In Asia, market liberalization pushes, coupled with changing customer behaviors and advances in technology, are forcing banks to move away from a product-centric approach to a customer-centric one where data become critical in guaranteeing the value and relevance of products offered to customers.
Across Asia, banks have recognized the need to embrace big data and artificial intelligence (AI) to remain competitive, utilizing data analytics and machine learning (ML) across a broad range of areas from personalized services and risk assessment, to fraud prevention and improving customer onboarding experiences.
During Fintech Fireside Asia’s latest virtual panel discussion, top executives from Vietnamese digital banking startup Timo, Hong Kong virtual bank Mox, Malaysian banking group CIMB and global data-driven personalization solution provider Personetics, shared key insights on the trends they’ve observed in the industry, how they’ve used data in their operations, and discussed some of the challenges they’ve faced in moving towards data-driven banking.
Dorel Blitz, VP Strategy & Business Development, Personetics, said that banks have sat on a treasure trove of data which has remained largely underutilized. His company helps over 80 financial institutions make sense of their data, using AI to analyze customer transactions in real-time to deliver financial management information.
Dorel Blitz, VP Strategy & Business Development, Personetics
“For so many years, banks weren’t really able to leverage their biggest asset and goldmine which is their own customer financial transactional data,” Dorel said. “Where we are coming in as Personetics … [is to help banks] leverage these goldmines of customer day-to-day transactional data from multiple data sources including open banking, cloud accounting software of the small business owners … and help banks move from a reactive approach into finally a smart, proactive financial data-driven approach.”
Personetics has been working with Singapore’s United Overseas Bank (UOB) on a number of projects, but one Dorel’s most excited about revolves around “self-driving finance,” a trend which he believes will be the next evolution of banking.
“It goes beyond just alerts, recommendations, and basic insights, it’s really the next level of leveraging data where banks, very similarly to self-driving cars, will be able to become ‘self-driving finance’ and think and act on behalf of their customers and help customers to automatically save for the future, cut a debt or invest,” Dorel explained. “Customers don’t need to set up goals and thresholds, and time limits and all of that. And we believe that’s the future.
“The next step and battleground for digital banking will be much more cognitive automation … and responsible to our financial lives, and allowing us to sit back and relax.”
Towards data-driven banking
Kanags Surendran, Regional Head, Digital, CIMB, said as the market gets more crowded and competitive with super apps, fintechs and forthcoming licensed digital banks entering the financial space, data will become “the differentiating baseline.”
Using sophisticated tools and AI, banks can analyze customers’ data to offer highly-tailored services at the right time and through the right channel, and raise the bar on personalization to the point where they can anticipate customer needs before the customer is even aware of them.
Kanags Surendran, Regional Head, Digital, CIMB
“It’s about those predictive behaviors, personalization. That’s where the differentiation lies,” Kanags said. “Those are the areas where we are spending a lot of our time on right now.”
Haymans Fung, Chief Customer Officer, Mox, said today’s customers want banking services that are personalized, smart, secure, fun and delivered speedily.
“There’s a rule within the bank that whatever we want our customers to do, it has to be completed within two minutes and with less than five buttons from a user experience (UX) perspective,” she said.
One area the digital bank is leveraging data to speed up and streamline processes is credit card approval.
Haymans Fung, Chief Customer Officer, Mox
“One of the pain points for customers is around sending out the documentation and proofs, and [then getting the application approved]. That’s usually a one week or one and a half [process] at the soonest for traditional banks,” Haymans said. “We really looked into how we could shorten that credit card approval process, and the way we did it was with data.”
Like any other financial institution, Mox looks at a customer’s credit rating provided by the local credit bureau and considers the bank’s own risk appetite. But in addition to these two parameters, it also looks at a customer’s data in terms of their estimated income, as well as behavioral data.
“Because of these extra datapoints, this helps us to make a better decision,” she said. “The end-customer experience so far has been pleasant. From their account, they only need to press three buttons and wait for a maximum of two minutes to get the credit card application approved and without them having to send us additional documents.”
CIMB also relies on data to automate credit decision models, a use case that has allowed the bank to provide credit to those whom have traditionally been excluded from the traditional financial sector.
“We have been able to use that to reach out to more customers and issue credit. This is an underserved market because they are not on the credit/rating bureaus,” said Kanags. “Bringing these underserved into the loan ecosystem, you are increasing the addressable market.”
Behavioral data can also be used to prevent fraud by automatically blocking suspicious transactions, he said. Another way for data to help the bank strengthen its fraud operation is by allowing it to determine a customer’s propensity of being defrauded.
Legacy systems, data integration and tech talent as top challenges
Henry Nguyen, CEO of Timo, said that although his company has been using customer data and insights to improve the platform’s functionality and user experience, including customer onboarding, there was still a long way to go.
Henry Nguyen, CEO of Timo Digital Bank
Timo was the first digital banking offering to launch in Vietnam back in 2015. Since then, the company has already gone through several changes, switching banking partner in 2020 and embracing cloud-native cores.
“The hardest part is to getting access to the right data,” Henry said. “One of the big push that we made was to migrate to Mambu as our core banking platform for greater flexibility and the ability to slice and dice all the data in the way that we needed to. That modern architecture allows you to do that in so much more simple and straightforward ways.
“We all love talking about data, but trying to get the right data at the right time, look at it the right way, and then really … make sure that you put data to work … that’s been kind of the challenge for us because there are tons of data out there.”
For Kanags, legacy core banking systems pose one of the greatest obstacles to banks looking to implement a data-driven strategy.
“The infrastructure and ecosystem of technology has been built over decades, so for you to get a single point of view of the data is not going to be easy,” Kanags said. “When you are a startup you are building that infrastructure around data from day one. In an organization that’s been around for dozens of years, it could be challenging to get the information infrastructure right and collecting from these platforms across those pools of data and doing that in real-time. That’s where the real leap is.”
For Mox, a virtual bank backed by Standard Chartered in partnership with Hong Kong Telecom (HKT) and PCCW, two telecommunications providers, and Trip.com, an online travel agency, one of the biggest challenges has been around system integration and regulation.
“When it comes to integrating partners’ data, it’s hard, because it’s different machines and because [these partners are from] different industries, [which] have different regulations,” Haymans said. “It’s not easy, even though we are partners, and this is one of the biggest challenges we are trying to solve now.”
Human resources is another key challenge banks and other stakeholders across the whole financial industry are facing.
“Today, we have the super apps, the fintechs, the banks… everyone is looking for the same talent, whether that’s digital, agile or DevOps, it’s the same type of folks, so you have a situation where there is a lack of talent across all the market, and industries,” Kanags said.
