.

·         A lender may get 100 loan applications from customers with a 600 FICO score, which at a distance, may all look the same, with varying degrees of credit history (thin file, thick file, average file). OL allows a lender to identify which of the thin file (or average file) credits may actually be good credits, and cherry pick the 10 best loan apps.

·         This analytics tool is based on a range of factors such as:

o   Borrower info: FICO score, credit thickness, LexisNexis scores (education records, phone records, utility bills and more) and alternative data sources

o   Loan info: LTV, Payment to income (PTI), loan term (how long), origination channel, etc.

o   Vehicle info: New vs used, make and model of vehicle, vehicle mileage, geographic location

2) A loan insurance program called Lender Protection Program (“LPP”). LPP is an arrangement that OL makes between the lender and an insurance company (OL currently works with two insurance companies, AmTrust and CNA), that enables a lender to limit their potential losses, by offlaying some risk to the insurer.

·         It is important to highlight that OL does not take any balance sheet risk with this insurance program, but it does earn a share of the insurance profit earned after taking into account loan losses.

·         The lender is incentivized to minimize losses as if the vehicle is repossessed and sold at 80% below the book value, the lender will be on the hook for the amount under the 80% of book value, while the insurer would pay the rest.

Using the OL service, the lender can completely customize the type of loan they want to target based on their own unique cost of capital, loan acquisition costs, expected recovery costs and target ROA.

Since inception, OL has facilitated >$75B in auto loans.

The geographic profile of the loans originated is fairly diverse: West (24%), South/Central (19%): Midwest (16%), South (31%), Northeast (10%).

Revenue Model

OL has three different revenue streams:

1)      Program Fees (~40% of revenue).  These represent fees that the lender pays OL and are based on the original size of the loan. On average, a lender pays OL a program fee of $470 per loan or ~2% of the overall loan size.

2)      Administrative Fees (~6% of revenue). These represent fees that the insurers pay OL and are based on 3% of the monthly insurance premium for as long as the loan remains outstanding. On average, the insurer pays OL an admin fee of $65 per loan.

3)      Profit Share (54% of revenue). These represent fees that the insurers pay OL and are based on a share of the underwriting profit earned (premium earned by insurer - insurer expenses – incurred losses). On average, the insurer pays OL a profit share of $615 per loan (they earn 72% of underwriting profits).

All together, ~40% of OL’s revenue comes from lenders while ~60% comes from its insurance partners. On average, OL generates $1,160 in revenue per loan.

Value Proposition

The easiest way to understand OL’s value prop is to walk through a typical example. A non-prime customer decides they would like to buy and finance a used vehicle from an auto dealer. The financing department at the dealer will gather the customer info and send out financing requests through its loan origination software (they usually have a list of 10-15 potential financing partners, each of which specialize in a slightly different customer credit profile). OL is integrated with over 20 3^rd party LOS (loan origination software) systems.

OL is embedded within the lender’s decisioning algo, and can provide a response to the lender within 5 seconds. OL is generally used by lenders in one of two approaches: 1) The lender rejects a loan app on their own underwriting and then passes it on to the OL system to see if the borrower may qualify there; or 2) The lender will utilize the OL system for any borrower within a certain FICO band. After OL makes its determination, the lender can then respond to the dealer. On average, OL will approve 6 out of every 10 loans based on their criteria. The vast majority of OL clients utilize OL for the second approach (any loan within a certain FICO band).

The dealer will then offer the customer the best 1 or 2 financing options, and then the customer decides and will obtain the car. Note that the speed of OL’s decision is critical, as the longer the customer waits for the financing proposals, the less likely they are to buy the vehicle. Also note that the neither the dealer nor the customer is aware that OL is being used – that happens behind the scenes between OL and the lender.

