Artificial Intelligence in Banking: More Hype Than Reality

Major consultancies constantly talk about how data and AI will transform banking. With good reason. Effectively leveraged, data and advanced analytics can enhance customer experiences, creating a value proposition consumers appreciate, and expect. Most financial institutions, however, are not using data that way, despite what they say.

Over the past year, the Digital Banking Report has conducted several research studies on the deployment and potential impact of data and artificial intelligence on the banking industry. We have found that the improved use of data and advanced analytics can improve customer experiences, generate better marketing results, streamline deposit and lending operations, increase consumer engagement, support innovation, and be a foundation for digital transformation.

Being a data-driven financial institution is no longer optional (if it ever was). In every industry, winners will be determined by how well data and AI can be used for the benefit of the consumer. Big tech firms such as Google, Apple, Facebook and Amazon (GAFA) are setting the pace, delivering experiences that are improving valuations and providing the foundation for entry into financial services. Fintech firms and non-traditional banking challengers are using data and insights to steal business from legacy banks and credit unions.

From tracking social media engagement to looking at spending patterns and the use of existing financial services, a data-driven approach completely changes organic growth opportunities from cross-selling to providing proactive advice. Instead of being a privacy threat, the intelligent use of data can provide a value proposition that the consumer appreciates and may even pay for (similar to how people pay Amazon for the ‘right to shop’ digitally).

Unfortunately, while there is virtually no question of the benefits of data and AI for the benefit of the consumer, the vast majority of deployment by legacy organizations still focuses on cost reduction and productivity and/or risk management. While these use cases certainly help financial institutions meet quarterly financial goals and protect against losses from fraud, the consumer rarely feels any personal benefit.

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Most Talk of AI by Banking is BS

From a consumer’s perspective, most use of AI for a better experience has been superficial at best. While the industry continues to say that the use of Data and AI is a major trend and is a priority as shown in this year’s Retail Banking Trends and Predictions report, research on use of AI shows that deployment for the benefit of the consumer has lagged the hype by a significant amount.

Except for the largest financial institutions, and some of the smallest, few organizations profess to be adept at advanced targeting, multichannel communications, real-time contextual offers or proactive advice. This is very disappointing given the marketplace realities across industries.

It is clear that banks and credit unions are testing the use of data and AI across businesses, but they are definitely not as bullish or proficient as public announcements would suggest. Where there is an investment in advanced analytics, our research shows that the impact continues to be focused on back-office efficiency, risk avoidance and cost reductions.

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Customer Experience Can’t Be Improved Without AI

Not all AI implementations have been internally-focused. For instance, Bank of America’s AI-powered digital assistant, Erica, has more than ten million users and completed 100 million client requests in the first 18 months since introduction. According to Bank of America, “The app can be configured to a person’s preferences and usage, giving everyone a different home page — similar to the way Amazon and Netflix give every user a different home screen.”

While not near the final potential of the app, the ability to be notified of a potential overdraft, remind a customer of a recurring payment, understand a customer’s spending and saving habits and warn a customer about a duplicate payment is a capability that few banks or credit unions can match.

With hundreds of billions of tweets, ‘likes’ and searches each day, financial institutions have the ability to supplement internal balance and transaction insights to create value for the customer or member. That said, few financial institutions even use the massive data at their disposal internally.

The key is to support intelligent interactions based on this data … in real time. The ability to create these type of engagements has become easier and easier with the creation of new technologies and ways to process data. The cost to do this type of analysis has dropped, even though the availability of talent to create and manage models has become more challenging.

Financial institutions can also create digital-driven products that have AI as part of the foundation. This can be done in-house or in collaboration with fintech or big tech providers using open banking APIs and the cloud. As discussed in the Innovation in Retail Banking report published by the Digital Banking Report (and available for free download), this type of collaboration speeds up the innovation process and supports digital transformation.

It’s Time to Walk the Walk

There is no arguing that organizations must respect the consumer’s desire for security and privacy and that any use of data for internal and challenges can not be considered roadblocks. Financial institutions of all sizes are beginning to focus on how data and insights can benefit consumers directly, because these same consumers are expecting more from their financial institution partner. Banks and credit unions must use current data and insights to:

  • Proactively notify a consumer when their balance may not be enough to cover upcoming disbursements.
  • Allow a customer to verify a potentially fraudulent transaction.
  • Advise a consumer on how to better manage their finances based on real-time insights.
  • Provide third-party offers based on contextual insights from primary and secondary data.
  • Customize digital apps based on individual usage.
  • Implement pricing models based on current and potential product and service use.
  • Deploy insights across the organization to allow each potential touchpoint the same view of the customer.
  • Use data and automation to reduce operational costs and risk.

Using data and analytics to improve the customer experience is not a new concept. In fact, the banking industry has discussed this capability for decades. The difference today is that the consumer understands the potential of using their data for their personalized benefit. It’s time that the banking industry walk the walk as opposed to simply talking the talk.

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