Page 23 - MTIA Summer 2022 Market Brief

Tech in the Balance
Challenges Streamlining
Data
First, loans present a high degree
of customization. While trade
organizations such as the Loan
Syndications & Trading Association
(LSTA) and the Loan Market
Association (LMA) help provide a
level of preferred standards and best
practices, no governing regulation
forces the adoption of such
standardization.
Second, and perhaps more critical,
communication and processes
rather than the data itself can create
steeper challenges to overcome.
Technology is foundational, but
people who are experts with
syndicated loans are essential to the
smooth, uninterrupted operation of
loan markets.
New transaction structures and increasing complexity have increased investor
demand for data and reports. Higher scrutiny from regulators is also playing a part
in these changing needs among loan market participants.
Many of these changes stem from the different requirements of investment
funds, CLO managers, underwriters, middle-office providers, custodians, and
trustees. Together, the forces that have brought data and reporting to the top of
the agenda in the loan markets raise the bar for the collection, trustworthiness,
and packaging of underlying loan data.
They also impact the providers of such data— namely, loan agents who provide
core loan processing data and loan market data providers of broader credit data.
Therefore, it is essential to look at the question of data and reporting from the
perspective of the loan markets overall, as well as specific users.
The Future of Data and Services
Many in the industry look forward to a future where loan data is centralized and
accessible in one platform (e.g., on the blockchain) to help address the data
aspects of these challenges. However, it is important to be realistic about the
constraining factors.
Future technological promises aside, paper, document images, email, and fax
still plague today’s loan markets. While all market participants would likely prefer
more efficient information exchange, today’s reality imposes a high degree of
manual processing. No technology solution by itself would change the need for
information exchange, follow-up on the part of the agent, and efforts to resolve
discrepancies within the dataset.
The Example of CLO Data Needs
CLOs are a case in point. The evolution in structures and documents from early
vintage 1.0 CLOs to today’s 3.0 CLOs imposes more risk testing requirements.
The requirements depend on specific data tracking from industries, spreads, and
countries to a much broader set of information, such as credit stats, EBITDA,
and cash flow for investors to digest—typically delivered via trustee/custodian
reporting supported by underlying manager data.
Moreover, regulators increasingly require CLOs to increase their level of
transparency with specified data fields and standard reporting templates
related to transaction documentation and more robust risk characteristics (see
”CLOs in the Spotlight” above). ESG has also become more
topical as investors are focusing more on allocating capital to investment
strategies that support socially responsible companies / industries.
Combining loan data from multiple loan agents in addition to various credit and
post-closing data sources is challenging. As a result, CLO managers and asset
managers participating in loans must reassess their operational infrastructure
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