SFTR: Opportunities and Challenges

The Securities Finance Transaction Regulation (SFTR) forms part of the EU’s response to the policy proposals issued by the Financial Stability Board (FSB) in August 2013. It aims to reduce risks by improving transparency in securities financing markets and seeks to impose a series of conditions and rules. Counterparties will be required to report details on trades and collateral to a registered trade repository (TR).

The European Securities and Markets Authority (ESMA) issued its final report on the technical standards for SFTR on March 31, 2017.  The report details a total of 153 reportable fields covering securities lending, repo, buy/sell-back and margin lending. ESMA has identified 96 fields that will be required to match (with limited tolerance) but has chosen a “phased” approach for the implementation of this matching process; 62 fields will be required to match at the beginning of the process, with a further 34 required to match beginning 33 months later. All data must be reported in a standard ISO 20022 format to a TR, with trade information required on T+1 and reporting of the associated collateral on S+1.

The reporting requirement is dual-sided and requires the provision of a unique transaction identifier (UTI) for each trade and a legal entity identifier (LEI) for each of the counterparts in the trade.  Market participants also will be required to report a comprehensive series of trade details throughout the lifecycle of the trade, including changes to market price and loan value as well as corporate actions out-turns.

The regulation requires counterparties to submit reports detailing counterparty data and full loan and collateral activity. It also mandates the reporting of margin information for transactions novated to a CCP and a daily report on collateral reuse.

The main challenge for market participants will revolve around the volume, content and timing of the reporting requirements as well as the stringency of the matching requirements. The current standard of data submission across the market will not be sufficient to meet the requirements of SFTR. EquiLend has focused on engaging with market participants to determine the market’s ability and appetite to contribute the required data in a timely and reliable manner.

The foundation of a robust solution for SFTR is a clearly defined UTI generation process; experiences with previous reporting regimes have highlighted the chaos that can ensue when this is not achieved. EquiLend has devoted resources and drawn on its experiences over the past 16 years as market leaders in the securities finance industry to ensure this process is not repeated. The UTI will be vital, not only for trade booking and allocation but also for reporting of collateral and lifecycle events.

While the responsibility to report is on the beneficial owner, the burden of information provision likely rests with agent lenders, who will need to provide transparency as to the identity of their underlying clients (utilizing ISO 17442 LEI), either at or shortly after “point of trade.” EquiLend will leverage its unique positon to assist market participants in this process, utilizing existing pipes and functionality within NGT to accept the break-out and allocation of “block” trades to a principal level.

Additionally, EquiLend will employ existing connectivity to lenders and tri-party agents to facilitate the provision of appropriately granular data for collateral allocations on an S+1 basis.

Beneficial owners will need to reconcile themselves to the fact that their identities and activities will be more transparent than ever before. Again, utilizing existing functionality, EquiLend will seek to assist those concerned by maintaining a mapping set, which will allow us to anonymize the data when providing it to trading desks while maintaining visibility for credit and operations purposes.

Many brokers see the increased visibility afforded by SFTR as an opportunity to introduce changes to the trading model. EquiLend is in conversations with a broad range of market participants to ensure features in NGT are able to support this differentiated trading model, which factors in risk-weighted asset calculations into trading decisions.

By collaborating with Trax, and focusing on each entity’s strengths, EquiLend and Trax can offer a modular SFTR solution: We will offer assistance to our clients with as much or as little of the SFTR process as they require. Clients that have existing regulatory reporting engines may opt to receive matched transaction data and handle the rest of the process themselves. Others may need EquiLend to match and enrich the transaction data and transmit it to a TR for them. Still others may need a combination of the two approaches.

While the implementation of SFTR will certainly be onerous for the lending community, the data that it will unlock will bring significant returns to all market participants. The market will benefit from a granular data set, available in a timelier manner, which will enable participants to more efficiently manage their portfolios and collateral. DataLend will provide clients with the tools to perform more intelligent revenue attribution analysis, point-of-trade pricing, ongoing rate monitoring and capital-cost analysis.

At the core of SFTR is attribution and data standardization; from a performance and pricing perspective, the data unlocked by SFTR will allow for more detailed revenue-attribution analysis. Agent lenders and beneficial owners will be able to dissect their portfolios to identify returns generated from term loans, different non-cash collateral types, varying margin levels or a combination of all three. This analysis will empower beneficial owners to make even more informed decisions around their program parameters and will provide agent lenders with the data they need to support their recommendations to their clients.

As regulators and the market move toward greater transparency, the need to demonstrate best execution has followed. The difficulty in proving best execution has been that the loan rate or fee is not solely driven by the intrinsic value of the security. Instead, collateral type, term, margin, counterparty and underlying client type are also considerations when pricing a loan. At DataLend, clients use DataLend’s Market Variance Research Report to mark trades to the industry. However, the industry averages include trades with varying parameters. In the future, DataLend will provide collateral- and term-based pricing, providing greater transparency to the end-user.

Finally, efficient capital management has become more important than ever for both lenders and borrowers. The enhanced analytics DataLend will create on the back of the SFTR transparency mandate will help facilitate the capital management process as market participants determine the most economical and efficient allocation of balances and resources.

EquiLend looks forward to providing a robust SFTR solution, complemented by enhanced DataLend analytics, designed to empower market participants to make more informed decisions around risk, trade and resource allocation.