AI in Asia: Reimagining banking operations through agentic AI
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AI in Asia: Reimagining banking operations through agentic AIDecember 12, 2025 | ReportMultiagentic systems are transforming operations, combining the power of technology, processes, and people to deliver outsized impact for banks in Asia. (39 pages) Agentic AI is expected to have a transformative impact on banking operations over the next decade, and many banking leaders are now seeking clarity on how AI and agentic AI can be harnessed in operations to optimize workflows, delight customers, cut costs, and increase productivity. About the authorsThis report is a collaborative effort by Abhilash Sridharan, Azam Mohammad, David Deninzon, Jan Henrich, Martin Rosendahl, Renny Thomas, Senthil Muthiah, Vinayak HV, and Violet Chung, with Hannes Bergström, Mint Namasondhi, Paras Chhabra, Rasika Ramesh, and Yuvika Motwani, representing views from McKinsey’s Operations Practice. Unlike previous technology waves, however, success with agentic AI and multiagentic systems will require an organization-level mindset shift and a fundamental rewiring of the way work gets done, and by whom.1Seizing the agentic AI advantage, QuantumBlack, AI by McKinsey, June 13, 2025. McKinsey research highlights ten key domains within banking operations that offer significant opportunity for reimagination, especially when approached holistically and through a fleet of nine enhanced agentic AI ‘operations transformers’ (Exhibit 1). These AI agents are reusable across functions, composable across journeys, trainable to institutional knowledge, and, most importantly, scalable to new use cases with minimal effort. Banking operations are ripe for reimagination Against a backdrop of rising customer expectations and a challenging operating environment, three drivers help illustrate AI’s potential in banking operations: AI is expected to disrupt the operations function more than any other lever. With end-to-end operations representing an estimated 60 to 70 percent of a bank’s cost base, based on McKinsey’s research and engagements, transforming operational processes could be an unprecedented value unlock in the financial services sector. In one example, a global bank has used AI and gen AI to streamline its Know Your Customer (KYC) processes by minimizing documentation requirements, enabling a faster, more seamless onboarding experience for customers. Financial services companies are uniquely positioned to absorb the power of AI across customer-facing, inward-facing, and support processes. Recognizing this potential, financial services companies spent $35 billion globally on AI in 2023, with investments projected to reach nearly $100 billion by 2027.2Artificial intelligence in financial services, World Economic Forum, January 2025. Regulators are increasingly open to AI-driven innovation, creating tailwinds for adoption. While regulators across Asia are keenly alert to the potential risks of AI adoption in the highly regulated financial services space, many national regulators are now encouraging banks to innovate with AI.3“Policy statement on responsible application of artificial intelligence in the financial market,” Hong Kong Financial Services and the Treasury Bureau (FSTB), October 28, 2024. By effectively acting as coworkers, today’s multiagentic systems can boost the productivity and efficiency of operational teams and make possible previously unimaginable business process transformations. They also represent a step-up from both predictive AI models and single large language models (LLMs) in their ability to automate complex, multistep workflows, get better over time, and perform tasks within clear guardrails (Exhibit 2). Banks today have an immediate opportunity to harness agentic AI to fundamentally transform their operations. The prize that beckons: breakthrough gains in efficiency and customer experience, and enduring competitive advantage. To get started, leaders need to embrace a mindset shift, from a technology-first approach to a business-first outlook. Ultimately, any undertaking to reimagine banking operations through AI is not simply a technology program; it is a strategic reinvention and rewiring of workflows. A clear vision, disciplined prioritization, and a road map that balances ambition with scalability can help to keep organizations on track. With endless AI-related opportunities to consider, such an approach could help banks remain focused on value and position themselves to capture the full promise of AI-driven operational excellence. To read the full report, download the PDF here.Abhilash Sridharan is a partner in McKinsey’s Mumbai office, where Renny Thomas is a senior partner; Azam Mohammad and Vinayak HV are senior partners in the Singapore office; David Deninzon is a senior partner in the New York office; Jan Henrich is a senior partner in the Tokyo office; Martin Rosendahl is a senior partner in the London office; Senthil Muthiah is a senior partner in the Boston office; Violet Chung is a senior partner in the Hong Kong office; Hannes Bergström is an associate partner in the Melbourne office; Mint Namasondhi is a consultant in the Bangkok office; Paras Chhabra is a consultant in the Gurugram office, where Yuvika Motwani is an associate partner; and Rasika Ramesh is a consultant in the Chennai office. The authors wish to thank AK Giridhar, Avinash Chandra Das, Devansh Sharma, Gaurish Shaw, Harshi Agarwal, Himanshu Agrawal, Jasmine Jain, Nitin Pai, Purna Choudhary, Ravi Teja Gullapalli, Ritesh Agarwal, Sauhard Gupta, Shwaitang Singh, Sokto Sultimov, Sudhakar Kakulavarapu, and Vaishnavi Gopikrishnan for