With the private credit market growing at pace – it’s projected to be worth $3.5 trillion by 2028 – managers are looking for new ways to create marginal gains across their offering. One way is by optimising their operations to collect, assimilate and leverage their funds’ loan data effectively. Kevin Hogan and Todd Werner explore how integrating teams, technology and data creates the ecosystem to provide that competitive edge.
In the rapidly evolving world of finance, private credit has become a vital component of capital markets. As companies continue to turn to private credit to meet their financing needs, the role of data in portfolio management has become critical. Accurate, timely, and comprehensive data is essential for assessing risk, valuing assets, servicing investors, and making investment decisions. A data ecosystem, integrated with the right team and technology solution, can sharpen a competitive edge where margins are thin, and investor demands are high.
The popularity of private credit as an asset class surged dramatically following the global financial crisis of 2008/09, reaching an estimated $1.5 trillion by the end of 2023, according to Preqin. This growth has been fuelled by ongoing shifts in public markets, investor appetite for higher but reliable yields and portfolio diversification, and borrowers’ preferences for more flexible financing options. According to BlackRock’s 2023 report, Private debt: a primer – unpacking the growth drivers, the private credit market could be worth $3.5 trillion by 2028.
Private credit encompasses lending activities between borrowers and non-bank lenders. Types of private credit include direct senior lending, junior capital (such as mezzanine, second lien debt, and preferred equity), distressed debt, and specialty financing.
This asset class can offer higher returns and greater protections for investors compared to public market debt. This is due to the lenders’ ability to negotiate loan terms, exert pricing power, and enforce covenants to monitor and restrict borrower activities. Covenants provide transparency and enable early detection of potential financial issues of the borrower, safeguarding lender interests. In the public markets, an investor must rely on the evaluation by the underwriters at the financial institution that underwrote the loan to assess the financial health of the borrower and are relatively inflexible on covenants.
Investors in private credit range from limited partnerships and registered alternative funds (business development companies, interval funds, tender offer funds) to separately managed accounts, insurance companies, and private wealth managers, all of which necessitates tailored product structuring and reporting.
For fund managers to thrive in this complex and competitive arena, they must have in place infrastructure that supports a seamless integration of people, technology, and a data ecosystem.
A data ecosystem refers to the network of users, processes, data sources, and tools used to assimilate and manage data. Key to building a fit-for-purpose data ecosystem is instilling a culture of data as an asset, creating a data governance framework, maintaining data quality, integrating data effectively, and investing in a scalable technology infrastructure.
A robust data ecosystem, once created, can more easily fulfil the requirements for borrowers, lenders, and investors across structures and strategies. It helps ensure all regulatory requirements are satisfied and makes the delivery of real-time reports possible. For example, in the EU private credit fund managers are subject to several regulatory frameworks that require detailed reporting including the Capital Requirements Directive IV (CRD IV) that mandates detailed data reporting requirements for banks and investment firms. These annual reports include disclosures on capital adequacy, risk exposure, and governance structures. In addition, managers must report on risk and investment strategies under AIFMD, sustainability risks in decision-making under the Sustainable Finance Disclosure Regulation (SFDR), and on accounting standards in the EU under EFRAG the European Financial Reporting Advisory Group (EFRAG).
Creating a process that allows stakeholders to access, review and amend data on a more timely basis streamlines the creation of these reports and so expedites the filings. Another example is that of large brokers who, as a requirement to be listed on their brokerage sites, require daily NAVs. To support daily NAVs, firms must have access to high-quality data and a technology solution that supports daily processing and includes comprehensive reporting capabilities.
A well-designed data strategy has many benefits, including improved operational efficiency and elevating the investor experience. When developing a strategy, it is essential to address the distinct needs of all internal stakeholders, including front-, middle-, and back-office teams as well as investors.
Front office personnel require up to date information on the financial health of the borrowers so that loans can be restructured to avoid defaults. Minimising default rates – the percentage of loans borrowers fail to repay – is a source of alpha for private credit funds. Firms that limit defaults can stay ahead of the competition.
Middle- and back-office teams need detailed, real-time information to effectively monitor the financial health of the borrowers, and to support the settlement, tracking, valuation, and reporting processes associated with various investment products. Investor services personnel, meanwhile, need data to efficiently onboard new investors, support investor queries, and ensure compliance with regulatory obligations (AML, KYC, FATCA and CRS). Investors too need access to data reports through easy-to-access investor portals.
Disparate data sources, varied and often incompatible technology solutions, and data integrity are all challenges to an effective data ecosystem. These must all be navigated effectively to build a cohesive, superior data model that optimises processing, supports high transaction volumes, captures granular data efficiently, and provides transparency through flexible reporting capabilities.
A key component of a robust data strategy for the private credit market includes establishing a reliable process for collecting and reporting data on loans.
Other functionality that should be considered includes deal-flow monitoring, a dedicated data capture process, and cashflow projections.
To deliver significant operational efficiencies, the loan solution should integrate with the general ledger to streamline entries, which significantly reduces errors relating to the management of multiple applications.
Aztec’s Loan Servicing Unit combines the specific loan expertise of our people with the specialised experience of our eFront Debt loan processing system, to provide specialist, end-to-end support for your private credit fund. The team are loan and system experts and are agnostic to NAV cycles, resulting in speedier and more efficient processing and the ability to provide position reporting in real-time to clients. They focus predominantly on updating the Investment Book of Record (IBOR) integrating seamlessly and immediately to the eFront General Ledger thereby creating the Accounting Book of Record (ABOR).
We’ve invested heavily in our private credit offering, turning it into a product that differentiates it in the private credit market. For more information on how we can support your private credit offering, please reach out to Todd or Kevin directly.
06 November 2024 Kevin Hogan
26 September 2024 Simon Ware
To discover for yourself what makes us the bright alternative and how we can support, please contact Kevin Hogan, our Head of Fund Services Ireland and Group Head of Private Credit.
