Both beneficial owners and agent lenders have been expanding data inputs, seeking a deeper and wider set of data points and newer, enriched datasets. We speak with J.P. Morgan and S&P Global Market Intelligence about the pace of data and tech adoption.
There is an increasing demand in using short interest data as a factor in making trading decisions, and short interest factors help asset managers and owners in stock selection and investment insight. Fundamental and quant fund managers use these data points to refine entry and exit points to identify potential turning points and contrarian ideas, explained Kabin George, head of Securities Finance Product Management at S&P Global Market Intelligence.
S&P Global recently acquired IHS Markit, whose Securities Finance product holds some 20 years of historical securities lending data that it provides to its customers such as beneficial owners, agent lenders, brokers and hedge funds.
The search for more and better data goes past the traditional focus on benchmarking and identifying revenue opportunities, said George. For example, interest in data related to the credit assessment of counterparts helps securities lending participants determine exposure by credit ratings of counterpart and optimize the management of their capital and risk weighted assets (RWA). According to S&P Global research, some $60 million of excess RWA could have been eliminated owing to borrows from suboptimal credit ratings when scrutinizing a sample of cost-of-capital-sensitive instruments.
Other examples include intraday rates for real-time data to find rerating opportunities and for price discovery, as well as a surge in interest in understanding repo data, particularly on the cash reinvestment side, with demand for information by tenor, haircuts, collateral and currencies, he added.
“Especially in the past two to three years, we see a surge on adding new data elements on to their lending program, and it’s not just to see how to improve their revenue, which is very important, but also to add other complementary datasets to ensure that the program is run efficiently and effectively,” he said.
ESG data points are also having a surge of interest, and there is a need for analytical solutions and self-service tools to help lenders make well informed decision on lending to optimize their returns while maintaining effective stewardship around their own ESG guidelines or mandates, said Chelvi Paramanathan, global head of Pricing and Analytics for Agency Securities Finance and Collateral Services at J.P. Morgan.
But there also needs to be some standardization and convergence on the ESG data matrices available in the market to comfortably integrate ESG data fully into the core lending platform, she added.
Paramanathan has over two decades of experience in the financial industry working at numerous banks such as Lehman, UBS, Barclays, and Citigroup, with a variety of roles that crosses quantitative research and trading as well as technology in Prime Brokerage and Fixed Income Derivative businesses. She’s also done a stint in fintech senior management role driving product innovation for buy-side and sell-side clients in the price discovery and optimization space.
Prior to the financial industry, she built mission critical systems using artificial intelligence techniques in a scientific research capacity. At J.P. Morgan, her responsibilities include Client Portfolio Evaluation and Pricing, driving innovative tools development and financial resource optimization initiatives for Agency Securities Finance and Collateral Services Businesses.
J.P. Morgan is well ahead in preparing the standard platform in terms of digitization, collateral mobility, flexibility and scalability to adopt to ESG-related changes and also performance measurement tools to simulate the impact on revenue performance due to client driven ESG related changes.
While platform integration is straightforward, challenges remain around the quality and source of ESG data in terms of coverage, accuracy, transparency and reliability, and she noted that ESG disclosure guidelines should be designed in collaboration with companies, investors and regulators to improve standardization, which will also boost vendor transparency on how ratings and scores are derived.
“We need to get to a point where it is regulated and standardized so that we can comfortably choose the vendors that are relevant to the problem we are solving, and be able to use those ESG matrices (and) scores together with internal proprietary (and) alternative data in our decision-making process,” she said.
Chelvi and Kabin will be joining colleagues from UC Regents Investment Office, BNY Mellon, Citi, EquiLend and Northern Trust at our annual Finadium Investors in Securities Lending conference.
Ahead of the event, you can preview some of the topics being covered: