AI might not be the best bet for banks pursuing digital transformation
BANKERS have been under pressure to digitally transform themselves as customers demand new-age products and services.
Since climbing the digital maturity curve helps reduce costs and boost profits in an industry struggling with margins, stakeholders are keen on bank CIOs and CTOs pursuing digital projects as well.
As a result, many leaders think of going after the most exciting technology out there — artificial intelligence (AI) — but that might not be the smartest thing to do argue IDC analysts at the recent Asian Financial Services Congress.
For banks working on digital projects over the years, carefully digitizing their portfolio of offerings to customers and streamlining back-end processes to minimize redundancies created by legacy infrastructure, AI might be the technology to help take the organization to the next level of maturity.
Unfortunately, it’s not a technology every bank can trial, deploy, and scale across the business right away. They’re simply not ready for it.
At a roundtable discussion during the event, Bank of the Phillippine Islands Chief Digital Officer Noel Santiago made an important comment that shows some leaders understand (and agree with) IDC’s advice.
“While we understand that the world is moving to AI, we’re going to wait and watch — not every use case is valuable to all banks. We’re buying a ticket to watch the match but we’re not putting a team to play the game,” said Santiago at the event.
Back home, his team is working on managing the organization’s repositories to create a sophisticated data platform that can support the use of smart and interesting AI solutions when they’ve been proven.
People’s Bank of Sri Lanka CIO Priyantha Edirisinghe agreed with Santiago and IDC.
“We’ve just started out with our digital transformation journey. We’re digitizing key processes that really help customers, but we’re not diving into AI — because that needs more data than we’re prepared for,” explained Edirisinghe.
Although some customers will be disappointed that the People’s Bank isn’t rolling-up its sleeves to develop AI-based innovations, the organization is certainly not lacking in its digital ambition.
Edirisinghe’s bank is certainly making headlines with digital-first solutions developed to remedy common pain-points and solve everyday challenges faced by its customers.
IDC AVP Christopher Lee Marshall is optimistic about the potential of AI but is clear with clients about the need to get the house in order before they embark on the journey.
“AI doesn’t make sense unless you have a data platform to support it. The whole data infrastructure, the business intelligence capability, the analytical literacy of the organization, the relationship between data and business strategy — these have all got to be in place before AI can help the bank,” Marshall told Tech Wire Asia.
“If you don’t have a customer-centric account opening process for example, and you’re asking for lots of data, at multiple stages of the process, then you’re asking for a lot of trouble and AI is not going to make any difference whatsoever,” elaborated Marshall.
The reason data is so critical to using AI at any scale in the financial services space is because that’s a requirement of the use cases currently dominating the industry.
“Most of the use cases in the banking space are machine-learning based. The classics are fraud detection, anti-money laundering, analyzing problem tickets in IT platforms. They’re analyzing patterns, categorizing them, and putting them in buckets to make analyses,” said Marshall.
Obviously, a strong data infrastructure needs to be put in place before patterns can be identified, built into a model, and used to spot deviations from those set patterns.
Although much of the discussion at the event was centered around more mature AI use cases like the ones Marshall highlighted above, there is a case for AI deployments at the fringes of today’s banking ecosystem — in the form of chatbots.
Chatbots, although a very basic AI solution, are a very popular solution among banks of all sizes across the APAC and the globe. They’re also a priority for leaders in many organizations because they can potentially save them about US$7.3 billion by 2023 according to a recent Juniper study.
At the end of the day, however, what’s important to remember is, banks have plenty of options to get started with their digital transformation journey and climb the digital maturity curve — and AI might not be the ideal first solution to look into.
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