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How AI Helps Banks Compete With Digital-First Players

By Laura Crozier

Since the 2008 financial crisis, banks have spent a lot of time and energy on regulatory compliance and cost cutting. Until just recently, as a result of growing regulatory demands, investment in new technology took a back seat, as did innovation.

Now, after a decade of cost reduction, banks are squarely focused on innovation strategies and new technologies that will help them grow and expand. However, in the past 10 years, the competitive environment within the banking industry has become very crowded. Digital-first competitors — like the bigtechs of Amazon, Google and Apple — and fintech companies, such as Square and Ally, have risen to disrupt traditional retail banking business models. With the rise of fintech and increased competition, the pace of innovation has shifted so that it is no longer controlled within the banking industry itself. While bigtechs and fintechs have not made retail banking obsolete by any means, they have certainly reshaped customer demands by providing superior customer service through their ability to deliver personalized experiences in real time.

As banks fight against the new digital competition bigtechs and fintechs bring, they must invest in improving the customer experience whether it is retail or commercial banking. The benchmark for excellence in customer experience is no longer Bank A versus Bank B; it’s whatever the best app is on the customer’s device.

AI: The Key to Better Customer Engagement and Growth

Exceeding customer expectations is the key to customer loyalty and, thereby, growth. In a recent report, Gartner researched how banks intend to drive innovation efforts and found that better customer engagement — together with new products and services — are the top drivers for pursuing innovation within their organization.

Additionally, according to the World Economic Forum/Deloitte, 76 percent of financial service industry chief experience officers agree that artificial intelligence is a top priority because it is critical for differentiation. In retail banking, differentiation begins with client insight. Leveraging AI allows banks to connect and gather all historic and incoming customer data no matter which channel it comes through, meaning physical locations (e.g., ATMs and branches), web channels, digital wallets, point of sale activity and mobile devices. Next, it contextualizes that information in terms of the customer profile that the bank has created based on its relationship with a customer. Once the activity is contextualized, it can be enriched and acted upon — whether that’s through supporting the front line in engaging with customers or digital marketers in analyzing the impact of campaigns.

AI allows banks to have actionable, 360-degree insights into customers’ activities that enable better understanding of customer needs in real time. With AI, banks can deliver on customer expectations more effectively and efficiently, upsell and cross-sell in a personalized fashion and even predict their needs in the future. Ultimately, AI drives growth by providing banks with the insights to ensure their customers are supported at every step of their journey, as well as enabling new products and business models to further engage with customers.

Achieving Personalized, Engaging Customer Experiences With AI

Banks that don’t embrace AI run the risk of losing both existing and potential customers to competition that offers superior personalized experiences. But with multiple channels through which to reach customers and the multiple underlying systems associated with specific banking products, it can be difficult for banks to consolidate real-time insights into customers’ activities, behaviors and preferences.

This is particularly true as banks undertake the curation and maintenance of an ecosystem. A key strategy to maintaining relevance and preserving competitive advantage is recognizing that one organization is likely not capable of doing everything required to deliver a mixture of innovation and services that ultimately provide excellent consumer products and experiences.

While the data is there, the key is knowing how to gather and leverage that information. Oftentimes, the two biggest obstacles banks face are 1) getting the data from across multiple internal systems, and 2) knowing how to analyze and act on that data to enable the delivery of personalized, contextual messages and curated experiences within a matter of milliseconds.

Below are some of the critical aspects to look for when deciding upon an AI-powered customer insight solution that will allow for seamless, omnichannel customer experiences.

  • Interaction with all established customer channels. A bank’s AI solution should be designed to monitor and facilitate real-time interaction across all existing channels and with its ecosystem in an agile, secure and scalable fashion. A bank’s call center personnel, for example, should have full insight into customers’ recent website visits and possibly social media activity. This kind of integrated information sharing is crucial to a customer’s experience — which, in turn, is crucial to a bank’s ability to cultivate long-term customer relationships. Customers don’t want to have to recount history with their bank; they want their bank to know that history and to build on it to foresee their needs.
  • Analysis and optimization tools that facilitate process improvements. Few banks have the required insight to act in real time not only when it comes to providing customer service, but also in terms of monitoring back-end systems. A bank should be able to analyze the underlying business processes, in addition to analyzing a customer’s experience on existing channels. Doing so will allow banks to determine how effectively their existing processes operate — whether there are any bottlenecks — and then model and implement process optimizations across all of their physical, web, digital and mobile channels to serve customers more effectively and provide a great customer experience.
  • Scalability and feature flexibility. As a bank’s customer base and ecosystems grow — as well as all the associated data — an AI solution should be able to keep up and grow with the business instead of requiring new technologies at every stage of customer growth. In addition, any AI platform implemented should not simply be a point solution that only has the capacity to fix one set of problems (i.e., greater customer insights and personalization). Rather, the solution should have the flexibility to address a variety of business challenges that banks may need to address in the future — for example, maintaining compliance and identifying market fraud.

AI is the key to helping banks transition from the old, physical world to a digital one, where they can better compete with digital-first players by becoming digital providers of highly customized customer experiences.

Laura Crozier is global industry director, financial services, at Software AG. For more information, visit www.softwareag.com.

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