their contributions to this article.Explore a career with usRelated ArticlesInterviewDeploying AI at speed and scale: Talking with ING’s Marnix van StiphoutArticleGen AI in corporate functions: Looking beyond efficiency gainsCase StudyHow a UAE bank transformed to lead with AI and advanced analytics (39 pages) Agentic AI is expected to have a transformative impact on banking operations over the next decade, and many banking leaders are now seeking clarity on how AI and agentic AI can be harnessed in operations to optimize workflows, delight customers, cut costs, and increase productivity. About the authorsThis report is a collaborative effort by Abhilash Sridharan, Azam Mohammad, David Deninzon, Jan Henrich, Martin Rosendahl, Renny Thomas, Senthil Muthiah, Vinayak HV, and Violet Chung, with Hannes Bergström, Mint Namasondhi, Paras Chhabra, Rasika Ramesh, and Yuvika Motwani, representing views from McKinsey’s Operations Practice. Unlike previous technology waves, however, success with agentic AI and multiagentic systems will require an organization-level mindset shift and a fundamental rewiring of the way work gets done, and by whom.1Seizing the agentic AI advantage, QuantumBlack, AI by McKinsey, June 13, 2025. McKinsey research highlights ten key domains within banking operations that offer significant opportunity for reimagination, especially when approached holistically and through a fleet of nine enhanced agentic AI ‘operations transformers’ (Exhibit 1). These AI agents are reusable across functions, composable across journeys, trainable to institutional knowledge, and, most importantly, scalable to new use cases with minimal effort. Banking operations are ripe for reimagination Against a backdrop of rising customer expectations and a challenging operating environment, three drivers help illustrate AI’s potential in banking operations: AI is expected to disrupt the operations function more than any other lever. With end-to-end operations representing an estimated 60 to 70 percent of a bank’s cost base, based on McKinsey’s research and engagements, transforming operational processes could be an unprecedented value unlock in the financial services sector. In one example, a global bank has used AI and gen AI to streamline its Know Your Customer (KYC) processes by minimizing documentation requirements, enabling a faster, more seamless onboarding experience for customers. Financial services companies are uniquely positioned to absorb the power of AI across customer-facing, inward-facing, and support processes. Recognizing this potential, financial services companies spent $35 billion globally on AI in 2023, with investments projected to reach nearly $100 billion by 2027.2Artificial intelligence in financial services, World Economic Forum, January 2025. Regulators are increasingly open to AI-driven innovation, creating tailwinds for adoption. While regulators across Asia are keenly alert to the potential risks of AI adoption in the highly regulated financial services space, many national regulators are now encouraging banks to innovate with AI.3“Policy statement on responsible application of artificial intelligence in the financial market,” Hong Kong Financial Services and the Treasury Bureau (FSTB), October 28, 2024. By effectively acting as coworkers, today’s multiagentic systems can boost the productivity and efficiency of operational teams and make possible previously unimaginable business process transformations. They also represent a step-up from both predictive AI models and single large language models (LLMs) in their ability to automate complex, multistep workflows, get better over time, and perform tasks within clear guardrails (Exhibit 2). Banks today have an immediate opportunity to harness agentic AI to fundamentally transform their operations. The prize that beckons: breakthrough gains in efficiency and customer experience, and enduring competitive advantage. To get started, leaders need to embrace a mindset shift, from a technology-first approach to a business-first outlook. Ultimately, any undertaking to reimagine banking operations through AI is not simply a technology program; it is a strategic reinvention and rewiring of workflows. A clear vision, disciplined prioritization, and a road map that balances ambition with scalability can help to keep organizations on track. With endless AI-related opportunities to consider, such an approach could help banks remain focused on value and position themselves to capture the full promise of AI-driven operational excellence. To read the full report, download the PDF here.Abhilash Sridharan is a partner in McKinsey’s Mumbai office, where Renny Thomas is a senior partner; Azam Mohammad and Vinayak HV are senior partners in the Singapore office; David Deninzon is a senior partner in the New York office; Jan Henrich is a senior partner in the Tokyo office; Martin Rosendahl is a senior partner in the London office; Senthil Muthiah is a senior partner in the Boston office; Violet Chung is a senior partner in the Hong Kong office; Hannes Bergström is an associate partner in the Melbourne office; Mint Namasondhi is a consultant in the Bangkok office; Paras Chhabra is a consultant in the Gurugram office, where Yuvika Motwani is an associate partner; and Rasika Ramesh is a consultant in the Chennai office. The authors wish to thank AK Giridhar, Avinash Chandra Das, Devansh Sharma, Gaurish Shaw, Harshi Agarwal, Himanshu Agrawal, Jasmine Jain, Nitin Pai, Purna Choudhary, Ravi Teja Gullapalli, Ritesh Agarwal, Sauhard Gupta, Shwaitang Singh, Sokto Sultimov, Sudhakar Kakulavarapu, and Vaishnavi Gopikrishnan for their contributions to this article.Explore a career with us