There is a legal question over customers’ privacy. Photo: iStock
Arriving at the mechanic to pick up the car from a service, your phone buzzes with a text message. It’s the bank, and it is getting in touch to offer you a loan for the $1500 repair bill you’re about to get.
The bank’s algorithms have calculated an interest rate which, based on your previous borrowing patterns and its view of you as a credit risk, it thinks you may accept.
If you want the loan, you can tap your phone and the money will be wired to the garage in seconds.
The big four banks’ algorithms have calculated an interest rate which, based on your previous borrowing patterns and its view of you as credit risk, it thinks you may accept. Photo: Louise Kennerley
It may sound far-fetched, but transactions like this are probably only a few years away, as banks eye the huge potential to enmesh themselves more deeply in consumers’ lives, and fight off lower-cost competitors.
Thanks to advances in computing power and customers’ embrace of digital finance, banks know more than ever about what their customers are up to: whether it’s browsing the web, shopping online, visiting the mall, or interacting on social media.
Already, they are busily harnessing this vast amount of data to sell products to customers before they ask for them: pushing travel insurance to someone who’s just bought airline tickets, or suggesting a home loan to the newlywed couple. But over the coming years, it is set to get much more tailored to the individual, and far more widespread.
Departed ANZ chief executive Mike Smith says business has never encountered the change and the speed of disruption we see today. Photo: Qilai Shen
As the traditional business of banking faces growing competition from new digital rivals, experts predict banks will increasingly be pushed into targeting customer “experiences” as they seek to remain relevant, and highly profitable.
Inevitably, however, this will involve a tension between what customers regard as the bank being helpful, and when it veers into the territory of ‘Big Brother’.
The fight for relevance
While the big banks’ power and profits are immense, a recurring theme at recent annual general meetings was that digital disruption is occurring at breakneck pace, and they are taking it seriously.
“While business has always had to deal with change it has never had to deal with the incredible pace of change and the speed of disruption we see today,” outgoing chief executive of ANZ Mike Smith told shareholders.
The traditional functions of a bank are pretty simple: taking deposits, arranging payments, and lending money to borrowers. However, there is growing competition in many of these areas from technology-based firms such as peer-to-peer lenders or indeed Apple Pay. Technology also means many of these functions performed by banks are becoming commoditised. They can be done more cheaply, with lower profit margins.
It is against this backdrop that lenders are eyeing off something they have in abundance: financial information about their millions of customers.
The explosion in digital banking has meant the banks’ information about their customers has ballooned. And advances in technology mean they can analyse it in ways that were previously impossible, to ensure they remain relevant.
“Providing just purely a transaction environment – processing your credit card transaction and storing your holdings of money – that’s becoming commoditised,” PwC’s analytics leader, John Studley, says.
“Where the game will be played in the future is in terms of products and services and making sure they’re contextually relevant to customers. And so all the banks are working quite furiously on building their big data capabilities to capture and harness better information about their customers to do that.”
It is a similar mantra from chief executives like Westpac’s Brian Hartzer. He argues the country’s second biggest home lender is not primarily a manufacturer or mortgages, but a company that helps people buy a home.
Geraldine McBride, a National Australia Bank director, has also outlined this type of strategy in response to digital disruption, which she said was “the biggest fear of company boards”.
“Yet banks have the opportunity to become major financial hubs by participating more broadly in their customers’ lives,” she said in a March interview with Fairfax Media.
So, how might banks further spread their tentacles into the economic lives of consumers?
An Accenture report of 2014 suggested they need to be more like online retail giant Amazon, with its ability to recommend products before you’ve even looked for them.
ANZ Bank, for instance, has invested in trying to predict what its customers will want, so that it can ping them with offers.
Customers buying overseas flights with their credit card will be targeted with offers to buy foreign cash or travel insurance.
Further in the future, it could aim to directly contact customers who it thinks are in the market for a credit card, based on their search behaviour on the bank’s website. After identifying the customer, the bank’s systems would determine how best to contact that person – an email or a phone call, say – based on what they’ve said before.
The pictures in that email could be generated to target the individual’s spending habits – so that someone who’s been spending overseas on their cards receives photos of foreign getaways in the promotional material.
ANZ’s managing director of products and marketing, Matt Boss, says this type of personalised marketing is not far away.
“This is where we’re going with our program. To be able to communicate at a one-to-one level, be able to have the content that is relevant to them in the channel they want at the time they want,” he says.
Other domestic banks have similar programs, all the while walking a fine line between being useful and creepy.
Westpac told a conference last year it is making millions of dollars in extra revenue by using big data techniques to make targeted offers to customers, though it would not provide further details for this story.
PwC’s Studley says within a couple of years, it will be commonplace for banks to routinely target people as they approach key milestones that often involve buying financial services, such as entering the workforce, getting married or having kids.
