Artificial intelligence (AI) plays a transformative role across many industries, and finance is no exception. In 2020, global investment in AI in banking was $12.4 billion; by 2025, that figure is set to reach $20.6 billion. According to Allied Market Research, the global AI in banking market is expected to reach $64 billion by 2030.
AI-driven solutions help personalize products and services to people’s needs, revolutionizing their experience. Eric Bierry, CEO of SBS (ex-Sopra Banking Software), says: “Generative AI is enabling a more human-centric approach for consumers to engage with chatbots and other customer service tools.”
At last year’s Summit, Mohammed Sijelmassi, Chief Technology Officer at Sopra Steria, and Dana Lunberry, Head of Data Strategy at SBS, discussed the technology’s potential – we explore their insights below.
Importance of human-centricity
When it comes to banking, people want their ethical and human values to be taken into account – they prioritize fair and unbiased interactions and systems that understand and react to their behavior. As such, technology, business practices, processes, and services should be developed with a deep understanding of human conduct, emotions, and aspirations.
And yet, when it comes to the world of finance, a 2023 study revealed 74% of customers believe banking isn’t personal enough.
Benefits and challenges of a technology-driven model
With that in mind, one-size-fits-all banking is giving way to a more customized approach. Over time, machine learning and predictive analytics have brought myriad opportunities to the arena, from customer retention to fraud prevention.
And more recently, generative AI has come to the fore. IBM refers to it as “deep-learning models that can generate high-quality text, images, and other content based on the raw data they were trained on”. In terms of banking, benefits include:
- Hyper-personalization of the customer experience (CX)
- “Uncannily human-like” interactions that were missing in the past
- Enhanced process automation, data-driven decision-making, and analytics
Dana Lunberry says: “Human insight and governance will always be a factor, but generative AI allows us to trigger new types of relationships – really, it’s conversational banking we’re going toward.”
A McKinsey forum supports that sentiment, with “two-thirds of senior digital and analytics leaders believing the technology will fundamentally change the way they do business”. Moreover, across banking, “the technology could deliver value equal to an additional $200-$340 billion a year”.
But because the industry is highly regulated, progress is incremental, with use cases carefully considered and tested. That being said, there are meaningful examples of how AI is leveraged by financial institutions.
- Wells Fargo is moving at an aggressive pace with generative AI: Their virtual assistant app launched in 2023 and is predicted to hit 100 million interactions a year.
- Bank of America created a customer service tool named Erica in 2018 and plans to spend $3.8 billion on new technologies in 2024 as they develop generative AI capabilities.
- N26 used open-source software Rasa to build Neon in 2018, a chatbot that handles complex support requests in five languages through their mobile app.
Reaching a human-centric approach
However, successfully leveraging AI to offer human-centric experiences requires trust in the technology. For people – customers and employees – to feel more comfortable and confident, Mohammed Sijelmassi believes banks need to improve data management and quality.
AI must also be embedded seamlessly into systems and processes. As Eric Bierry notes: “Banks are beginning to leverage generative artificial intelligence in their internal operations to create synthetic data in a fraction of the time it would take them to compile the same data manually. Although that efficiency is occurring in the back office, they can then use the data to train AI models they plan to introduce to consumers on the front end.”
Even with those things in place, banks risk non-acceptance and reduced customer loyalty because of AI-related cybersecurity, privacy, and regulatory concerns. People also worry about bias, fairness, errors, inaccurate recommendations, and a loss of control. Ultimately, they need to understand the benefits of AI and why they can trust it.
Potential of AI in banking
With that in mind, the Summit speakers answered frequently asked questions about artificial intelligence and human-centricity in banking. Below is a summary of their insights.
How do you envision the future role of AI?
Dana Lunberry: Technology connects financial services to other aspects of our lives – open banking and finance and beyond. It’s about using intelligence to move past the small ecosystem we have today to a much broader one across industries.
Another area is humanizing AI, as is security. Fraudsters use artificial intelligence, so what more appropriate way to tackle cybercrime than with the same technology? Some predictions say one-third of AI in the future will be used to combat its misuse.
Hopefully, the customer will be shielded from that, leaving them to seamlessly experience financial services and a greater ecosystem beyond, because of AI.
How can banks integrate technologies like generative AI into their existing systems without disrupting current operations and customer relationships?
Mohammed Sijelmassi: They need an architecture that allows them to plug AI capabilities into their existing legacy systems and stitch components together. They also need to leverage the valuable data they sit on – internal and external – and not have a monolithic structure.
Reshaping banking with AI and human-centricity
Artificial intelligence in banking isn’t new, but it is advancing. Indeed, generative AI has the ability to hyper-personalize CX and provide human-like customer support services, but only if the technology works alongside people. On top of that, instilling trust, shifting mindsets, and addressing other concerns are crucial. When that happens, the potential is huge.
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