Data is Disrupting Private Credit, Driving the Asset Class Digital

Over the past few years, institutional investors have increased their allocations to private credit lending. A desire for higher returns in a period of low-interest rates is the key driver. According to PitchBook, a research and technology firm focusing on private capital markets, a record high of $191.2 billion flowed into this asset class in 2021. Another market data provider, Prequin, reports that this market has seen consistent and robust growth, averaging 13.5% annually in recent years. Preqin forecasts that private credit will accelerate to a compound annual growth rate of 17.4% between 2022 and 2026, propelling it to become the second-largest private capital asset class in 2023.

Even as interest rates rise, this trend is set to continue. Unlike investing in the fixed-rate public bond markets, private credit allows investors to gain access to variable-rate, low correlation, low volatility and shorter-duration investments. This attribution mitigates a portfolio’s overall risk profile.

The massive fiscal and monetary stimulus injected into the system over the past few years means private credit investors have the capital to lend. Finding the right borrowers can be a time-consuming, manual and error-prone process. It is highly competitive and requires extensive contacts and costly research. After all that effort, institutions still risk failing their investment parameters, remit and due diligence requirements.

The pandemic as a catalyst

When in-person networking, conferences, on-site visits, deal-making and due diligence went virtual two years ago, it was hard to conceive how deals could move forward. It quickly became clear that replacing travel and meetings with virtual deal sourcing accelerated closings. This shift allows lenders and borrowers to execute transactions from anywhere, at any time. Digital marketplaces stepped up to empower investors to quickly source deals online, further accelerating a standard and scalable approach to due diligence, pricing, structuring and executing transactions. With all this efficiency and newfound time, the number of deals began to rise.

While public investment pricing and research have long been accessible online, the $100 trillion private credit space has always been opaque. However, data-driven platforms and artificial intelligence are closing the information and efficiency gap between public and private investing. With new online marketplaces, transactions are getting sourced, put through due diligence, structured and closed quicker and more efficiently than before.

How data connects lenders and borrowers

What we’ve seen is a rapid and momentous shift from a human-centric business to a data-driven digital business that seamlessly matches lenders and borrowers. Marketplaces can connect lenders with borrowers by relying on data and algorithms to find appropriate deals. Investors can set extensive parameters such as investment focus, desired yield and duration. Borrowers input their desired cost of capital and critical financial data for lenders to review. With all this data in one place, lenders and borrowers can understand each other’s motivations faster and forge more meaningful partnerships based on shared goals.

In the world of data, we can break it down into three types: referential, also known as static data that doesn’t change often; transactional, which is data that moves quickly and evolves over time; and state machines, which gives data depth by presenting it as a lifecycle. These states can be used to build workflows that are easy to interpret and drive universal agreement of process. As a result, data-enabled platforms can remove inefficiencies and standardize deal processes. Although basic and obvious in appearance, these marketplaces have recently looked to identify patterns in deals and drive market efficiencies.

With new algorithms, we can centralize the process of private lending, making it look more like investing in equities. Today, asset managers can process all information in minutes or even seconds and complete transactions in a fraction of the time it once took.

Algorithms are transforming how we extract data. Instead of making borrowers log on and fill out forms, we can identify and process data from structured, semi-structured and unstructured documents—PDFs, Excel spreadsheets, videos—places where valuable data has traditionally been lost in a sea of information. Not only does this simplify the process, but it also provides further automated validation by moving from a few dozen data points to thousands or even millions just by uploading a few documents. This also challenges the decades of “data rooms” that have entrenched large portions of the alternative investment space. Delivering documents to people in a legacy file system brings no value. Taking that data and proactively delivering insights in a uniform and repeatable manner saves days, weeks and, sometimes, months of time.

In the private credit market, new technology is also effectively freeing up borrowers who previously had to devote countless hours seeking to find and share information with investors. These technologies enable them to spend their time doing the infinitely more valuable work of running their businesses. Ultimately, new technologies facilitate better data management without forcing companies to add new employees. That’s where all businesses want to be—adding revenue without headcount. As investor appetite for private credit grows and digital solutions mature, we can expect to see greater transparency, speed and deal flow.

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This was originally published by our founder on CXO Tech Magazine. Full article can be found here.