And these offers will become increasingly tailored to the individual, or at least their demographic.
The chief executive of US software firm Nomis Solutions, Frank Rhode, has talked with local banks about programs that can help set interest rates on mortgages, to remove the haggling that takes place between customer and banker.
“What big data technology allows banks to do is actually mine their history of customers, and behaviour, and say you know what, rather than leaving it to the judgment of the front-line banker to come up with an appropriate discount, let’s use the data to guide that front-line banker to present the right offer or a set of offers to the consumer,” he says.
Just like the example of the car mechanic, banks are also bound to look for closer tie-ups with other businesses like retailers. Overseas, this is already occurring.
Bank of America keeps tabs on where customers are shopping the most, and promotes discounts to its customers visiting those stores.
In Japan, Studley points out, phone networks are partnering with banks and fast goods chains to send vouchers to customers who use their phone to pay for food.
All of these moves help banks by putting them in the middle of transactions, allowing them to sell more products to each customer.
The view of many executives is that such cross-selling leads to customers who contribute more revenue, on average, and are less likely to leave. When profit margins are being crunched, it is a tactic that the lenders hope can help preserve the high returns many investors expect.
Big Brother is watching
As well as using your financial data to sell you more products, the rise of “big data” allows the financial sector to more closely scrutinise borrowers.
Assessing whether to lend to someone is a process that hasn’t changed a great deal over the years. It typically involves looking at payments history, how much debt a customer has, and their income.
Now, banks have far more information at their fingertips, which they are likely to use.
A partner at King & Wood Mallesons, Kate Jackson-Maynes, highlights a range of online lenders in the US that are using customers’ online behaviour as part of their loan approval process and in setting interest rates.
Kabbage, a small business lender which has launched in Australia, refers to information from a customer’s eBay, PayPal and Facebook page, she says.
Jackson-Maynes also points out that Facebook recently took out a patent on the idea of using the average credit rating of a customer’s “friends” to determine how creditworthy the borrower may be.
In Australia, however, fewer lenders are using online behaviour in their credit assessments. It is mainly confined to small business lenders such as Kabbage.
“The key reasons why I believe we aren’t seeing more Australian financial institutions and insurers using these new data sources are the ‘big brother’ factor, the limitations of traditional data analytics, and concerns about the application of current laws to such activities,” she says,
Debt collectors are getting in on the act, too, with some reports in the US of debt collection businesses using Facebook not only to locate people, but also harass them.
PwC’s John Studley says looking at non-traditional sources of information about customers, such as social media, is bound to become more common.
“Who are the people [who] you interact with on social media, and if those people have a criminal record or have been caught with a criminal record or have been involved with money laundering, or so on, then that might then be something that impacts your credit assessment when the banks look at you as a prospective customer,” he says.
Equally, it is likely banks will start to use systems that may alert them to public changes in information about a borrower.
If they recently change their LinkedIn status to someone seeking a job, the bank would be aware of this if they then try to borrow money, for instance.
But there is, of course, a limit to how far these boundaries can be pushed. Accenture’s report said banks were the most trusted institutions with customer data – ahead of telecommunications companies or technology giants such as Apple and Google.
At some point, the move to “personalise” interaction with a customer crosses a line and becomes an invasion of privacy.
“Where this can go honestly is as exciting as it is kind of scary,” one banking insider concedes.
So far, the experts say banks are well aware of the trust customers place in them, which makes them reluctant to push the boundaries on privacy.
Sharon Rode, industry practice lead for banking at Capgemini, a consultancy, says there probably isn’t a lot of “cold-canvassing” of customers for this very reason.
“From a privacy perspective if you have a transaction account, you’ve got a fair bit of detail about that customer anyway, and they’re mindful that when they talk to them they’re not seen to overstep the bounds on what they offer,” she says.
There is also a legal question over customers’ privacy.
King & Wood Mallesons’ Jackson-Maynes says that from talking to clients, they are getting more comfortable with the “Big Brother” factor through prominent disclosure about what they are doing.
It’s still unclear how the regulatory landscape may need to change in response to the rise of these new data sources, but she says there are calls for regulations to be “massaged” so it “aligns” with the rise of big data.
In practice, banks will probably need to figure out the difference between what is a “helpful” personalised offer, and what is overstepping the mark. And exactly where this line is will vary for different customers.
Frank Rhode, of Nomis Solutions, argues that consumers will gradually become comfortable with the bank knowing more and more about them, because this will become the norm in other parts of their lives. But banks will need to remain vigilant in not taking things too far.
“The whole notion of big data is that you go down to the individual consumer and you have lots of insight and information, but you also need to take a step back and say “Is this fair, is this something that would pass the red face test?’ ”