SIBOS: Industry has to make the basics of its data strategies “rock solid”
When it comes to deploying the right artificial intelligence (AI) and machine learning solutions for data strategies, the industry needs to “lay a solid foundation for its data strategy,” said Ian Donald, Head of Prime and Securities Services Technology at Standard Chartered Bank.
On a panel titled Transformative Securities Technologies and Operating Models hosted by Tata Consultancy Services (TCS) BaNCS, Donald explained that a robust data strategy requires “the right data in the right place, at the right time.” .
This should be combined with proper governance and skilled personnel – not just technology personnel, but also business and operations personnel – for a collaborative approach, according to Donald.
He added, “Business processes are largely data dependent, this is nothing new and has been since the industry began. But especially in the last ten years there has been an explosion of new data solutions. “
“Ten years ago, data scientists were considered quite a niche role in financial services, but today a chief data officer has a lot more responsibility than ever before. We see more data lakes emerge and a wealth of tools available that can help keep data at hand.
“And this shouldn’t be done in isolation, of course there has to be an understanding of customer needs and their weaknesses to see how we can solve their data-related problems. This is a rich area that you can explore further as long as you have this strong foundation. “
Moderator Giles Elliott, Head of Business Development, Capital Markets at TCS, asked Donald if he thought the securities industry had “moved slowly” in adopting AI and machine learning in order to fully exploit the data opportunities.
Donald commented, “The industry has been reasonably conservative in its approach to adopting both AI and machine learning, but they are catching up. The impetus for securities services and custodians is there to address this problem head on – that is, how AI and machine learning can be used to address the vulnerabilities in industry data. This is a collective problem that we as an industry should be able to solve together. ”
Elliott then went on to discuss the impact of the pandemic on transforming new technologies such as AI and machine learning, of which Donald said, “It has certainly been an interesting couple of years, the pandemic has accelerated the need for collaboration and an innovation agenda.” . ”
He added, “Personally, I’m a huge fan of physical data and until the beginning of the pandemic it was still a given way to access it. But when the industry started working from home it became problematic. “
“From a personal point of view, I used to sign physical documents, but when the pandemic came it obviously went electronic quickly and I wondered why I hadn’t done this sooner, it was so much easier. And I thought, in which other areas could I still digitize? “
Rajesh Gopinathan, CEO and Managing Director of TCS, added that AI and machine learning are essential for compliance and the fight against money laundering, with AI specifically helping TCS with predictive analytics, he said.
“Now, [industrywide] We have the tools to help us do a lot more than we could in the past. “
Moderator Elliott then asked what the securities sector could learn from the cashless payments sector in the future.
When asked, Donald said that “cash is at the forefront of innovation”. He also cited that Sweden wants to be cashless as early as 2023 and that Singapore is following the same path of becoming a cashless society in the near future.
Gopinathan closed the panel by predicting that “tokenished assets will be the future” and that traditional and emerging asset classes are “two worlds that can certainly coexist”.