OL is also valuable as a lender still needs to pay the LOS and other fees even for loans it does not ultimately underwrite (time, pull the credit report, etc.), so OL helps eliminate some of this wasted expense by increasing the look to book ratio. In addition, many credit unions don’t have credit staff working in the evening or weekends when some dealers are open, so they are incapable of responding to a non-vanilla customer without OL.

OL offers value for all system participants: the end consumer gets better financing rates, the dealer can sell more vehicles, the lender can issue more loans but within appropriate risk parameters, and the insurer can grow premium volumes with an attractive ROE in an uncorrelated line of biz. Note this example included the dealer (indirect lending for the credit union), but OL can also facilitate direct auto lending as well (a potential borrower goes directly to a credit union to obtain a loan).

The customer calls we have done have been sterling.  Today, the majority of OL’s customers are credit unions along with a handful of regional banks.

It is important to understand that credit unions are in a unique position within the financial landscape: they are non-profits and they cannot raise incremental outside capital. As a result, credit union management and boards tend to be highly risk averse, and quite slow moving. Without OL’s offering, they would not be able to offer much loan exposure to near-prime auto customers, as they do not have the analytical capabilities or risk appetite to do so (most credit unions have a pretty lean staffing model and limited IT budgets).

By partnering with Open Lending, credit unions can offer more loans to their members (or attract new members), that they can hopefully increase their share of wallet with, so the benefits extends beyond just the net interest earned on the auto loan issued.  While there is a “cost” to use Open Lending (2% of the overall loan size in program fees and then higher interest rates due to the insurance program), even the more sophisticated credit union customers don’t view Open Lending as “expensive” – rather they view it is enabling them to make loans they previously could not while not taking undue credit risk. By utilizing OL and shifting down the credit spectrum, credit unions also improve their relationships with dealers.

OL reports a 99% accuracy rate for all loans generated.

As a result of this value proposition, OL has a very satisfied lender customer base. Former OL employees we have spoken with suggest that customer logo retention is >96% and customer losses are very rare. OL also disclosed net retention rate in its prospectus, which aligns with this: 127% in 2016, 127% in 2017, 120% in 2018, 121% in 2019.

Go-To-Market

As discussed above, credit unions are very conservative and slow moving, and have low trust in a new player on the block. As a result, sales cycles are on the longer side, and can range from 6 to 16 months, but probably average around 9 months. The good news is that as OL has grown it has recently landed several larger credit unions who can be used as reference customers, and the word of mouth benefit and credibility of OL is growing. OL’s CEO, along with many of the OL employees, spent their entire careers working in credit unions before starting OL, and so they have domain expertise and extensive relationships. In June 2018, the National Association of Federally Insured Credit Unions (NAFCU), which is the FDIC equivalent for credit unions, named OL as a Preferred Partner, and in June 2020, they named OL an Innovation Award winner. This is a big deal as it is a major seal of approval from an organization that is viewed as a watchdog for bad behavior.

Implementation times tend to take around 2-3 months but can be done in as little as 6 weeks. Once implemented, it takes a bit of time for the credit union to ramp up their loan volumes with OL, but a lender generally starts to hit significant volumes by the 6 month mark. While implementation is not necessarily a quick process, as many credit unions have pretty dated IT stacks, every customer has praised the OL implementation team and blames any hiccups on themselves vs OL. Every customer we have spoken with has also applauded the post-sale service & support.

OL has ~300 lending customers, and had grown its customer base at a ~40% rate in 2018 and 2019 (61 new customers in 2017, 58 in 2018, 77 in 2019). There is not meaningful customer concentration on the lender side: the largest customer is 5% of program fees, while the top 10 customers are 32% of program fees (down from 37% in 2018).

Opportunity with Captives

While OL’s primary customer base to date has been credit unions, and to a lesser extent, regional banks, the company has recently made significant traction with OEM captive financing arms. OEM captives are a very large chunk of the auto finance market (~20%).

