Tool up: can Data Analytics make a difference?

In our ongoing quest to get behind the hype, we consider Data Analytics and how much of a benefit this gives banks, service providers and retailers when it comes to payments. James Wood crunches the numbers…

Recent advances in computing power and more efficient software development mean that some sophisticated services once reserved for large, wealthy corporates are now becoming more attainable, if not exactly going mainstream.

Automation, too, has played role: the widespread use of accounting packages such as Quickbooks and NetSuite testify to the extent technology has enabled smaller businesses to manage their own professional services.

In payments, providers have for some time been enabling access to highly sophisticated data analytics packages for smaller banks and retailers.

Previously reserved for those players large enough to either develop their own software or purchase systems on license, now analytics providers are offering so-called “Data Analytics as a Service”, or DAaaS, to smaller banks and retailers in exchange for a month-to-month or single-service fee.

This is big business: ResearchDive estimates the market for data analytics in payments will be worth around $4.8 billion by 2030, growing at just under 5 percent per year to the end of the decade.

The reason behind this success is that many banks are coming to realise their transaction data is a strategic gold-mine.

“Banks are increasingly seeing consumer transaction data as a strategic gold-mine.”

However, time and budget constraints mean most banks do not keep up with developments – or manage their data effectively. What’s more, current data management tools used by banks are inflexible, and expensive to introduce and maintain.

If managed and interpreted better, customer transaction data could lead to outstanding business performance, including cost/benefit analyses of card programs, more targeted and effective marketing activities, the development of new products and a great understanding of how, when, where and why customers use certain payment products.

Alex Reddish, Managing Director of payments infrastructure provider Tribe, says DAaaS services can provide benefit across the value chain, and are important for payments businesses that want to prepare for a market moving towards Open Finance.

“One of the key considerations when entering payments is complexity. Starting with the number of parties involved in initiating or accepting a transaction, to the unexplainable fee at the end which you get for making one – it’s confusing.

However, ignorance is no longer bliss. We talk a lot about hyper personalisation – we’ve all been to enough conferences where it has been spouted. But DAaaS genuinely brings this to life.

And we’re not just talking about banking apps notifying people on monthly overspend. We’re talking about Open Finance and the ability for financial data to be valuable and useful across multiple industries.”

From marketing to fraud prevention

One of the key uses of payment analytics comes in marketing.

If banks and retailers are able to gather, integrate and process payments data from sources such as cards, mobile wallets and bank transfers, it can lead to serious benefits.

Payments companies across the value chain can access insights into where their revenues come from and trends in how and when people are paying.

European payments solutions provider Nets has developed a suite of data analytics tools that filters and aggregates customer transaction data and analyses it to deliver reports that group and visualise customer behaviours.

Nexi say their solution saves business analysts time by aggregating transaction data and comparing it to customer profiles.

They also claim it can deliver novel analytics through segmentation.

“Business analysts can group transactions by product, customer demographic, time series, location and a host of other options”, says Andrej Anđelić, Account Executive at Nexi.

“Results can be compared against targets for that payment product, customer segment or other criteria, enabling the rapid development of an accurate, effective business strategy.”

Likewise, banks can use analytics in the fight against fraud.

According to a report from the Association of Certified Fraud Examiners’ Organizations (ACFEO) in the US, banks that use proactive data monitoring can reduce their fraud losses by an average of 54% and detect scams in half the time.

GDPR – the big “but”…

While the positives may sound attractive, data gathering and analysis is not without its challenges – not least of which is the increasingly vexed question of consumer privacy.

Across the EU, the UK, Canada, Australia, Japan and increasingly the US, consumers are waking up to the fact that their data can be of as much value to a company as their custom.

As a result, many companies face either an inability to collect data under national regulations, or the accretion of partial data sets from consumers who do not consent to the use of their data.

Without complete data sets, companies can risk drawing the wrong conclusions – that can be expensive when it comes to taking anti-fraud decisions.

Synthetic data – modelling the market

To circumvent such issues, new providers are emerging that provide synthetic data sets to help banks and fintechs model the market, simulating loss events and consumer buying behaviours.

Synthetic data is ‘artificial’ data that maintains the same statistical properties as ‘real’ data, but generated using algorithms.

Whether the aim is to make data available across an organisation or accessible to third-party partners, synthetic data helps fintechs and banks make more accurate decisions while respecting consumer privacy.

In the UK, the FCA is testing the potential role of synthetic data in the way financial services test, design, develop and regulate.

While synthetic data may have its uses, it’s hard to imagine any synthetic data set that can capture the protean nature of the payments market, especially now as new payment types – not to mention new fraud types – are proliferating rapidly.

Obvious benefits, up to a point…

The fact that Data Analytics as a Service is now available to a wider range of players in payments can only be a good thing – in some ways.

It goes without saying that the capacity to assess and analyse existing customer behaviours will always be useful, since it can help to point out areas where service can improve – or where new products are required.

Likewise, if DAaaS points out where recurring fraud risks and losses are happening, that’s great.

As with so many additional services outside the basics of acquiring and processing, however, the payments C-suite should fight shy of seeing DAaaS by itself as a “silver bullet” – either for marketing, fraud prevention or anything else in fact.

In marketing, a wider appreciation of trends and good old-fashioned creativity and effectiveness count for a lot; and when it comes to fraud, there can be few things that work better than KYC which is as robust as possible, and strong customer authentications wherever necessary.

That said, DAaaS should prove a welcome addition to the toolkit for most banks, fintechs and service providers looking to compete both online and in store.

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