Banks in Singapore are leveraging SGFinDex, a public digital infrastructure, to create more holistic products for consumers.
The availability of aggregate information about their customers is allowing one bank, DBS, to define what “financial inclusion” means in the context of a wealthy, heavily banked city-state.
“In Singapore, ‘underserved’ is about access to advice, not access to banking,” says Evy Wee, managing director and head of financial planning, investment and insurance solutions for the consumer banking group.
DBS and its rivals have offered online versions of banking services for years. The launch in 2020 of SGFinDex, or Singapore Financial Data Exchange, an initiative developed in partnership with the private sector, has turbocharged the bank’s mobile wealth offering. It uses the government’s national identity database (SingPass) to give consumers the ability to consent to having their information shared among member financial institutions.
Seven banks, along with the Singapore Exchange’s depository, and government pensions, housing and tax authorities, may then access that data.
Turbocharged planner
This data pool has given banks a powerful tool to compete against fintechs, including the consumer-facing robo-advisors such as Endowus and StashAway that have garnered assets.
DBS had already introduced a mobile consumer product called NAV Planner in 2020, as an attempt to take its private-banking capabilities, break them down to bite-sized investment sizes, and use digital tools to make these available to consumers.
Then data from SGFinDex became available. This information is sticky, because it works on the basis that a person gives SingPass a one-time consent for everything, and this consent lasts for one year. Even if people want to stop sharing, this gives banks a broad and stable view of a customer.
Insurance need
The SGFinDex information in turn makes for a more powerful financial advisory tool. The next big step, expected to take place in November this year, is its inclusion of insurance data.
“When we launched NAV Planner [in April 2020], we expected people would be most interested in investments,” Wee said. But Covid hit. “Instead customers were asking about protection.”
For DBS that means 2.6 million of its roughly 5 million retail customers (mostly among younger generations) in Singapore have so far participated in NAV Planner to some degree.
Wee says the results are dramatic: in 2021, DBS consumers roughly doubled their exposure to digital investments including mutual funds, to S$2 billion. “Customers guided by NAV Planner fare better than dormant or non-users, and on average have a 50 percent higher AUM, including deposit savings,” Wee said.
This highlights the potential for a bank with access to such an array of data to make advice an actual business. To date, banks in Singapore (and most of Asia) tend to push customers to make transactions because few customers will pay for advice – a situation in which banks’ frontline staff are incentivized to sell expensive products, and which naturally leads to mis-selling.
Scaling advice
Therefore advice has always been limited to relationship managers (RMs) handling wealthy customers in the private bank – and even there, banks end up acting more like brokers, in part because they lack the information about customers to know how to advise them well.
Technology is making access to investment products easier for lower-income people, and it creates the potential for scale – and at scale, advice, be it robo or human, could become a seaworthy business.
But scale means not just lots of customers. It also means lots of data on a lot of products. That’s why DBS’s Wee says she is eager to incorporate insurance into NAV Planner.
First, because DBS has only a few partners for its bancassurance offering, such as Chubb and Manulife. But SGFinDex is expected to include all the big players active in Singapore, such as AIA, Aviva Singlife, NTUC or Prudential.
Second, because the bank can create better products. DBS already has a good idea about customers’ savings. It is learning about investments. But by next year it will be able to see a customer’s insurance profile too. Since Covid, NAV Planner has received customer questions about being under- or over-protected, or whether they should surrender a life insurance policy.
These are important questions in the broader context of financial planning. Just as a mortgage might trigger a younger person to take an interest in their overall financial profile, insurance is a trigger for middle-aged or older customers to need advice about decumulation and whether they are prepared for retirement.
Partner versus in-house tech
DBS has worked with Hong Kong-based fintech Quantifeed to build the nuts and bolts of its internal robo advisor, incorporating house views from its private bank’s investment team to help with portfolio rebalancing and other tasks. The bank needed Quantifeed partly for the fintech’s expertise, but also because Quantifeed has an asset-management license and the consumer bank does not.
To keep the retail offering as easy to use as possible, NAV Planner sticks to simple products. In the local context that means funds or ETFs that are listed on SGX or that are part of the funds on offer at the Central Provident Fund, the government’s pension system.
DBS has built proprietary machine-learning systems to design financial planning around buckets of asset types. This is how the bank competes, given that rivals such as OCBC, UOB and Maybank – as well as Citi, HSBC and Standard Chartered – can access the same data from SGFinDex, with their customers’ consent.
“Risk profiling is the hardest part,” Wee said, noting that consumers can also request time with an RM. “Being able to determine investment preferences is where our AI/ML really kicks in.”
Given a consumer can consent to share their data among all participants in SGFinDex, it is this ability that becomes a bank’s competitive advantage. “It boils down to each institution’s ability to add value in terms of guidance and advice around financial and retirement planning,” Wee said.
Next iterations
It’s also making DBS more attractive as a distributor to fund managers – and, Wee hopes, to insurance companies.
“Data and technology has helped us better gauge an individual’s behavior,” she said. “Distributors are now asking us to co-launch new products because we can get an instant response.”
A final aspect of NAV Planner is what Wee calls its guardrails. If users don’t have enough funds, the app will tell them that “investing can wait”. It is not just a goals-based app, but one that calculates tradeoffs – because it can see liabilities across a user’s accounts. Adding insurance data will be the last big step, although Wee envisages more sophisticated financial products may also be possible.
The biggest local challenge to NAV Planner is that competitors have the same data pool, and they are all using the same SingPass infrastructure. To avoid commoditization, NAV Planner has to offer better advice, which comes down to the ingenuity of the bank’s data analytics.
The long-term challenge is how DBS could export NAV Planner to other markets. It can learn by example and apply it to a market with similar government-identity infrastructure, such as India or Hong Kong. But just as legacy mainframe architecture limits what banks can do with traditional business, the domestic basis of data sharing is a restraint on making digital banking scale internationally.
That’s a problem for banks operating in a market of just 5 million people. But for DBS, it’s a problem that can wait.
