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Finding value in data-driven direct lending

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Private debt is increasingly popular but at a time of uncertainty, could this new asset class absorb the amount we want to allocate to it? Dr. Daniel Bartsch, Founding Partner & Managing Director, creditshelf Aktiengesellschaft, recognises these issues, and suggests 6 ways you could drive a data-driven strategy to maximise your opportunities.

Are you ever wondering if the time is right to increase your allocation to private debt? After all, the rapid growth of private debt investments has raised concerns about how much money can be absorbed by this new asset class. Overcrowding may lead to diminishing returns and/or less stringent standards on credit quality. And investors face uncertainties about the resilience of these investments as most of the managers have never gone through an entire economic cycle.

Maybe time has come to leave the beaten path of traditional private debt investing and start considering data-driven direct lending. Over the last years, a new breed of players has been using speed, data and technology to extend private credit to the most underserved market segment: small- and medium-sized enterprises (SME). Can this model mitigate some of the typical risks associated with private debt? And what are the characteristics of these loans?

Direct lending taking a different path

Following the early advent of „peer-to-peer“ platforms pursuing retail money, the industry has gradually shifted towards institutional funding. Today, mature direct lending platforms such as Lending Club, Ratesetter or Zopa are predominantly backed by institutional investors. Despite the increasing resemblance with respect to funding, there are still some notable differences which are important to highlight towards investors looking to allocate capital in this space.

1. Use of technology to support data-driven decisions:

Classical private debt funds largely rely on offline deal sourcing and purely manual credit analysis. In comparison, platform lenders rely on technology both for loan origination as well as for supporting the credit process throughout the entire credit value chain. At creditshelf, we have built tools allowing us to analyse the accounting data of our clients at single book entry level. We also use software to cross-reference such accounting data with actual cash flows in bank accounts. Nevertheless, our final credit decisions are always made by experienced individuals, who are supported by data-driven analytics and dashboard outputs. As we accumulate and analyse more data, we can make better and much faster credit decision.

2. Granularity and portfolio diversification:

In Germany alone there are currently around 40 active debt funds, none of which is targeting individual ticket sizes below EUR 5m. On the other hand, platform lenders are typically offering loans starting even below EUR 100k. Depending on the platform, investors may invest evenly across the entire origination pipeline, leading to unparalleled portfolio diversification.

3. Target segment:

The reason why traditional managers have a preference for larger borrowers (typically over EUR 10m EBITDA) is the constraint of covering the rather costly and cumbersome work of sourcing, analysing and structuring each deal. Enabled by efficiency gains from technology and semi-automated credit processes, platform lenders can afford to target SMEs. This unique advantage should offer some kind of protection against the impact of overcrowding.

4. Transparency:

Platform lenders have a data DNA. This means they are able to provide a vast pool of data to their prospective investors, including a real-time view of the loan-book and performance and loss metrics. Some platforms offer this data publicly, others use NDAs and subsequently grant access to investors, allowing a deep dive into the numbers at level of the individual loan/borrower.

5. Sourcing bias:

Most traditional funds heavily rely on their network within the private equity/investment banking industry to generate sufficient deal-flow. Their loans are often originated in a transactional context, such as M&A or management buyouts. This leads to a certain dependency on the overall health of private equity. On the opposite, platform lenders typically build their own non-sponsored deal-flow across a number of distinct distribution channels.

6. Risk/return profile:

Private debt managers and platform lenders both target sub-investment grade corporate borrowers, i.e. ratings in the BB/B space where banks usually lend on a fully secured basis operating with very conservative loan-to-value or debt/EBITDA metrics. Although direct lending offers more flexibility to borrowers, this comes at a significant mark-up over existing bank debt. Traditional private debt funds frequently use longer-duration bullet loan structures, whereas platform lenders usually rely on shorter duration, self-liquidating amortising loans. This significantly reduces the risk from sudden changes in the interest rate regime.

Not so far apart

At the essence both models aim at delivering superior risk-adjusted returns compared to debt investments available in public markets. Yet, the cost-effective loan origination of direct lending platforms allows investors to access certain segments of the credit market that would otherwise be non-investable. At creditshelf, we strongly believe that investors are rewarded handsomely by investing in a well-diversified portfolio of SME loans and at the same time may avoid many of the distinctive risks associated with traditional private debt.

When looking for a suitable manager in direct lending, a good place to start is on evaluating the credentials of the investment professionals. Experience matters and most successful platform lenders are run by senior finance executives. These individuals frequently have an investment banking or asset management background and are employing teams of experienced credit professionals. Moreover, investors should get a clear signal that the manager is eager to constantly improve its proprietary credit model and is reacting to changes in the economic environment.

Regardless of whether the manager is pursuing a traditional or a platform model, they need to convince institutional investors to put their money at work without sacrificing on prudent financing standards. Only a thorough understanding of each borrower’s credit profile as well as stringent credit management processes will achieve sustainable returns to investors in the long run.

About the author: Dr. Daniel Bartsch

Daniel has 15 years of international consulting and banking experience. At creditshelf Daniel is responsible for operational business and relationships with customers and business partners. Previously, he held a senior executive position at UBS, managing the institutional distribution of bond and equity products. Professional assignments took him to Zurich and Singapore. Daniel graduated with a degree in business administration from the University of Mannheim and a doctorate from the University of Düsseldorf.

Disclaimer: The publisher of this white paper is creditshelf Aktiengesellschaft, Mainzer Landstraße 33a, 60329 Frankfurt a.M. This promotional material is subject exclusively to German law. It is intended for educational purposes only and in no way constitutes a solicitation to buy or sell any investment. It does not take into account the particular investment objectives, financial situation or special requirements of the recipient and does not replace proper financial advice based on timely information. We recommend you consulting investment, tax and legal advice before a possible investment. Opinions, estimates and projections constitute the current judgment of the author as of the date of this report. They do not necessarily reflect the opinions of creditshelf Aktiengesellschaft and are subject to change without notice.

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