In 2019, OL signed two OEM captives. One of the captives is a major domestic and the other is foreign (both are easily ascertainable with some research). OL has estimated that each captive opportunity would represent ~$30M to $100M of revenue (vs a 2019 revenue base of $93M).

The OEM volume began to ramp in the 2H of 2019, beginning in the week of August 18 and with a more sizeable increase in October and November. Loans from captives were ~5% of overall loans for 2019.

Captive #1 started with an 8 month pilot in 1 of 4 geographic regions for those with credit scores of 560-619, and then expanded the program nationwide in April 2020. They are now running an additional pilot to expand the range of credit scores from 560-679.

Captive #2 started in October 2019 but as covid hit, withdrew from near-prime lending, resulting in lower loans over the coming months. OL continues to work with them and expects them to ramp up in Q4.

OL is also currently doing a data analysis (the typical pre-cursor for consideration) for another large captive. The company has also stated that they have multiple OEM customers in the pipeline for launch as early as 2021.

OL also recently hired a new VP of Sales responsible for Captives & Banks, who previously spend 3.5 years at TransUnion, as the Major Account Executive covering Enterprise Automotive, who should be well suited to help open additional doors.

Insurance Partners

OL has two insurer partners: AmTrust and CNA. AmTrust has worked with OL since 2010 and CNA has worked with OL since 2017.

OL’s loans are split 50/50 between the two insurance partners and the terms are identical

AmTrust: OL’s latest contract with AmTrust was amended in July 2017 and ends on 12/31/2023. It auto renews for 2 year terms unless either party provides written notice. AmTrust is the 42nd largest commercial insurer by premium in the U.S. Its top three lines of business are: Workers’ Comp, Warranty, Commercial Auto & Liability, Physical Damage. It has a A- AM Best Rating.

CNA: OL’s contract with CNA ends on 12/31/2023. It auto renews for 1 year terms unless either party provides written notice. CNA is the 10th largest commercial insurer by premium in the U.S. Its top three lines of business are: specialty (management & professional liability), Specialty (Warranty & Alternative Risks), Commercial (Middle Market). It has a A+ AM Best Rating.

Both contracts have non-compete clauses so neither insurer can work with another party like OL

The insurers view the partnership with OL as advantageous as it delivers attractive ROEs and has relatively low capital charges vs other business lines. In addition, insurers benefit because this line is also less correlated to many of their other P&C lines of business. The insurer earns both a carrier fee of 8% of the premium written, along with an 18% share of the underwriting profit, which equates to $325 per loan (or 15% of the premium). Importantly, even if losses turn out far greater than expected, the insurers should still be able to return a healthy profit.

Our research indicates that the P&C insurers are very satisfied with OL as a partner and are eager to take on additional business with them. This is also a small piece of business for the insurers: in 2019 the insurers earned $105M in premiums through the partnership with OL vs combined total net written premiums of >$15B.

Given there are only two insurers, there is significant customer concentration. Revenue from insurers is ~60% of total revenue, so AmTrust = 30% of revenue and CNA is 30% of revenue

Our research suggests OL will likely bring on 3rd insurer within a year, which would further diversify revenue and reduce concentration (would become 20%/20%/20%)

We don’t believe disintermediation from the insurers is likely given they want to be in the insurance business, not the lending business. Having a competing product would take years to develop and require replicating OL’s software & analytics tools, and building out a lender network.

TAM

There were $612B of auto loans originated in 2019, which have grown at a 4.5% 5 year CAGR and a 2.9% 3 year CAGR. 12% ($72B) is from credit scores between 620-659, while 20% ($112B) is from credit scores <620. The share of non-prime customers (32% / $194B) peaked at 45% in 2006, troughed at 30% in 2009, and has remained around 32% for the last 3 years.

OL’s own TAM estimates vary slightly, as they suggest 43% of auto loan originations on “near-prime”, putting their TAM at $250B.

