Artificial Intelligence (AI) is set to transform the finance industry, streamlining processes and improving customer service. Yet, financial institutions are keenly aware of the ethical issues and risks that come with this change. As AI begins to permeate every facet of personal and business banking, Global Finance hosted a Digital Banking and AI Innovation panel in London. Industry leaders gathered to discuss the implications of these new technologies and how to adopt them for the benefit of everyone involved.
The panel was expertly led by Gilly Wright, Global Finance’s Technology and Transaction Banking Editor. The panelists included Hussein Al-Abdulla, Head of Alternative Assets and Marketing at Commercial Bank Qatar (CBQ); Sachin Arora, Head of Strategy for Financial Services at Infosys; Olli Anteroinen, Head of SME Digital for Business Banking at Nordea; Payal Jain, Head of Application Engineering and Platforms at Citi; and Friedman Wang, Head of the Digital Technology Division at CTBC.
Global Finance: What role can AI play in the way financial services are delivered and consumed?
Sachin Arora: To grasp AI’s role and impact, we must first understand how customer experiences are created. Customers typically don’t think about their bank when they wake up. They have an emotional relationship with money. Bad news spreads faster than good, so a positive customer experience in banking often involves protecting the brand and its meaning to customers. I view ‘customer experience’ as the intersection of products, processes, and people. A company might have an excellent product, but if the customer interaction process is flawed, it diminishes the experience. Similarly, a well-functioning customer service process is ineffective if employees aren’t equipped to handle queries.
In this light, AI holds tremendous potential to enhance bank products, automate processes, and empower employees to better serve customers.
Sachin Arora is the Associate Vice President and Head of Strategy for Financial Services in Europe, the Middle East, and Africa at Infosys. In addition to his role as AVP, Sachin leads Mergers & Acquisitions for Infosys’ Global Financial Services business. He is a member of the Executive Committee for Global Financial Services, the largest business unit at Infosys, with over $5 billion in annual revenues. Based in London, UK, Sachin has extensive experience in the banking industry, engaging with regulators and global financial services firms.
Sachin has a proven track record of helping firms with advisory & execution of large-scale transformation and innovation. Operating at the intersection of business and technology, he is passionate about the future of banking in an AI-first era. He is a pragmatist change maker with a belief in the power of collaboration with an open ecosystem of clients, partners, startups, and industry bodies.
Global Finance: Cutting through the hype, what role can AI play in the way financial services are delivered and consumed?
Friedman Wang: In Taiwan, we have more than 12 million customers, but only 3% have their own financial advisors. That means the majority do not have access to our wealth management services, which is a flagship business for us and contributes more than 40% of the total bank’s profit. However, from the perspective of our 1,000 financial advisors, even though each of them has around 400 clients, they are only familiar with around one-third of their customers. If we can leverage AI to roll out hyper-personalization at scale, our wealth management profits would grow significantly.
To date, we have been using an AI algorithm to try to achieve two things: first, to enhance our sales efficiency by better predicting the next products for our markets; and second, to personalize the service for our customers.
To help us achieve these goals, we are using big data so every advisor can better understand each customer, their life stage, and their lifestyle. We can then provide a highly personalized wealth management service.
Friedman Wang, CTBC is responsible for overseeing the development of the bank’s digital technology strategy, implementing innovative business models, delivering digital technology solutions, and managing technology integration and governance.
From 2018 to 2023, he concurrently served as the top manager of the Data R&D Center of CTBC Financial Holdings, promoting to director of the Data and Technology R&D Department in 2020. He enabled the creation of a big data R&D center for CTBC Financial Holdings and implemented a dual strategic approach of AI. These efforts have won numerous global innovation awards from WCIT, Gartner, and IDC.
From 2005 to 2019, he worked in CTBC Bank’s Retail Banking Credit Risk Management Division as Vice President, deploying personal financial risk management systems and operations internationally, including in China, the United States, Canada, Japan, the Philippines, Indonesia, and Thailand.
Global Finance: Turning to SME banking, how is AI helping smaller companies?
Olli Anteroinen: I view AI’s potential for SMEs through the lens of digital services, focusing on delivering excellent customer experiences and business outcomes for this segment across the Nordic countries.
Nordea is using AI to improve the delivery of digital services to SMEs by speeding up time to market. We are using GitHub co-pilot and combining it with our own source code to enhance customer value.
Since 2017, we’ve been using virtual assistants for both staff and customers. By 2020, 80% of our interactions were conducted via chat channels managed by our virtual assistant.
Olli Anteroinen is the Head of SME Digital in Business Banking of Nordea Bank Oyj, the leading financial institution in the Nordics. Olli Anteroinen joined Nordea in 2006 and has worked with Retail (SME) customers and life insurance in various positions, lastly focusing on digital and business development.
He holds a Master of Science degree in Economics and Business Administration (major in Knowledge Management and Information Networks) and Lappeenranta University of Technology School of Business.
Global Finance: What are the next steps with visualization, another emerging area of AI?
Anteroinen: Our next step is to enhance the customer experience by leveraging AI in new concepts within digital banking. Data visualization is one of the ways we can use AI to introduce new ideas within the digital banking services we offer.
For example, we can use visualization to help SME customers manage their cash flow by combining different datasets we have within the bank with customers’ financial data to produce valuable insights. We aim to achieve this by 2025.
Global Finance: How is AI addressing customer needs and expectations?
Hussein Al-Abdulla: CBQ has been working for years to use AI to develop our systems and processes to enhance the customer experience. This effort has been partly driven by Qatar’s demographics: over 55% of our population is under 26, so they prefer mobile banking over visiting branches.
We recognized the need for this customer experience about eight years ago, and today approximately 95% of our customers use the bank’s mobile app.
