Artificial intelligence(AI) is reshaping banking operations, but its rapid adoption is revealing critical vulnerabilities in governance, security and fairness.

TAB Global explored transformative trends shaping the global financial services industry, highlighting AI’s growing role. AI adoption spans the banking value chain, enhancing chatbots, automating loan approvals, improving fraud detection and refining risk modelling.

Institutions like Emirates NBD and JPMorgan Chase are integrating AI into their core operations to improve decision-making and risk management.Meanwhile, banks are partnering with fintechs to provide seamless financial experiences beyond traditional banking. Super-apps like Alipay and Grab are embedding financial services within e-commerce and social platforms, creating new revenue opportunities.

AI-driven credit risk models are transforming small and medium-sized enterprise (SME) lending by making it faster and more inclusive. Institutions like WeBank are using AI to provide real-time, personalised credit solutions, significantly reducing loan processing times.

The role of AI in hyper-personalisation is expanding. Banks such as TPBank and OCBC use AI-powered financial planning tools to provide real-time, personalised advice, enhancing customer engagement and retention.

In international payments, AI improves fraud detection and streamlines compliance. Financial platforms like Revolut and Wise optimise cross-border transactions, reducing fees and processing times.

AI is also being used to assess environmental, social and governance (ESG) risks, optimise sustainable investment portfolios and improve green lending. Standard Chartered and CTBC, for instance, have integrated AI-driven ESG risk models into their investment strategies to align with global sustainability goals.

As AI continues to reshape financial services,institutions must embrace innovation while addressing emerging challenges like AI ethics, transparency and regulatory compliance.

Financial institutions face obstacles in AI adoption

AI adoption in banking and financial services is advancing rapidly but it comes with significant challenges, from regulatory concerns to evolving customer expectations. Financial institutions must navigate these obstacles to fully realise AI’s potential.

Fraudsters are using AI to execute highly sophisticated cyberattacks, including deepfake fraud and AI-powered identity theft, pushing banks to continuously enhance AI-driven fraud detection models. JPMorgan Chase and Standard Chartered are leveraging AI-powered cybersecurity solutions to detect fraud anomalies in real time.

As AI plays a greater role in financial decision-making, banks face increasing regulatory scrutiny over bias, transparency and fairness. Unified AI governance frameworks are emerging to ensure explainability and ethical AI use in credit scoring and loan approvals. The European Union’s AI Act and Singapore’s FEAT principles are shaping AI governance standards in financial institutions.

Traditional banks that fail to innovate risk becoming backend service providers, as fintechs and technology giants dominate customer-facing services. Big tech companies like Apple and Google are expanding financial offerings, challenging banks to provide seamless and innovative AI-driven services.

Fintechs such as Revolut and Alipay are integrating AI-driven financial planning tools to enhance customer engagement. AI is enabling fully automated transactions embedded in customer experiences, such as AI-driven payments and voice-first banking. While this improves convenience, it risks reducing customer financial awareness and involvement in decision-making.

Some banks, like OCBC, use AI-driven nudges to educate customers on spending habits while automating payments. AI models require high-quality, structured data, which remains a challenge for many banks with legacy systems. Institutions must invest in data standardisation and AI infrastructure to unlock AI’s full potential.

Banks like WeBank and Ping An Bank have successfully implemented AI-native architectures to improve data utilisation. AI is also reshaping customer engagement from traditional relationship management to AI-driven hyper-personalisation. However, financial institutions must balance automation with human interaction to maintain trust and customer loyalty.

China Merchants Bank, for example has introduced AI-powered virtual advisors for high-net-worth clients while maintaining human relationship managers.

These challenges highlight the complexities of AI adoption in banking. Institutions must develop a balanced AI strategy that enhances efficiency and personalisation while ensuring compliance, security and customer engagement.

The benchmarking programme analyses hundreds of financial institutions globally each year, revealing clear patterns in how AI and digital transformation have progressed across the retail banking and digital finance landscape.

