Financial Center Artificial enthusiasm Information 17 avr. 2018 Are new technologies really going to reshape the securities services industry over the next decade? A report published in March 2018 by consulting firm McKinsey suggests that over the next five years, the global securities services industry will face more change than it has over the last two decades as it incorporates new technologies such as automation and robotics, advanced analytics, and distributed ledger technologies (DLTs). The report, “A calm surface belies transformation in securities services”, notes that custody and fund administration have experienced a decade of continuing margin pressure on their core services, but that in the next few years, rising asset values and increasing net interest income will offset this with industry revenues growing at approximately 3% a year. Success, however, will require “heavy investments in advanced analytics, automation and robotics, and other new technologies, as well as innovative services in data transparency, risk management, and regulatory reporting. Companies that fail to take clear strategic stances and continue to squeeze out only small and tactical gains in efficiency will be left behind as the industry transforms.” Is that engagement evident in industry attitudes? In 2017, SIX commissioned a study of approaches to new technologies in financial services. In September and October 2017, 60 decision makers at financial institutions were interviewed, including heads of custody, heads of operations as well as collateral managers in the US, UK, Germany and Switzerland, to gauge their expectations of how technologies such as artificial intelligence (AI) and robotic process automation (RPA) are likely to be deployed in the securities industry in the years ahead. Creating value through new technologyAsked which technologies they believed would be in mainstream use for at least one post-trade function by 2027, 63% of respondents cited RPA and AI, 57% DLT, 50% cryptocurrencies and 37% application programming interfaces (APIs). Common uses of AI in post-trade processing by 2027Some 87% of respondents saw a genuine use for AI in post-trade processing. The most common mainstream use envisaged is for regulatory compliance (53%), particularly among asset management firms and those who see regulation as hampering innovation. Other uses cited by a significant number of participants include client service (50%), collateral management (48%) and margin call processing and dispute resolution (40%). Areas that can benefit from RPARPA is seen as likely to create the most value through cost reduction (68%) and driving efficiency (57%). It is perhaps one of the most visible technologies in terms of early adoption, where it is already deployed to handle routine, rules-based functions such as account opening. In addition to RPA, it is clear that custodian banks have been increasingly experimenting with different types of AI, such as machine learning. Speaking at Sibos 2017 Toronto, Kirsty Roth, Global Head Operations at HSBC, said the technology will eventually benefit employees in back- and middle-office roles. “These people did pretty dull tasks, and now they do not have to,” she commented. “People are moving up the value curve, which is better for their careers.” Nor does it seem that fears of being made redundant by “intelligent” machines are widely shared in the securities services industry. In a recent poll organized by Global Custodian magazine, only one in 39 people believed their role would be automated by the end of 2020.