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Fintech Lending Strategies Have Been Able to Generate Robust Performance
Ron Barin, Global Head of Strategy
22 April 2024
Technology-enabled corporate receivables and consumer lending strategy market leaders, such as Fasanara, have a long history of generating strong, consistent investment performance for their investors. This long successful track record is reflective of having a distinct investment process, extensive operational scale and advanced credit risk management.
Tech-enabled lending strategies have also created favourable real economy impact by helping to channel capital more efficiently to underserved small and medium-sized enterprises (SMEs) and consumers, when compared to traditional commercial banks.
Lending strategies are designed to provide investors with stable, reliable, low-risk returns as an uncorrelated, diversified, short-duration alternative to more risky and volatile traditional asset classes. The resulting stable investment returns reflect the large, persistent credit spread on the capital deployed, coupled with an advanced credit risk management infrastructure that is in the DNA of the investment process, helping to minimise delinquencies and defaults, and maximise recovery rates.
In fact, some tech-enabled lending strategies, such as Fasanara’s, have produced an enviable investment return profile, generating only positive monthly (and annual) investment returns since inception.
Stable Positive Return Drivers
The drivers of stable, only positive monthly return generation across market cycles, for firms like Fasanara, are due to the following factors:
1. Sustainable underlying loan yields
2. Maximum originator & loan diversification
3. Advanced credit risk management tools
4. Enhanced credit protection
1. Sustainable Underlying Yields
Tech-enabled lending strategies fundamentally generate stable gross yields which have historically more than offset defaults, fraud and hedging costs.
a) Receivables: Sustainable SME loan funding premiums are generated from the purchase of short-term receivables from small suppliers of large, investment-grade corporate debtors through fintech origination lender platforms. Unlike a debtor’s long-duration senior bond, the yield on the receivables is not impacted by changes in interest rates given the fixed-rate nature of the receivable and its short duration. These receivables typically have a duration of less than 90 days which creates a portfolio that is naturally self-liquidating, minimising credit risk. A tech-enabled origination model, like the one Fasanara has developed, allows for the ability to continuously select the most attractive receivables by yield, counterparty, sector and country to maximise the funding premium and minimise default risk.
The mechanics of a typical corporate receivables factoring asset manager strategy are:
- Large opportunity set: Factor receivables of SMEs who are the small suppliers of larger companies via a proprietary Fintech originator lending platform
- Factoring a receivable means that the asset manager is buying the receivable of the SME where the SME (seller) has sold goods to a larger, typically investment grade company (debtor)
- SMEs (who are underserved by traditional lenders) sell their receivables to enhance their working capital position since they are typically in a negative cash flow position
- The asset manager is therefore only exposed to the credit risk of the larger corporate debtor in this transaction – the debtors are typically large investment grade companies (such as Ford Motor, Apple, Unilever, etc.) and this results in a very low historical default rate
b) Consumer Lending: The consumer lending credit spread has exhibited historical persistence at an average spread of 12.0% over the last 20+ years. This spread is driven by the high interest rate charged on consumer loans less the lower historical default rate. The current weighted average coupon (WAC) on consumer loan portfolios is high and has increased since mid-2022 as Marketplace Lenders (MPLs) have repriced their loan interest rates to align with the higher rate environment and have tightened their underwriting criteria, resulting in increased borrower FICO scores.
It is interesting to note that the interest rate on consumer loans has been persistently elevated with little correlation to changes in interest rates while the default rate is directly impacted by the economic cycle. In fact, the consumer lending credit spread remained positive even during the outsized stress of the Global Financial Crisis. A tech-driven origination model allows for the continuous selection of the most attractive shorter maturity (1 year), small notional ($1-5k) consumer loans to maximise the consumer lending spread and minimise default risk.
2. Maximum Originator & Loan Diversification
Typically, we see the leading tech-enabled lending strategies using a portfolio construction approach that is based on the principle of maximum diversification and the law of large numbers to help to cherry-pick the best originators and loans to naturally immunise the short duration portfolio from delinquency, default and fraud risk. This approach differs from a typical alternative private credit manager which employs a more concentrated portfolio, with longer duration, as it relates to originators, loan positions, sectors and geographical exposure. Leading tech-enabled lending strategies, like Fasanara’s, are highly diversified across the following dimensions:
- Originator Platform
- Originator Exposure Limits
- Loan Positions
- Loan Size / Short Duration
- Sector Exposure
- Country Exposure
- (Largely) Captive Originators
- Stable Institutional Investor Base
3. Advanced Technology & Credit Risk Management
Technology and credit risk management are at the core of leading tech-enabled lending strategies. . The disruptive machine-learning driven technology infrastructure that is employed allows for the handling of the complex task of identifying, assessing, processing and monitoring the millions of loans in the portfolio. At the same time, having a technology stack that provides the ability to perform deep originator due diligence and to successfully manage relationships with a deep line-up of originators is mission critical. Leading tech-enabled lending strategies, such as Fasanara’s, have built a large internal team of IT professionals to provide the operational scale necessary to develop the proprietary risk management infrastructure to support and evolve the technology stack and risk management.
