A diverse panel of tech experts took the stage at Nicsa’s recent SLF to share their perspectives on the asset management industry’s digital transformation trends — from blockchain and artificial intelligence (AI) to behavioral biometrics and cybersecurity. The session, moderated by Lyndsay Noble, Director of Data Science at SS&C, featured thought leaders from BNY Mellon, Securitize, and Fidelity Investments.
Beyond Blockchain
Carlos Domingo, Co-Founder and CEO at Securitize, said the biggest misconception surrounding blockchain is that it’s being promoted as a solution for the world’s largest problems.
“Blockchain, in particular, only solves certain problems where you have a number of people who need to collaborate on the same set of data, and they need to trust that data without a centralized entity that controls the flow of data,” Domingo said.
And, although Bitcoin was invented 10 years ago, blockchain as a technology suitable for the enterprise environment is still in its early stages. “It reminds me of the beginnings of the internet — in blockchain, we are still in the dial-up era, if you will,” he said.
At the same time, Domingo said blockchain is a particularly useful platform for digitizing the representation of ownership. “We’re still at the forefront of the technology, but at the end of the day, in the world of securities, blockchain can provide better, cheaper, and faster solutions than traditional technology.”
Behavioral Biometrics and Fraud Prevention
Michael West, Vice President of Cyber Investigations at Fidelity Investments, said AI requires a mindful approach as well, specifically within the fraud industry.
“I hear quite frequently that people think you can use AI without understanding what the data means— and I think that’s a recipe for false positives and disappointment,” he said. “It’s almost become a threat to the anti-fraud industry because it’s getting a disproportionate amount of attention, meaning time and money.”
West said there’s a broad range of acceptability when it comes to AI causing customer friction.
“When you’re logging in somewhere, and your machine-learning modules might detect suspicious activity and requires two-factor authentication, that’s a very different interruption of a process than a machine learning process that attaches to restriction codes and can stop a stock trade mid-sentence,” West said.
Artificial Intelligence and Machine Learning
Michael Demissie, Head of Advanced Solutions - Machine Learning, AI, at BNY Mellon, said that while there’s ample emphasis on what machine learning solutions can do in a small, experimental setting, there’s not a lot of focus on how to deploy such solutions in production at scale.
“We need to put the same level of attention on the entire lifecycle in terms of what it means to maintain and monitor a machine-learning solution from a performance and support perspective,” he said. “Technology is often described as an easy plug-and-play solution when that’s not always the case.”
Still, AI and machine learning are driving advancements from the back office all the way to portfolio management in helping automate operations and investment decisions, among other processes.
“We are seeing a lot of benefits of AI techniques around blending disparate data and manufacturing intelligence and insights, and telling the stories of what the data are showing to sales and marketing associates so that they can activate it,” said Jane Conway, Digital, a data and analytics innovator for investment and asset management firms worldwide.
“I think the thing to remember is that the purpose of AI is the artificiality,” she added. “That it’s just a technique to pull together information to help humans make decisions better. We are the best, smartest machines. The challenge is, we can’t process gobs of data at once.”
Note: Although the observations contained in this work represent the best thoughts of the individuals comprising the Nicsa panel, they do not necessarily reflect the views of Nicsa or any of its member organizations. Matters addressed in this work may touch upon legal or regulatory matters, however nothing herein is intended to be or should be construed as legal advice. You should contact your own counsel in order to obtain legal advice regarding these or any other matters.
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