SFTR may enable AI in securities lending
30 November 2017 London
Image: Shutterstock
Incoming regulations that require vast amounts of data generation could pave the way for the introduction of artificial intelligence (AI) into securities lending, according to Broadridge.
The data that will come from compliance with the Securities Financing Transactions Regulation (SFTR), expected to go live in 2019, and the European Market Infrastructure Regulation (EMIR), could allow firms to employ AI to “second guess moves by counterparties, clients and regulators and central counterparties”, Broadridge predicted in a recent whitepaper.
The paper stated: “For example, regulators may react to certain trends in the SFTR data that signal a buildup of risk by raising haircut floors or increasing capital requirements. If market participants can use AI to better predict when this type of activity will occur, along with other key events such as bond market squeezes, then this can inform strategic decision making.”
Broadridge noted that although an AI system may be able to gorge on this banquet of data, the key to its usefulness will “depend on whether the depth and timeliness of data publicly available allows interpretation of market trends in a way that can guide future decision making”.
“This could provide an opportunity to apply cognitive computing algorithms against SFTR and EMIR data.”
However, the report added: “Due to the large volumes of very granular data being collected, some work may still be required to standardise this to a degree it can provide value.”
Several firms outside the usual front running technology giants are looking to see if AI could be a way of making all the data being generated for these regulations to work for the firms themselves and not just sit on the regulator’s record books.
Broadridge is looking into how AI can improve securities finance supply and demand.
According to the firm, this includes securities available for borrow/loan or needed for settlement, short selling, or any other purpose.
Caceis is one of many asset servicing firms using machine learning to ease the pressure on its securities lending desk and boost returns for clients by applying AI techniques to price loans of corporate bonds.
Clearstream is also championing the cause for AI as a vehicle to greater efficiency.
In its October data report, the post-trade services provider claimed that new waves of technology, such as AI and blockchain could support the market in overcoming barriers to harmonisation.
Clearstream claimed that these new technological developments, will also help to deliver efficiency gains and support risk mitigation.
The data that will come from compliance with the Securities Financing Transactions Regulation (SFTR), expected to go live in 2019, and the European Market Infrastructure Regulation (EMIR), could allow firms to employ AI to “second guess moves by counterparties, clients and regulators and central counterparties”, Broadridge predicted in a recent whitepaper.
The paper stated: “For example, regulators may react to certain trends in the SFTR data that signal a buildup of risk by raising haircut floors or increasing capital requirements. If market participants can use AI to better predict when this type of activity will occur, along with other key events such as bond market squeezes, then this can inform strategic decision making.”
Broadridge noted that although an AI system may be able to gorge on this banquet of data, the key to its usefulness will “depend on whether the depth and timeliness of data publicly available allows interpretation of market trends in a way that can guide future decision making”.
“This could provide an opportunity to apply cognitive computing algorithms against SFTR and EMIR data.”
However, the report added: “Due to the large volumes of very granular data being collected, some work may still be required to standardise this to a degree it can provide value.”
Several firms outside the usual front running technology giants are looking to see if AI could be a way of making all the data being generated for these regulations to work for the firms themselves and not just sit on the regulator’s record books.
Broadridge is looking into how AI can improve securities finance supply and demand.
According to the firm, this includes securities available for borrow/loan or needed for settlement, short selling, or any other purpose.
Caceis is one of many asset servicing firms using machine learning to ease the pressure on its securities lending desk and boost returns for clients by applying AI techniques to price loans of corporate bonds.
Clearstream is also championing the cause for AI as a vehicle to greater efficiency.
In its October data report, the post-trade services provider claimed that new waves of technology, such as AI and blockchain could support the market in overcoming barriers to harmonisation.
Clearstream claimed that these new technological developments, will also help to deliver efficiency gains and support risk mitigation.
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