Interoperability and connectivity are intrinsic necessities as the traditional world of marketable securities moves towards a digital future, says Igor Salzgeber, VP, business executive, securities and processing, FIS
Digital transformation affects every aspect of our personal and professional lives. The ability to store and transfer data, and to analyse and process it to deliver actionable information, drives virtually every aspect of modern life. Similarly, within the financial markets digital transformation has gained significant momentum over the recent past. As such, it is no surprise that the securities finance and collateral industry is looking closely at how to leverage digital technologies to change existing business models and processes and to provide new revenue and value-generating opportunities.
In our industry, as with many others, such a transformation is vital to meet today’s challenges and for future growth. The good news is that there are multiple innovative initiatives available today from providers like FIS and from industry partners. This article looks at what is driving this digitalisation in our domain and how market participants are addressing it.
What do the statistics say?
Digitalisation and the need for efficiency improvements represent broad objectives, but what are the actual numbers behind this pressure? In 2020, FIS Securities Finance Market Data recorded an average daily loan count of 2.32 million. In 2021, these numbers increased very slightly, by around 2 per cent, to 2.37 million a day. The first quarter of 2022, however, has seen a jump to 2.71 million loans per day. So, while the difference between 2020 and 2021 was marginal, the growth in activity between 2020 and 2022 shows a 17 per cent increase in activity.
The number of loan ‘units’, defined as one share or bond lent or borrowed, is on the rise too. In 2020, each day saw an average of 2.06 billion units lent. Last year saw this jump to 3.27 billion units, and the first quarter of 2022 has seen daily averages of over 4.05 billion units, almost double the volumes moved across the market in 2020.
Revenues have grown during the same period — but only marginally, indicating that the industry is working much harder to gain these incremental advances. The outlook for 2022 would suggest that the steep rise in transaction rates will continue, with each additional loan creating frictional costs for booking, settling, marking, and reporting. With the additional spectre of enhanced penalties for settlement failures looming, the need to automate and drive those costs down intensifies further.
Taking advantage of machine learning
Widening the pipework to accommodate the increase in breadth and depth of activity is only part of the solution. Successfully managing these increased flows can only come through effective, accurate and timely connectivity from the origination of the borrow request to the settlement of the return leg of the desired instrument, all against the most economically suitable collateral.
Breaking that out into logical steps, FIS has machine learning processes in place that can identify and address the requests most likely to turn into actual borrows, enabling the many thousands of speculative requests to be downgraded. This process enables downstream activities to focus on the requirements that will deliver for the requesting clients, while facilitating trades that earn revenues.
Once orders are processed effectively, they need to find the right supply. There are several platforms and solutions available on the market, each addressing specific parts of the puzzle rather than the entire cross-product picture. An efficient and automated marketplace that delivers the most economic match will outperform simple rules-based messaging systems.
But what does ‘most economic match’ mean? The cost to borrow a security can no longer be measured by just the fee or rebate. Reporting costs, the cost of collateral delivery, settlement failure risks and balance sheet utilisation all play a part in determining the actual cost of a transaction. With loan count activity levels on the rise, and revenues lagging frustratingly, margins are under pressure. As a result, making the most of every trade becomes increasingly important.
The application of machine learning will enable future platforms to make increasingly accurate and effective recommendations for matching availability and demand. This will bring down the costs of transactions, preserving and even growing margins.
New connections Using the CDM
The current flow of securities lending post-trade processing is being challenged both by regulation to shorten settlement timelines and by tighter fail control. However, FIS is working on significantly improving and streamlining existing processing times to enhance the interoperable flow. This includes working with those clients who are only partly on our platform, planning communications with other vendor platforms through the Common Domain Model (CDM).
Callback message processing, when borrowers and lenders are on separate platforms, is currently a manual task. This process can result in mismatches that can create costly headaches, from delays in the return of collateral to the application of shares to the incorrect loan, which can be time consuming to resolve. Recalls are another area where not all participants are using the automated solutions in the market, resulting in incorrect recall processing. With regulations moving toward accelerated settlement dates in the US and fines in EMEA, market participants will not have time to research and correct errors caused by manual processing which risk failures or fines. Removing as much manual intervention as possible will play a part in alleviating some of these pain points.
As new products come to the market, connecting to these platforms will become integral in terms of giving clients the connectivity they need to support their businesses.
Interoperability: advances in pre- and post-trade
In light of ever-growing trading volumes and squeezed margins, efficiency gains are more important than ever. In the past, having conceptual knowledge of who will accept what collateral has been good enough, but today that approach needs a technical overhaul. To empower efficient trading decisions, deep sets of data need to be analysed.
From a simple availability perspective, firms need to know what positions they have, where they are located, what they are worth and where they can be used. These are simple enough questions on the face of it, but as you drill down into each, the need for the right wiring is evident. This can be thought of as a three-part maxim: centralise, analyse, optimise.
Gathering your inventory of usable positions demands up-to-date feeds of trading, liquidity and settlement activity. That calls for connectivity with all the trading activity across the firm, as well as with the custodian and triparty network to centralise what assets are unencumbered in the box at any location and all in real-time. That usable inventory should then be overlaid with a centralised store of collateral schedules for all the possible uses of those assets: triparty shells, central counterparty (CCP) schedules, central bank schedules and bilateral counterparty schedules. It is vital to have connections in place to external infrastructure providers to import the eligibility rules, pricing rules and concentration limits.
Once the firm knows which assets are at its disposal, and where they can be used, the next step is to look at what is needed. Those requirements can be affected by revenue objectives as well as liquidity, capital, and collateral needs across CCPs, triparty, central banks and bilaterally. That will become simpler in a distributed ledger based world, but in the meantime, those are connections that every firm in the market must manage and may be best handed over to a trusted partner to benefit from scale. With those connections in place, the firm will be able to analyse inventory potential in detail, and map strategy to goals for liquidity, revenue, and collateral. Only then can the next optimisation step be taken.
As the traditional world of marketable securities moves along the path to its digital future, interoperability and connectivity are intrinsic necessities. The Common Domain Model will help with standardised representations of assets, trades, schedules and so forth, all of which are key staging posts along that road. It is incumbent on technology vendors and infrastructure providers to support those standards as the lines between traditional assets and digital assets become increasingly blurred.
In conclusion
In an increasingly complex and globally connected world, making the right connections in the right way is essential. Overlay distributed ledger delivery with the benefits of having market participants communicating using the Common Domain Model, and the market has the template it needs for efficient order origination, management and matching, all of which is key to ensuring the accurate and timely delivery and return of assets and optimised collateral. Many of these market developments have been discussed in the abstract for years, but they are now a reality — and, indeed, a necessity if the market is to grow and develop both efficiently and effectively.