Banks account for the largest share of auto lending (33%), followed by credit unions (31%), then finance co’s (19%) and captives (17%). Captives tend to skew much higher on super prime / prime credit, while banks and credit unions do a bit more near-prime and sub-prime, but the bulk of near-prime and subprime is done by independent finance co’s. Auto lending is a highly fragmented market with the largest lender only accounting for 5-6% of total loans, the top 10 accounting for ~30%. The 20th largest lender has <75 bps of share.

In 2019, OL facilitated $1.7B in insured loans. We believe this can grow at a ~25% CAGR, reaching $6B in 2025 (continued growth with credit unions and regional banks (15% CAGR) and ramping up of OEM 1 and 2). At $6B of annual originations, this would be only 1% of the total market or ~3% of our estimate of the near-prime market.

Credit Unions: There are 5.2K credit unions in the US that hold $1.64T in assets, $1.1T in loans, and $380B in auto loans (35% of total loans) vs OL’s 300 active customers. The vast majority of credit unions offer auto loans (>9 out of every 10). The industry is quite fragmented, with the top 10, 50, 100 and 250 credit unions, accounting for 17%, 22%, 33% and 43% of assets, respectively. The 50th largest has $4.3B in assets, the 100th has $2.8B, and the 250th has $1.3B. There are 1.6K CU with assets >$100M (OL’s target market). OL has customers ranging from $25B in assets down to $130M in assets.

Regional Banks: Historically OL has focused on credit unions, but regional banks are increasingly another growth vector. The 100th largest bank in the US has $16B of assets and there is a very long tail of small, regional players that also engage in auto lending (5.3K banks in US vs 5.2K credit unions). OL has landed several sizeable regional bank customers ($3.8B Amarillo National Bank, $1.0B Beneficial State Bank) and continues to make progress.

Captives: there are 16 OEM captive finance companies, which the company estimates at a $1B revenue TAM ($30M to $100M revenue opportunity per captive). Even winning 1-2 more OEMs would be a significant lift in revenue.

The recent implementation of CECL could be another tailwind to encourage adoption of OL as using OL would enable lower reserve requirements.

Competition:

Based on our work thus far, we have not found any competitor who offers a similar product as Open Lending, and this is mirrored in the language in the OL prospectus. There is of course competition from other lenders competing in the near-prime space, but we believe the highly fragmented nature of the market, as discussed previously, should not prevent OL from growing considerably from its current base and earning attractive returns. The bifurcation between prime lenders and sub-prime lenders has existed for decades, and we expect this will continue to create an attractive opportunity for OL, which has been confirmed with our conversations with industry sources.

We believe OL is likely to remain insulated from competition for the following reasons.

·         OL creates significant value for its customers by enabling greater lending with appropriate risk parameters for a customer base that does not have the capability or risk appetite in-house, but OL is not perceived as expensive (the customer views it simply as an incremental loan that could not have been made before).

o   OL’s underwriting algo is strong – encompassing >2M different risk profiles (vs 210 different profiles back in 2008-09)

·         Switching costs: It takes 2-3 months to implement a solution like this, and OL’s customer base is conservative and slow moving and is unlikely to try and leap to a new unproven solution

o   OL has been at this for 17+ years and has built up trust and understanding with its credit union customer base

o   It took years to integrate into the 20+ LOS systems that are used today enabling OL to give a decision in 5 seconds

o   In addition, OL’s systems have been built to handle the significant regulatory and compliance burdens (TILA, ECOA, FCRA, FDCPA, GLBA, SCRA, ETA, Bank Secrecy Act)

o   Entrenched vertical market software businesses that are liked by customers with low churn like OL typically earn outstanding margins

Returns

The combination of ~25% CAGR in loans, slight margin expansion, free cash flow generation and OL eventually trading at 20-25x free cash flow should produce a mid to high teens return from today’s price.

Catalyst

Announcement of additional customers, particularly captive OEMs.

Announcement of a third insurer.