In the securities lending sector, the assessment of performance has become an essential element of market operations. Despite its daunting nature, performance measurement has transitioned from manual calculations to digital data aggregation, providing valuable insights for market participants to make informed decisions.
Key industry players, such as S&P Global Market Intelligence and DataLend, offer vital tools for market participants to improve their lending activities, pricing strategies, and risk management. These companies have enhanced transparency within the securities lending market, empowering beneficial owners to take a proactive approach in managing their securities lending activity.
Data lies at the core of performance measurement in securities lending, encompassing critical aspects such as revenue generation, risk-adjusted returns, borrower demand, and market dynamics. Comparing programs with those of peers enables market participants to optimize returns within a well-understood risk framework.
The introduction of Securities Lending Performance Measurement (SLPM) guidelines by the International Securities Lending Association (ISLA) represents a significant step towards standardizing data presentation, ensuring consistency, and enabling beneficial owners to make more informed decisions about their lending strategy. These guidelines cover inventory data, transaction data, and static data, setting an essential industry standard that drives transparency and performance improvement.
The evolution of performance measurement in securities lending has increased the demand for detailed and standardized reporting, allowing clients to take a more hands-on approach with their investment teams. This evolution has also led to a more tailored approach to data usage, enabling owners to individualize their data needs and monitor their lending programs more effectively.
As data usage has grown, securities lending markets have become more sophisticated, with the ability to manage risk in real-time and leverage automation for streamlined processes and faster decision-making. Both S&P Global Market Intelligence and DataLend offer programmatic tools to provide a near real-time view into lending program performance, ultimately unlocking liquidity within the market and improving the allocation of financial resources throughout the lending chain.
Looking ahead, the incorporation of artificial intelligence (AI) is on the horizon, with the potential to further transform the landscape of performance measurement programs in securities lending. While the implementation of AI is already underway in some areas, there is growing potential to harness AI’s capabilities for more advanced and sophisticated performance measurement.
In conclusion, performance measurement through data analysis is crucial for beneficial owners and market participants in securities lending. The ongoing evolution of data usage, automation, and the potential integration of AI underscore the ever-growing significance of data in shaping the future of securities lending.