AI Trends with Traction

As we head further into 2019, artificial intelligence is uniquely poised to drive operational efficiencies, strengthen compliance efforts, and inform investment decisions in fund management.

“There’s a lot of change going on in the world at large in terms of technology and human behaviors — and none more so than in the field of financial services,” said Nasir Zubari, CEO at theLuxembourg House of Financial Technology Foundation, during a recent #WebinarWednesday panel on the topic. “Fintech is a buzzword, and AI, blockchain, and big data are inescapable to some degree in our daily lives.”

Zubari moderated the panel, which featured candid discussions with leaders from Accenture, BNY Mellon, and Trinova Group.

SIGNIFICANT TRENDS

David Jones, Managing Director at Accenture, has made quite a few observations on the state of AI in the financial services industry in the last nine months:

  1. Management objectives and organizational support are maturing.“In 2018, about 80 percent of organizations had some sort of true funding to support AI-driven strategies,” Jones said. “As we pivot into 2019, the expectation is that capabilities and delivery mechanisms will mature.”
  2. A linkage between re-engineering, intelligent automation, and sourcing strategies.“Think about how you’re going to drive operational optimization and align your organization to accommodate new technologies,” he said.
  3. Customer journeys and data maturity are central to scaling efforts.“Data maturity and analytics are the drivers behind how AI is being deployed, and thus central to that effort overall,” Jones said.
  4. The road forward is clear, at least in the near term. Data within documents, like transmission filings; semi-structured texts, such as email; and voice, including phone calls; are being aggressively pursued in terms of how organizations are leveraging AI capabilities. The key is to access information and use it to drive more best-practice actions our consumers.
  5. Platform plays will influence strategy and drive the talent agenda. “The pivot from rule-based decisioning to AI-based decisioning is happening over the next 12 months,” Jones said. “AI-based decisioning platforms will be inclusive of things like robotic process automation.”

OPERATIONAL CONSIDERATIONS

Chuck Gallant, Managing Director at BNY Mellon, provided an operational perspective on digitizing the service environment through AI. “We have set up a center of excellence, called Intelligent Process Automation, to deal with everything from automation and robotics to machine learning and the cognitive work we’re doing,” he said.

Gallant echoed Jones’s statement regarding the importance of re-engineering. “We start with a re-engineering team and situational analysis — whether it’s a sales process or a servicing process we want to automate,” he said. “We break that process down and do a lot of mapping with it to understand what we want to automate and what solutions we can implement. We don’t implement a solution just for the sake of it.”

Gallant said BNY Mellon leverages automation for repetitive, manual data entry processes whereas machine learning takes things to the next level. “There are a lot of technologies out there that can pull textural and even handwritten data off documents, but the success rate of reading and interpreting that data tends to be fairly low with today’s character recognition technology,” he said.

“Through machine learning, we can actually learn from the entries that are made in error — for example, if the letter ‘I’ is mistaken as a one, etc. — and we can enhance the process of character recognition so we have more success with data we’re extracting from these documents.”

THE VIEW FROM LUXEMBOURG

Martin Dobbins, Managing Partner and Independent Director at Trinova Group, said AI, machine learning, and distributive ledger technology are impacting fund administrators and custodians as well as transfer agencies and management companies.

“Some of what’s been driving a lot of these technologies — other than operational efficiencies and costs — is regulation,” Dobbins said. “How do they adapt to some of the regulatory environments we see around KYC/AML, risk management, regulatory reporting, and financial reporting?”

Enter FinTech players. Dobbins said these companies are committed to evolving themselves to support the industry through a laser-focused approach on specific functionalities.

“They’re not trying to be everything to everybody,” he said. “You might have firms focusing on distributed ledger technology around authorized signatures. We’re seeing expanded attention on distribution due diligence, which has been a key aspect for the Luxembourg industry when it comes to distributing in over 65 countries.”

Dobbins said applying AI and machine learning to Luxembourg regulations has helped reduce onboarding time. “It’s improved the quality of information, and from that, built out a much more robust data environment where you now see risk and compliance organizations having more real-time information available they can use to make bigger, more efficient decisions.”



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