From Automation to Augmentation – AI In Finance Awards 2025

Traditional artificial intelligence, including machine learning and statistical modeling, is nothing new to financial institutions. AI has long been instrumental in data analysis, trend forecasting, automation, risk management, and enhancement of customer service. At the same time, however, traditional AI was paving the way for the emergence of a more revolutionary tool: generative AI (GenAI).

GenAI is rapidly transforming and accelerating AI’s integration and impact within the finance sector, leading to rapid adoption and influence. Due to this profound shift, Global Finance has chosen to recognize financial institutions that are moving beyond mere task automation to truly augment human capabilities, enabling hyper-personalization, proactive risk management, and new value propositions within a rapidly evolving digital landscape.

OpenAI’s release of ChatGPT in November 2022 was the start of public awareness and mass usage of AI. But banks have largely taken a risk-based and governance-first approach, aiming to ensure that harnessing the benefits of Gen AI does not jeopardize responsible, secure, and ethical deployment that maintains public trust and financial stability.

At Singapore’s DBS Bank, consideration of any AI initiative starts with three questions: 1)“Can we use it?”: ensuring legal and regulatory compliance; 2) “Should we use it?”: evaluating the ethical implications through the bank’s PURE Framework for Data Ethics; and 3) “How should we use it?”: prioritizing fairness, transparency, explainability, and accountability in implementation.

“We believe that by balancing innovation with a strong ethical compass, we can harness the power of AI to enhance our services and benefit our customers and employees,” says Nimish Panchmatia, chief data and transformation officer at DBS. While DBS is enthusiastic about exploring GenAI’s transformative potential, he adds, “We understand that responsible innovation is paramount. Our approach is guided by our core values and a robust Responsible Data Use framework.”

Another challenge for banks, according to Andy Schmidt, vice president and global industry lead for banking at CGI, a multinational IT and business consulting firm, is picking a use case that goes beyond what’s already done through Robotic Process Automation and simple automation. While this might seem negative, implying a lack of innovation, Schmidt notes that fintechs are using existing knowledge as a training ground to streamline actions. This approach creates space for true innovation. 

The industry also struggles to calculate the ROI of speeding up existing projects, making room for innovation even harder. Schmidt recently asked a top-tier US bank about the ROI of their AI work. Their response: “We don’t know. We know it’s better. We know it’s smoother. But we can’t truly calculate the ROI.” Schmidt believes that if even large banks struggle with ROI on improvements, securing funding for “it-just-seems-better” projects, especially experimental ones, will be challenging.

That said, AI is poised to revolutionize banks, transforming them from transactional entities into intelligent, integrated, and proactive financial partners.

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