Matthew Chessum, director of securities finance at S&P Global Market Intelligence, reflects on the importance of complete and accurate inventory, transaction and static data in enabling consistent performance measurement across securities lending markets
Data is a very powerful tool. It exists almost everywhere and has provided the basis of some of humankind’s most impressive inventions. Financial markets have been built upon data, whether that be in terms of pricing, liquidity, risk management or a combination of all three. As technology has improved, the quantity and quality of the data available has also grown and improved. Within the securities lending markets, this evolution in the complexity and availability of data points has been facilitated and controlled by the introduction of the International Securities Lending Association’s (ISLA’s) Securities Lending Performance Measurement (SLPM) guidelines.
The SLPM provides the foundation for market participants to achieve high quality, complete and consistent data comparisons across the securities lending landscape. There are three primary areas of data management that are included in this guidance: inventory data, transaction data and static data. Each of these focuses on producing data standards to remove common inconsistencies that often lead to confusion or misrepresentation of data sets, making comparisons less accurate or, in some cases, completely ineffectual.
Inventory data
The definition of inventory is often unique to every market participant. A portfolio manager may include all of their assets under the title of inventory, whereas a securities lender may class their inventory as lendable assets in lendable markets only. Without firm agreement on what the term refers to, performance and risk metrics are often confused and inconsistent between entities.
Transaction data
The completeness of transaction data provided to all data providers remains key to ensuring successful and accurate comparisons and programme oversight. Consistent delivery of all client transaction level data is essential to provide the most comprehensive view of market activity.
Static data
Application of different standards for correcting data errors and identifying data omissions often contributes to a lack of consistency. Clear identification of client types, to ensure consistent peer group comparisons, is imperative in delivering accurate and useful performance measurement guidelines.
At S&P Global Market Intelligence, the application and provision of accurate and timely data across the financing markets remains a cornerstone of our product offering. Following the introduction of the SLPM guidelines in 2021, the goals and requirements of the initiative were fully embedded into our products and services.
As a market-led initiative, we believe it is essential to follow the technical guidance on offer through the SLPM to ensure that the data on offer remains fully aligned with industry standards.
To ensure adherence to the guidelines, the following changes were made to the way that data is collated and processed.
1. Benchmarking is based on total assets and lendable (after any restrictions)
The ingestion of trades and inventory files has been updated to comply with the best practice guide published by ISLA in September 2020. Contributors can now provide both total assets and lendable assets in their daily files. A new preference filter, Lendable Type, has been added to the web portal to analyse performance on a total or lendable asset (excluding restrictions and buffers) basis.
2. Revenue adjustments
Having the ability to include deferred revenue adjustments in performance measurement tools is critical to ensure that data remains accurate and useful. Up to five years of adjusted securities lending revenues can now be added at the entity or security level to facilitate accurate performance analysis. Adjustments can be made for a specific date or month (or value), which are then reflected in the performance measurement reports.
3. Revenue splits
As a new feature, lenders and beneficial owners now have the ability to add their revenue splits to their profiles. Users therefore have the ability to see their gross as well as net revenues and any returns after fee splits.
4. Return on net asset value and assets under management
Lenders and beneficial owners have the ability to input their net asset value (NAV) or their assets under management (AUM) to calculate their returns based upon either metric.
5. Right of substitution
The ingestion of a right of substitution data flag is now possible. Having this ability provides more granular detail to market participants and helps to build a more accurate picture of the financing landscape.
6. Pay to hold
While this is not a data point that is subscribed in the SLPM guidelines, a pay-to-hold option has been added and can now be ingested across data sets. This forms part of continuing efforts to improve the granularity of data provided. This remains an important feature in building a true picture of the securities finance market and it differentiates actual stock loan trades from inventory that has not yet been deployed.
Being able to assess the relative performance of a securities lending programme relies upon the quality and accuracy of the information being used. By ensuring that the guidelines provided by the SLPM best practice documentation are adhered to, all market participants can ensure that comparisons, predictions and appraisal of their activities remain both accurate and useful.
As the availability of data supply grows — and the applications of that data become increasingly important — industry standards created by a broad range of market participants are critical in providing meaningful data points that can translate into effective and valuable insights and signals. Following the recent explosion in the interest in artificial intelligence, never before has the quality and granularity of data been so critical to future innovation and positive, meaningful outcomes.
