Market data: Why beneficial owners are hungry for data

The new trend for beneficial owners to take full advantage of data is important in Europe, where lending revenues have declined because of monetary policy. Lynn Strongin Dodds reports.

Beneficial owners can not only use data to compare market participants but also to enrich their securities lending programmes. A recent survey by DataLend in conjunction with Funds Europe showed that generating alpha was the main driver for 66% of respondents that were engaged in securities lending – a 7% hike from the previous survey in 2017.

Moreover, 81% of beneficial owners were widening their usage of securities lending market data, employing it to determine which assets to use, to monitor agent performance and quantify the effect of any changes to guidelines.

This is a real sea-change because in the recent past, beneficial owners mainly used the information for price transparency, liquidity and benchmarking. They did not integrate the material into their wider portfolio strategies.

Nancy Allen, global product owner at DataLend, says it has only been in recent years that securities lending has become more complex. There are new challenges, she says, that are primarily driven by regulatory changes and capital charges and which have made the management of lending programmes considerably more nuanced. Beneficial owners, alongside their agents, must consider a wider range of collateral types, varied term structures, new routes to market and ongoing regulatory reporting requirements.

“Securities lending revenue, formerly viewed as an offset of custody fees, management fees or operational expenses, is now understood to be a revenue stream that can enhance the performance of the underlying fund,” she adds. “In other words, securities lending is officially an investment product, and beneficial owners are actively managing their programmes to extract optimal value.”

Ben Challice, global head of agent lending and collateral management at JP Morgan, echoes these sentiments. “What is interesting is how data is increasingly being consumed higher up the chain,” he says. “Traditionally, the data was used for benchmarking purposes – but today, asset managers and owners are using pre-trade analytics to help inform the investment decision-making process. They want to better understand, for example, the specialness of an asset, how widely it is on loan and the drivers of demand.”

Crowding into opportunities
Current market conditions have also focused beneficial owners’ minds. The prolonged low interest rate environment has meant that many fund managers are crowding into the same opportunities.

“In the current cycle, we are seeing asset managers and owners looking at generating alpha from wherever they can get it,” says David Lewis, senior director at securities lending service provider, FIS.

“Although the return from securities lending is relatively low and it comprises a small part of the income of, for example, an equity portfolio, it can still make a difference.”

Paul Wilson, global head of securities finance at IHS Markit, has also seen in the past year “a material increase for greater transparency”. He says this is because there are more beneficial owners chasing the same revenue opportunities and using different data points to better structure their programmes and make risk and reward more quantifiable.

Although different tools are at their disposal, there has been greater emphasis on analysing revenue attribution to identify which assets are generating returns and why.

DataLend’s Allen says: “They [beneficial owners] are looking at what is driving the return – is it collateral, term, intrinsic value or cash reinvestment? By looking at attribution from a different angle, beneficial owners can identify missed opportunities. For example, are there dormant assets in inventory that could have been lent out profitably?”

Allen believes that once beneficial owners understand the revenue attribution of their own portfolio, they can learn more by looking at the broader industry’s performance. “Performance measurement is a process to assess how the industry, on average, would have performed with a specific portfolio over a period of time,” she says.

“It is a valuable way for a beneficial owner to identify broader industry trends and demand opportunities. When revenue attribution is combined with performance measurement, the beneficial owner is best positioned to capture optimal value.”

Against this backdrop, agent lenders are attempting to up their game by using data more effectively to help frame discussions around programme parameters. They not only want to help clients boost returns but also their own lending revenues.

Figures from IHS Markit show a mixed picture. Lending revenues rose 4.7% to $2.6 billion (€2.3 billion) in the third quarter of 2019 from the same period the previous year. However, the driver for this was activity in the US. Their counterparts in Asia and Europe experienced, respectively, 14% and 13% declines.

The end of QE
In Europe’s case, the drop was partly due to the decline of revenue streams from lending high-quality liquid assets, or HQLAs – a term that normally refers to developed market sovereign bonds. This occurred due to the European Central Bank winding down its quantitative easing programme in December 2018.

The revenue decline was also attributed to the lofty returns from sovereign bonds, which hurt borrowing demand because short selling based on expectations for interest rates went askew as the US Federal Reserve cut rates instead of, as expected, increasing them.

Agent lenders are under pressure to roll out more sophisticated and innovative analytical tools and to offer systems that can aggregate internal and market data that can be used to identify market trends and price instruments more clearly.

There is no one-size-fits-all solution. Mark Jones, regional head of securities lending at Northern Trust, points out that requirements vary significantly across beneficial owners depending on their size, location, complexity and the structure of their programme. “We are definitely having deeper conversations and are seeing a greater demand for more bespoke tools,” he says. “There are still some beneficial owners who want to see a report monthly but who are also seeking more information about their programmes – the lent assets, collateral and risk management factors.”

They are also turning to agent lenders to separate good data from bad data. Ross Bowman, global head of client management, securities lending at BNP Paribas, says: “What we are seeing is that beneficial owners are combining statistical market data provided by external vendors with programme-specific market colour they receive from their agent lender.

“They want insights into trading strategy and underlying demand rationale to support how they see their programme being traded. However, they also want flexibility in the way the data is distributed and to have the ability to pick and choose the data elements they want.”

BNP Paribas has introduced a pricing engine which uses machine-learning techniques together with numerous data points that, says Bowman, can help price securities demand more efficiently and determine where prices may move to.

One of the biggest hurdles is the lack of standardisation, according to Challice at JP Morgan. The variety of systems means data is in different formats. This is something the industry is trying to grapple with, he says.

One of the silver linings of the Securities Finance Transaction Regulation (SFTR) is that it will produce more timely and standardised data. This is expected to take data to the next level of transparency, Challice adds, and enable beneficial owners to make more informed decisions regarding risk and trading decisions.

DataLend’s Allen also believes that SFTR will have an impact. She also underlines the importance of having standardised formats when it comes to performance measurement and says there is a need for more consistency in data submission.

“The industry as a whole is working to establish standards, and data providers are continually evolving our data-cleansing algorithms to ensure the highest quality of output is supplied back to our community of users,” she says.

SFTR, which is expected to become effective in April 2020, aims to shine a brighter light on securities finance by creating a need for numerous collateral updates, lists of counterparties, and daily information on margin-lending transactions and valuations.

The data requirements are described by many participants as unprecedented, with the SFTR mandating 155 data fields compared to 129 required under another regulation concerning over-the-counter derivatives, known as Emir, and 65 data fields for the wide-ranging Markets in Financial Instruments Directive. The problem is that although the SFTR data-fields may be more in line with those of Emir, 40% of the 155 data fields are not readily available today and firms will have to conduct an audit to locate the data.

In addition, the reporting will have to be submitted in a specific format – ISO20022 – to trade repositories for the first time, and reconciliation will be required across 96 fields.

©2019 funds europe



Innovative US companies are providing some of the solutions to the climate crisis and transition to a more sustainable economy. We see potential opportunities in areas including renewable energy and…
This white paper outlines key challenges impeding the growth of private markets and explores how technological innovation can provide solutions to unlock access to private market funds for a growing…


Visit our dedicated Ireland channel for all the latest news and analysis on the country's investment industry.