Banks and asset managers lending in parallel could offer investors an interesting credit solution.
By Gianluca Oricchio, CEO of Muzinich & Co. SGR and Global Head of Artificial Intelligence Solutions
Over the last 15 years, banks have focused on deleveraging while asset managers step in to fill the lending gap. More recently, we have seen the emergence of «parallel lending» where asset managers lend to companies alongside banks.
Under Basel Regulations, banks can optimize their Net Return/risk-weighted asset ratios by sharing plain vanilla term loans with asset managers who lend under the same loan agreement.
Potential Win-Win Scenario
This approach may benefit both parties. The bank can reduce risk and counterparty exposure while providing the asset manager access to its distribution network and a large number of sourced transactions.
The asset manager may then cherry-pick to build well-diversified portfolios while utilizing a bank’s revolving credit facilities/short-term financial support in the event of temporary stress. Globally, the potential market is around $96.2 trillion1, while in Europe it is around $4.9 trillion.
Illustrative First Lien Loan in the Company Capital Structure
(Source: Goldman Sachs Asset Management Private Credit, Senior Direct Lending Platform, April 2022, (pg. 11). For illustrative purposes only.)
A parallel lending investment strategy primarily invests in first lien/club loans and senior secured assets which may be the safest/most senior and often secured assets. A well-diversified and granular portfolio (minimum c. 100 loans) may protect capital while maximizing yield by capitalizing on the minimization of black swan events through diversification, and on the premise that joint default probabilities are lower than the default probability of a single holding.
Given this focus on risk reduction, a portfolio can potentially be rated investment grade, enabling banks to provide long-term leverage to the portfolio at very competitive interest rates. However, an asset manager must be fully independent of a bank yet have direct access to any company under consideration for lending to carry out the due diligence process and must have the same quantitative tools as European banks (i.e., Basel III Advanced Internal Credit Rating Models).
Use of Artificial Intelligence
We advocate an investment process with three pillars to include qualitative/fundamental analysis, Basel III Advanced Internal Credit Rating Models (and risk-adjusted pricing tools) and new artificial intelligence (AI)/deep learning critical decision support systems (or advanced risk tools).
AI should be used to enhance decision-making through augmented data analysis of enormous sample size, and not, in its own right, as an algorithmic or «black box» credit selector. The multi-layer neural network is a powerful tool for data analysis where AI combines with human analysis to increase the accuracy and quality of output and can increase the ability to separate bad companies from good during a due diligence process.
Ongoing Bank Deleveraging
However, the final investment decision remains human-based. Looking ahead, we expect to see an increase in credit funds based on parallel lending because they may offer attractive returns, low volatility (they do not have a daily mark to market) and low interest rate risk because most of the loans are floating rate.
This is against a backdrop of ongoing bank deleveraging where there is an abundant supply of loans – especially in the underserved lower middle-market – capital protection for banks and innovative credit analysis where there is a vast, under-mined universe of credit data on small and medium-sized enterprises.
In an environment dominated by recession and inflation, we believe a well-diversified portfolio of floating rate senior credit has broad appeal.
1Financial Stability Board report. Non-Bank Financial Intermediation Report, December 2021.
2ECB: Statistical Data Warehouse, as of January 2022.
Gianluca Oricchio is CEO of Muzinich & Co. SGR and Global Head of Artificial Intelligence and Robotics. Prior to joining Muzinich, Gianluca has been Managing Director in several European Banking Groups and has developed SME Credit Rating Models and Early Warning Systems. He has been an advisor of Moody’s Analytics. Gianluca is a Ph.D. in International Accounting and a Full Professor of Corporate Finance and Accounting. He graduated from La Sapienza University.
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