How generative AI and BIAN technology standards are shaping the future of banking

30 January 2025

Author

Gemma Godfrey

Board Chair, Non-Executive Director, Post-Exit Entrepreneur

“Banks face disruption from every angle, says Ian Gillard, Senior Executive Vice President of Bangkok Bank. Indeed, over the past few years the banking industry has undergone significant disruption due to technological advancements, changing consumer preferences and regulatory developments. Banks are facing three simultaneous challenges, says IBM Consulting® partner Shanker Ramamurthy: how to grow and differentiate, how to lower the stubbornly high cost/income ratio, and how to manage risk and regulatory exposure.

Meeting these challenges requires multiprong modernization. Gillard and Ramamurthy, both BIAN board members, offered solutions at the 2024 Banking Industry Architecture Network (BIAN) Banking Summit.

One of the biggest challenges for the banking industry is the amount of time and money spent on testing technology. BIAN chairman and former HSBC Group Chief Information Officer (CIO) Steve Van Wyk says that one of the root causes of this is banks “testing the monolithic code base rather than being able to handle it on a component or microservice basis”.

Modernizing the core of a financial organization’s operations may be the key to unlocking innovation, with the digital transformation of the middle- and back-office enabling focus to shift to developing innovative, new solutions and customer-facing enhancement initiatives. In response, IBM consultants are helping clients to implement extreme digitization in those spaces to eliminate complexity and duplication and re-allocate investments toward customers, platforms and ecosystems designed to deliver superior value. Might this move the return on investment for banking modernization programs from the low single digits to nearer 20%?

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Bank modernization in growth markets is happening at speed

Banking modernization in growth markets is happening at a scale unseen in mature markets, with an incredible percentage of transactions conducted through mobile. IBM has worked with clients such as State Bank of India, DBS in Singapore, and Bradesco in Latin America, helping them take advantage of these capabilities, with multi-channel integrations such as open banking, embedded finance and beyond banking platforms.

Using BIAN’s standard framework has accelerated transformation, making technology easier to test and break down into components. As Van Wyk describes it, this is like breaking down a complex construction into individual “Lego brick” components that are simpler to integrate into other systems across not just the bank but the industry.

Similarly, Paolo Sironi Global Research Leader of Banking & Financial Markets for the IBM Institute for Business Value, believes that banking transformation requires “solid but flexible development platforms” to disentangle the “spaghetti-like” bank technology architectures. It’s his position that small to medium enterprise (SME) banking is where many financial institutions and new entrants will be competing the most in the next five years. These institutions will use a combination of digital solutions, ecosystem partner collaborations and emerging technologies such as generative AI to create new business models that better serve this vast client segment important to the global economy.

In Thailand, Bank of Bangkok has been able to leapfrog the PC era and use personal devices instead. Ninety-seven percent of banking is carried out on mobile, customers have never had checks and many don’t have bank cards. ATMs are cardless, and people use them by scanning QR codes with their phones. As a result, the stability of their call centers is even more important; digital services can’t be out-of-action for more than eight hours, in total, all year. This is even more impressive when you realize they must contend with a 10x surge in demand on peak days, with up to 300% more activity around pay day.

The move to real-time payments is not without its challenges. It merges the timing for two discrete processes for transaction confirmation and settlement, having them occur simultaneously in real-time. This has meant money can move with less time to identify fraud and stop money ending up in the wrong hands.

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AI is driving productivity and profitability

The future of computing will include the combination of bits plus neurons and qubits, and the banking industry will use these technologies, including generative AI and quantum computing to reinvent itself for the future, per a presentation at the BIAN conference by Dr. Darío Gil, Senior Vice President and Head of Research at IBM.

IBM itself has seen over USD 3 billion of productivity gains and a 40% savings in its human resources (HR) budget. Employees can answer 80% of associates’ top HR inquiries by using its generative AI platform for enterprise, watsonx™. This example is relevant to the financial services industry given its vast amount of knowledge its workforce is required to have. For clients, the business impact of working with IBM consultants and technology includes a 90% accuracy rate on customer inquiries, 1200 hours of labor saved and 80% lower cost for first drafting of legal documents.

How IBM can help

With software development lifecycles accelerating, IBM is working with clients, including most of the largest financial institutions around the world, on how to use IBM technologies like watsonx and Granite™, inference labs and other capabilities in the marketplace. Generative AI is being integrated into processes to make them more effective and efficient. At the same time, as gen AI accelerates the rate at which code can be created and implemented, the attack surface increases (with more software needing protection in real time) and can quickly become more complex as you build more code across an organization.

Looking ahead, companies continue to grapple with the challenge of how to successfully scale adoption of gen AI. There are many considerations, including governance, data privacy, trust and authenticity, operating model and return on investment. Saket Sinha, Senior Partner within IBM’s global banking and financial markets consulting practice, explained that IBM is working with clients to help with these considerations, find answers to the toughest questions. As well as work collaboratively to remove operational hurdles and pave the way for greater efficiency and innovation.

Expertise and collaboration are crucial to navigating this journey, especially as the next phase of advancement that previously took 15 years is compressed into five. As Ramamurthy says, “in 30 years of consulting with the financial services industry, I have never been more excited by a technology than I have been about the potential of generative AI”. It’s hard not to agree.

Gemma Godfrey is a Board Chair, Non-Executive Director and IBM Partner
 

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