This allows for the leveraging of algorithms to help cherry-pick the best originator platforms and loans to mitigate default and fraud risk and maximise recovery rates. AI and machine learning are powerful tools that help take advantage of the vast amount of data that is amassed from executing millions of loans since inception. These tools, coupled with human insight, allow for the effective analysis of vast amounts of data, recognise patterns, allow for a dynamic asset allocation process and assist in detecting credit risk and fraud with greater speed and precision.
a) Originator Due Diligence Process: Development of a rigorous cross-functional due diligence process, is crucial as it is needed to screen the Fintech originator universe and assist in selecting the originators that meet strict underwriting criteria. Further, continuous monitoring of the onboarded platforms is required to enable detection of potential performance deterioration and provide early risk warning signals.
b) Debtor Credit Rating: An important best practice, that is utilised by Fasanara, is to assign a proprietary credit rating to every debtor in the portfolio to calculate expected default probabilities. A proprietary machine learning based credit model should be constructed to calculate a Debtor Rating (AAA to C) integrating originator credit ratings, 3rd party debtor financial data and payment history for the debtor and the seller over the medium term. The credit model should also incorporate any debtor credit enhancements into the determination of the debtor rating.
c) Fraud Mitigation: One of the risks that lending strategies are exposed to is the risk of fraud as originator receivables may be fake or duplicates. A multi-pronged approach should be developed to mitigate fraud risk: (1) partner with high quality originators who have their own fraud check processes and (2) try to embed originator fraud buy-back provisions. In addition, having a vast number of positions in the portfolio naturally immunises the overall portfolio impact of any potential fraud risk. Lastly, machine learning and neural network portfolio monitoring systems can be used to flag suspicious invoices and potential fraud risk.
d) Stress Testing: Another risk management best practice is to perform ongoing stress testing relative to potential adverse scenarios. Default rates, recovery rates and loss rates should be continuously stress tested under crisis scenarios using a deep neural network stress model.
4. Credit Enhancements
Credit enhancements are an additional tool that leading tech-enabled fintech lending strategies use to manage credit risk to generate more stable, persistent returns. A number of credit enhancement techniques are utilised to add additional capital protection and increase the credit profile of the strategies to help add protection against the growing risk of a significant recession. These techniques include over-collateralisation, first-loss protection, credit insurance, government and corporate guarantees.
a) Over-collateralisation: The typical advance rate (which is similar to a mortgage loan-to-value ratio) for tech-enabled lending strategies relative to the value of the receivable or consumer loan borrower’s collateral ranges between 70-90%. This helps to mitigate the risk of uncertain or changing underlying collateral values and adds an additional layer of credit protection.
b) First-Loss Protection: First-loss protection is also typically used as an additional safeguard against potential losses in the event of default or insolvency. Tech-enabled lending strategies, such as Fasanara, may use credit insurance on a significant portion of the loans in their portfolio. We believe that a favourable tradeoff exists between the modest cost of first-loss protection and the amount of risk reduction and return enhancement that it provides. Some tech-enabled lending strategies have the ability to dial down the level of first-loss protection to increase the return on their mandate in separate accounts.
c) Credit Insurance: Credit insurance is also typically used as an additional safeguard against potential losses in the event of default or insolvency. Tech-enabled lending strategies, like Fasanara, may use credit insurance on a portion of the loans in their portfolio. For example, Fasanara partnered with Allianz Trade in September 2023 to underwrite credit risk insurance (up to $1bn in volumes) for receivables purchases by Fasanara’s strategies in the B2B ecommerce space.
Tech-enabled lending strategies would typically apply for insurance of a receivable (with Allianz or other insurance provider) if it deems it appropriate to do so. This primarily is a function of the size of the (debtor) exposure: typically, the threshold is EUR 1M exposure, but this does not mean all EUR 1M+ exposures are insured. Indeed, insurance may not be required in case the receivable already has a good credit package attached to it.
Conclusion
Tech-enabled receivables and consumer lending strategies have a long track record of generating strong, consistent performance. Lending strategies, like Fasanara’s, which have a distinct investment process have delivered stable, persistent, low risk returns with an enviable return profile, generating only positive monthly returns since inception. The drivers of a successful tech-enabled lending strategy, reflect the interplay between a number of factors: the robust, favourable return profile of the niche asset classes invested in, the increased opportunity set from the growth of the non-bank lending sector, extensive operational scale which provides the edge to leverage the Fintech ecosystem and proprietary, disruptive machine-learning technology and risk management tools (coupled with human insight) to support and efficiently manage the scope and complexity of the investment portfolio.
We believe that these tech-enabled lending strategies will play an increasingly crucial role in supporting SMEs and consumers and will continue to provide a favourable real economy impact. This trend is driven by the banks withdrawal from SME lending. which has created a funding gap estimated to be in the trillions and has been triggered by the banks not having built the technological infrastructure needed to properly manage SME loan portfolios and by the increased regulatory capital requirements faced by banks.