Becoming a Better Bank Through Payment Data Aggregation

Payments Leader

Posted on December 29, 2016

 

How to exploit the goldmine of data and transaction patterns under our noses

Every financial institution sits on a treasure-trove of information, but what are they doing with it? Back-office servers maintain flawless records on all customer transactions and represent an impeccable source for consumer behavioral analysis. If only this vast store of intelligence could be thoroughly analyzed to improve services and products or, even better, packaged up to generate revenue.

The Gatekeeper Dilemma

Payment systems across the globe record every single transaction in exquisite detail. And, of course, holding private data securely as the system of record is a core capability for financial systems. Instead of lying dormant, transactional data could be utilized to inform strategy, improve product services and fine tune operational procedures.

Restrictions on data usage are well founded, but they can be inconsistent. Banks could certainly benefit from selling some data, but they’re limited in how they can do so. In many cases, even ethical uses of benefit to the customer are prohibited. This results in many banks stipulating a total lockdown of data – some even going so far as to outlaw any data derived from their customers’ transactions.

Understandably, banks need to protect their customers’ sensitive, private data from being used for nefarious purposes, but are the blocks too stringent? Nobody is suggesting releasing all transaction histories along with names and account numbers, but there could be many benefits from analyzing large numbers of anonymized transactions to discern patterns and trends across a range of demographics.

Anonymize and Monetize

There is a growing appetite for far-reaching, detailed data on consumer spending, and banks are ideally placed to provide it. These meta-analyses show patterns, trends, preferences, peaks and values that can be extremely useful – the attributes surrounding the transactions (when, where, how often, why, etc.) are more valuable than the individual payment for predicting mass behavior; In many ways, the individual transactions are irrelevant.

Financial institutions could learn a lot from their customers’ product usage patterns, but many are interested in going further – monetizing the process and reselling prepackaged insights to external parties. In both cases, there is a need for the financial industry and regulators to restart the conversation on customer information usage with a view to adjusting data protection rules and norms. A broad industry-wide consensus is needed to unlock the full potential of the data stores within all banks.

On a basic level, more intelligence could be gathered on the frequency of use of different payment options linked to transaction sizes, volumes, repetition, type of spend (retail, transport, entertainment, etc.), and peaks and troughs. Cross-reference this to pertinent demographic groups across different channels, and banks are presented with a way to truly understand a customer, using information sourced from real spending patterns, not just self-identified preferences. Imagine knowing how consumers really spend, how a prepaid user differs from a credit user, what the true profitability is per product, and how you should focus to evolve.

A Wellspring of Value

Information may equate to power, but more importantly, intelligent data analysis provides financial institutions with valuable insights into becoming better service providers. Behavioral analysis is the best tool for demonstrating how, when and where people spend; it outperforms any preferred client sector, social status group or age range. The information results in improved service through more precisely targeted product propositions that better match the customer segment’s spending.

With more uniform and less restrictive customer data analysis, banks could benchmark themselves against their peers. Comparisons could be made between different product silos in order to identify points for improvement. In the payments industry, both processors and banks could use the data in ethical and productive ways, such as adjusting behavior in order to better serve the end customer based on their needs, and reducing fraud by spotting questionable usage patterns early.

Multiple industries are interested in retail market behavior, making information even more valuable. For instance, hedge funds need to be informed on individual retailers and how customers spend at the outlets – ideally with historical comparison.

The Data Market

Like it or not, our private data is a salable commodity that has created a very new market for exchange. Many organizations such as Google, Apple, Facebook and WhatsApp happily sell customer information and behavioral patterns. In many cases, the selling of collected customer information could be seen as their primary business model. Financial information maintained within banking systems may be lagging behind these other industries.

Data protection legislation must evolve for financial institutions to catch up. However, even if the regulations change, very few banks are big enough to make a difference alone, and many outsource their processing, leaving them with less data still. Such payment processors are ideally placed to report to banks on their own performance. More interestingly, large-scale processors can provide a bigger picture across thousands of banks – but only if banks and regulators derestrict data protection and usage rules. Payment aggregators can effectively anonymize huge blocks of private customer data in order to provide valuable insight that will empirically inform strategy and daily operations.

It is time to look again at confidential data. And the payment industry needs to focus on this now, as there will be big opportunities to those that are open to getting there first.

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Payments Leader

Payments Leader from FIS provides insights on credit, loyalty, fraud and emerging payments strategies through blog posts from our industry experienced authors.