BNY Mellon: ‘Doing the right thing’ to pave the way for AI & data analytics
CUSTOMERS are getting increasingly anxious about the use of artificial intelligence (AI) and data analytics in the banking and financial services industry, worrying about ethical flaws, biased decisions, among other things.
However, regulators are taking action. Recently, the Hong Kong Monetary Authority issued guidelines to the industry about the use of AI — while the Monetary Authority of Singapore (MAS) has been working with industry partners for a while to develop principles, frameworks, and policies.
At the recent Singapore Fintech Festival, MAS announced the formation of a consortium to develop a new framework, dubbed Veritas, to strengthen internal governance around the application of AI and the management and use of data.
The consortium, currently comprised of 17 members — includes BNY Mellon, a 235-year-old institution with a global presence and plenty of experience dealing with rapidly changing markets and consumer demands.
To understand the objectives of the new Veritas framework and the bank’s opinion on the responsible deployment of technology, Tech Wire Asia spoke to BNY Mellon Global Head of Innovation Hans Brown.
“From our perspective, we want to stay ahead of the curve when it comes to technologies such as AI and data analytics, which means we have to be part of the discussion with regulators and industry partners as these tools are developed.”
Since the beginning, Brown emphasized that BNY Mellon’s founders have built the organization on the principle that it can always be trusted to ‘do the right thing’.
“So, we’re looking to ensure that we can get moving with AI and data analytics applications while staying true to our ethos.”
The purpose of the Veritas framework is to enable financial institutions to evaluate their AIDA (artificial intelligence and data analytics) – driven solutions against the principles of fairness, ethics, accountability and transparency (FEAT) that MAS co-created with industry partners last year — “and we’re focused on getting to a point where we can do it at scale”.
Overall, although the emphasis on ethics and transparency is being driven by regulators in Asia, Brown believes that there’s a need for senior business leaders, including leaders at BNY Mellon, to provide guidance to managers within the organization and contribute to the discussion outside the organization.
“It’s not just the right thing to do, it’s what regulators across the globe — including MAS — expect of us, and it’s what our clients expect of us, it’s what society at large expects of us.”
Brown, who appreciates the opportunity to be part of the consortium, is excited about the discovery, research, and analysis that all of the organizations will do together and the impact it will have on the future use of AI and data analytics in the financial services industry.
“We don’t know what we don’t know, which is why we welcome the fact that this is a consortium-based approach and harnesses the collective intelligence of all the organizations involved.”
At the end of the day, the Global Head of Innovation expects that the consortium will reach an agreement on what it means to actually comply with the MAS’ FEAT principles, in a scalable and systemic manner — but he said he won’t be surprised if we end up doing something more or even different.
Ultimately, the consortium is on an R&D mission and there’s no guarantee around what it will find or decide at the end — but it will be a step in the right direction, that’s for sure.
BNY Mellon’s innovation mantra: Run your own race
The bank’s efforts to ensure the ethical and responsible use of AI are laudable but it raises questions about whether or not that will slow down the organization and allow competitors to race past them with exciting innovations.
Brown assured Tech Wire Asia that he along with BNY Mellon Head of Digital Roman Regelman are doing everything in their power to “digitize this very bank” and its operations quickly, effectively, and meaningfully — and responsibly. The one thing they aren’t doing, however, is worrying about the competition.
“It’s a false economy to worry excessively about what your competitors are doing versus what you’re doing.
“The way I look at it is, if we’re focused on the outcomes that we want for our clients and are constantly engaging with our clients, we’ll not only understand their challenges but also be able to help overcome them proactively.”
BNY Mellon, for example, is currently working on several projects, including many that leverage AI, but its ultimate focus is on helping customers get more out of their relationship with the bank.
A project that Brown highlighted involved the use of AI and natural language processing to classify email inquiries from clients – it is a task that generates no revenue and requires time and effort to sort through and respond to.
Through the use of a machine learning model, it helps to generate greater operational efficiency and reduce costs, thus allowing the staff to focus their time and energy on performing higher-value activities for the customers.
Automating all of those inward email inquiries using technology not only helps free up executives and therefore costs, but also allows the bank to focus their time and energy on doing more meaningful work for its customers as a result.
“We choose to focus on whether we’re doing the right thing for our clients, every day — that’s where I choose to burn all my calories — understanding them, empathizing with them, and preparing to help them deal with future challenges.”
Ultimately, BNY Mellon is keen on upholding the tradition set by its forefathers and believes that ‘doing the right thing’ will always pave the way to sustainable, tangible, long-term success.
- New industry guidelines make facial recognition-based payments safer
- Can e-wallets really take off if user concerns remain unaddressed?
- Experts believe that AI can enhance the clinical decision support system
- Data sharing in manufacturing offers an untapped value of $100b
- If anyone can successfully launch a digital currency, at scale, it is China