COVID-19 accelerated the development of our mobile app, as customers relied on it for daily activities. For instance, CBQ developed an app for domestic maids to open accounts through mobile.
This initiative demonstrates our commitment to meeting customer needs, and we anticipate further development in mobile banking in unexplored areas.
Hussein Al-Abdulla, a member of the Executive Management team at Commercial Bank, is EGM, Marketing & Alternative Investments. Having started in retail banking at HSBC in Qatar, Hussein covers several areas for Commercial Bank and is a specialist in retail banking, marketing, strategic planning, digital transformation, and asset management.
Global Finance: Is Generative AI really the answer? AI can be expensive, so how does the cost impact return on investment?
Payal Jain: The good news is AI is becoming more affordable. Generative AI isn’t always the solution, and we will see other AI technologies advance in the future.
Currently, as GenAI becomes more accessible, it lowers the barrier to entry, allowing for broader application. Initially used for routine tasks, it’s now being applied to more complex workflows.
At Citi, we assess GenAI’s ROI by the value it provides, including productivity gains across the bank and among various stakeholder groups, such as engineering, sales, marketing, and operations.
Payal Jain is the Head of Application Engineering & Platforms for Citi, and she is a part of the CTO Engineering & Architecture. Before joining Citi, Payal was a hands-on engineering leader building large-scale software at Google and Salesforce. She is passionate about creating innovative software. Her current focus includes developing the core GenAI building blocks that will enable Citi to leverage Generative AI. She is also a Citi Tech Fellow.
Global Finance: As AI is used more widely, how can we ensure it is used responsibly? Can you discuss hallucinations in Gen AI?
Arora: At Infosys, we collaborate with over 1,000 clients, some of whom have reported AI hallucinations. We advise our clients to view hallucinations not as a bug, but as a feature of large language models. Allow me to elaborate.
The quality of output from large language models depends on their training databases. If these databases have biases related to specific business dimensions, the model will naturally reflect that. The training approach also significantly impacts the accuracy level.
We must strive for consistency, repeatability, predictability, fairness, and bias avoidance. There are techniques and technologies available to handle hallucinations, so it’s crucial to shift our mindset and regard these as features of the AI process.
Jain: I agree that hallucinations are inevitable in building platforms or solutions for enterprise production. Good data is crucial.
Global Finance: What type of training guardrails does Citi have to deal with fragmented data?
Jain: Data fragmentation is a significant challenge, and we’ve been at the forefront of building guardrails. To incorporate GenAI, we must adopt a defensive approach whenever deploying a model or releasing a new use case into production. With each application built, we ensure that the data used is classified appropriately. We aim to protect our most sensitive or restricted data.
We also recognize that data has been a persistent issue. Our priority is to create higher-quality data to unlock more insights and access richer metadata, aiding us in our AI journey.
Global Finance: What’s the role of regulators in the AI journey, and how are they shaping the use of GenAI?
Wang: In Taiwan, the regulator issued the first AI governance guidelines in June 2024, set to take effect by year-end.
The guidelines require banks to design an AI process that prioritizes customers and offers them the right to accept a service and an alternative solution.
Banks are adopting a risk-based approach, classifying AI applications from low to high risk and using various factors to define metrics for clear guidance. We are working on establishing a financial AI standard to create a regulatory framework for all players.
Global Finance: Is collaboration and creating ecosystems the best way to advance AI?
Al-Abdulla: Absolutely, collaboration is essential as many market players offer different capabilities.
In Qatar, I’m pleased that our regulators, particularly the Central Bank, have provided a technology framework for banks to collaborate with FinTech companies.
For instance, we recently partnered with an investment firm to develop a tool allowing many of our customers to place buy and sell orders via a mobile app.
Global Finance: What do you envision as the ‘end game’ for AI? What are your goals?
Anteroinen: Our end goal is to enhance customer satisfaction and leverage business personalization, segmentation, and automation. We aim to create tangible business value while ensuring responsibility and maintaining trust.
Wang: From CTBC’s perspective, we are working to integrate two types of AI to offer safer solutions to our customers.
With GenAI and other technologies advancing rapidly, we plan to introduce virtual banking services by next year, providing affordable services to our customers as an end goal.
Al-Abdulla: I envision social media as a new banking system, similar to WeChat in China, where users can manage everything within the app on a simple platform, once privacy and protection requirements are met. Investment firms are already offering advisory services through social media, which is a comfort zone for many. I anticipate this happening sooner rather than later.
Global Finance: How can AI be used to reimagine experiences and rearchitect businesses?
Arora: At its core, AI and other emerging technologies offer tools that enable businesses to be more effective and relevant to their customers.
In 2004, when Google first went public as a search engine, it was valued at US$27 billion. Few could have predicted its role in democratizing the internet and growing to nearly US$2 trillion in value 20 years later! What does this imply for Open AI or other AI pioneers? Could it become the first US$10 trillion company?
“For me, the real end game is to explore the art of the possible and see how we can reimagine the customer experience.” – Sachin Arora, Infosys
However, achieving this requires re-architecting the operating model. AI engineers must ensure that this tool, which can accelerate business outcomes and customer intimacy, is developed safely and compliantly.
Simultaneously, we all need to refresh our mindsets as technology evolves and we reach inflection points. Use cases and applications will change, and we must all ask ourselves – as individuals and professionals – how do we reinvent our roles as entrepreneurs, employees, and stewards of our organizations?
Global Finance: Thank you all. It’s evident that the financial industry continues to explore AI possibilities responsibly and engage in thoughtful discussions about its future.
/cdn.vox-cdn.com/uploads/chorus_asset/file/24016887/STK093_Google_02.jpg?w=75&resize=75,75&ssl=1 "Google Home Experiments with Access Tiers for All Users in Smart Homes")
