Four Takeaways From the 2019 Finadium Investors in Securities Lending Conference

BBH was pleased to sponsor the Finadium Investors Securities Lending conference on May 2- 3 in New York City, and represented the industry on several panels.  The forum was well attended by Asset Managers, Beneficial Owners, Agent Lenders, Prime Brokers, Hedge Funds, as well as a variety of industry vendors, and provided comprehensive insights on the market trends influencing our industry. 

Our key takeaways from the conference were:

Challenging Demand Environment

As markets continue to rally, securities lending demand has been subdued as hedge funds continue to lack conviction in short strategies. According to IHS Markit, global securities lending revenues for Q1 2019 were 10% lower than Q1 2018, although 3% higher than Q4 2018. The bright spot is corporate events, such as the Eli Lilly spin off of Elanco Animal Health which generated an estimated $177 million* in revenue for lenders who held shares of LLY in Q1. While hedge fund demand is cyclical, some structural changes are impacting our industry more longer term. Specifically, greater focus by borrowers on internalizing loans has taken some activity away from beneficial owners, and tax changes in Germany, France and Canada have further challenged traditional yield enhancement revenue. However, there are also some structural factors giving rise to optimism too. Borrowers have largely adapted their balance sheets to post-crisis regulation and the capacity constraints which have subdued hedge fund leverage in recent years are less of an issue now. Additionally, progress is being made in creating a securities lending and borrowing framework available in key emerging markets, most notably China which would be a boon for beneficial owners.

Supply Dynamics

As the relevancy of securities lending increases, particularly amongst asset managers, global lendable assets reached $20.4 trillion in Q1*. Given the aforementioned subdued demand environment and focus from borrowers on efficiency, it is increasingly important for lenders to position their assets to be as attractive as possible in what is a very over supplied market – particularly in the general collateral space – where the ability to lend for fixed terms with flexible collateral is important to balance sheet sensitive borrowers. However, there is less pressure on lenders whose philosophy is to generate risk-adjusted returns from intrinsic value lending, since the costs for borrowers is less of an issue when borrowing specials. Instead, evaluating parameter flexibility (security buffers, lendable markets, funds and asset classes) offers a more appropriate way to boost returns.

Given the oversupply in the market, there was discussion about whether it is worthwhile for new lenders to come to the market if they hold only large cap general collateral securities. This position was questioned given how lucrative recent opportunities have been for holders of blue-chip names such as Eli Lilly, DELL and CBS.

Tech Spend Focus

Given the demand environment and pressure on profitability, the industry is making increased investments in technologies that improve efficiency and pricing power. As lenders evaluate ways to make their supply more attractive, trading desks are exploring algorithmic pricing and machine learning to increase automation and execution. Developing proprietary trading capabilities and client experience tools remain core to most agent lender’s internal development efforts, while commoditized technologies such as post trade processing are being purchased from vendors. Meanwhile, regulatory reporting initiatives such as SEC Modernization and Securities Finance Transaction Regulation (SFTR), have resulted in a larger portion of IT spend dedicated to data transparency and connectivity, ensuring lenders are able to meet their requirements under the new regulation.


There was general acceptance that performance benchmarking in securities lending has been sub-optimal for a couple of reasons.  First, the data is not granular enough to provide real like for like benchmarking. For example, comparing performance data, which includes clients with wholly different tax rates and collateral parameters is inherently flawed, and second, the data can be manipulated to show every agent being the top performer in the market.  Data vendors such as IHS Markit are therefore working towards creating more filters to accommodate better like for like benchmarking and working with the International Securities Lending Association (ISLA) to agree on a uniform set of performance metrics.


*source: IHS Markit