Banks adapting to post-COVID-19 world overlook power of data
Banks re-evaluating business models to incorporate new strategies and remote capabilities in a post-COVID-19 world should not overlook the role data and artificial intelligence (AI) play in fortifying customer relationships and better meeting their needs.
The historically risk-adverse banking sector has not aggressively pursued predictive models as a way to boost revenue, a mindset that has cost them market share to encroaching tech companies. According to a March PYMNTS study, banks reported a nearly 70% increase in AI use from a year ago, but that brought the industry use up to only 10%.
The low adoption rate suggests a false sense of relationship security among banks who may feel their accumulated internal data provides sufficient insight into their customers’ behavior. The reality, however, is that they have failed in many cases to detect patterns within those chronologies that could be used to identify relevant products and services for customers.
They also have missed a significant opportunity to leverage non-bank data in the way their tech competitors have. Banks could spot additional patterns in consumer behavior by using social media platforms and other online data to better understand their internal profiles.
Now, with priorities shifted from comfort and growth to stability and survival, creating a holistic customer experience and understanding the financial needs of consumers is even more critical. Use of data and AI will be key to building staying power for banks serving what will likely be a smaller market with fewer assets.
Banks have the advantage of historical perspective, but don’t always see its full potential. More could use their internal data to create predictive models to gain insights into customer thresholds such as risk levels, price sensitivities, or propensity for prepayments. Analysts can use AI to forecast behavior and help build products and services around emerging trends.
By mining debit card data, they could determine where customers spend money and how the current economic shutdown is changing that spending behavior. They could track life stages to determine what kind of loan or account customers might need next, whether for a wedding, college tuition or debt refinancing. They could promote a home renovation loan or use of an existing home equity line of credit to a customer whose mobile banking app geolocation registers as Home Depot.
To compete with personal financial management apps, banks could allow customers to tie their budget to their geolocation, requesting, for example, that $10 is automatically added to a “bar fund” every time their phone indicates they’re at the gym. They could be alerted whether they’ve stayed within their grocery budget (or how much is left) every time they arrive at the supermarket.
Only a few banks have managed to master these analytics, as many are limited by models that fail to account for price elasticity. Tech companies have been able to exploit this weakness by adapting models to changes in consumer attitudes, continuously learning from new data points and extrapolating trends to predict future behavior.
Secondly, banks could spot new patterns by tracking outside data. They could incorporate peer data or use social media or detailed purchase data to detect correlations within their internal sets, relying on AI to process the increased volume.
Post-pandemic, this might mean supporting customers with better financial services.
Europe has already adopted open banking, allowing third parties to access bank financial data to offer more apps and services to customers, and many expect the US to follow suit. With that, and the proliferation of APIs, the days of exclusive access to financial data for banks may be numbered
Large tech companies, of course, have already made major headway mining non-bank data and have begun striking bank territory, most notably with Facebook’s announcement to launch a crypto currency and wallet, Apple’s roll-out of a Goldman Sachs-backed credit card, and Google’s partnership with Citigroup and Stanford Federal Credit Union to offer checking accounts.
Banks can use data to stand out from the competition and fortify their position against evolving tech companies. First, they need a deeper understanding of their customers, not one based on a single event or interaction, but one built on a more complex view of behavior. By looking at an evolution of financial behavior and how it correlates to non-bank life, banks will better understand what motivates customers and spot emerging trends to build new products and services in a dramatically different world.