In 2025, submissions for digital transformation and AI adoption have surged, particularly from digital banks and financial platforms in Southeast Asia, Latin America and the Middle East, amid intensifying competition.

Digital-first players like Nubank and Tinkoff Bank have consistently ranked high due to aggressive expansion and AI-led personalisation. AI Adoption is expanding across banking functions, embedding AI across customer-facing and revenue-generating areas. In marketing and sales, AI-powered propensity models, intelligent campaigns and churn prediction have become mainstream.

Customer service increasingly relies on conversational AI, voice-first banking and emotional AI to enhance interactions. AI-driven financial planning and advisory tools now provide personalised advice, life event predictions and AI-assisted negotiations.

Emirates NBD and JPMorgan Chase have deployed AI chatbots and predictive analytics to personalise banking experiences. Beyond optimising services, AI is driving product innovation. Some platforms have deployed AI-powered bots that negotiate pricing and product features on behalf of clients. Collaborative product development, integrating customer feedback with AI-powered market analysis is refining product offerings.

Standard Chartered and Revolut for instance, leverage AI-driven personalisation to tailor financial products to individual needs.

AI adoption differs across financial categories. Financial platforms lead in AI adoption, leveraging data scale and ecosystem integrations. Digital banks focus on efficiency and personalisation, optimising lending and customer service. Retail banks are catching up, primarily using AI for risk management, fraud detection and regulatory compliance.

Alipay dominates financial platforms, leveraging AI-powered risk assessment, while WeBank leads in digital banking AI adoption.

Overall, 2025 marks a shift from early-stage AI experimentation to mature, large-scale AI adoption. Financial institutions that effectively harness AI will continue to lead in innovation and customer engagement.

Financial platforms lead in AI adoption

Theanalysis of AI adoption across retail banks, digital banks and financial platforms provides critical insights into the financial sector’s evolution. The AI adoption score is a composite measure based on automation, data analytics, customer engagement capabilities, risk management integration and overall digital transformation strategies.

Financial platforms like Alipay and WeChat Pay lead in AI adoption leveraging their scale, extensive customer data and embedded finance capabilities. These platforms offer hyper-personalised services, AI-driven credit underwriting and real-time predictive analytics.

AI-driven fraud detection and compliance automation have significantly reduced transaction risks, making financial platforms dominant players in digital finance.

Digital banks are rapidly advancing AI capabilities, particularly in credit risk assessment, customer service and personalised banking solutions.

Many digital banks have integrated AI-powered advisory services, robo-advisors and predictive analytics to enhance customer interactions. Nubank for instance, uses AI-driven chatbots and deep-learning-based financial planning tools to provide hyper-personalised services. AI is also optimising loan approvals and credit underwriting, allowing digital banks to approve loans within minutes.

Traditional retail banks are accelerating AI adoption, integrating it into fraud detection, risk management and compliance automation. While AI-powered personalisation is still evolving, major banks are focusing on AI-driven credit scoring, digital lending and AI-enhanced customer service. Banks like JP Morgan Chase and Emirates NBD have successfully deployed AI in predictive analytics for credit risk, improving loan underwriting accuracy​.

AI adoption is evaluated across five key dimensions. In customer experience, AI chatbots, sentiment analysis and predictive engagement enhance interactions. Operational efficiency is driven by AI-powered automation, robotic process automation (RPA) and workflow optimisation. Product innovation leverages AI for lending, investment advisory and hyper-personalisation. Risk management benefits from AI-driven fraud detection, cybersecurity enhancements and predictive risk modelling. Regulatory compliance is strengthened through AI-based anti-money laundering (AML), know-your-customer (KYC) and reporting automation.

Financial platforms lead in AI adoption, while digital banks are making rapid advancements. Traditional retail banks, though initially lagging, are accelerating their AI transformation to remain competitive. The next wave of AI innovation will likely involve deeper integrations of generative AI (GenAI) and real-time decision-making capabilities.

AI adoption is transforming banking across multiple functions, from customer personalisation to risk management.

Outstanding institutions that have successfully embedded AI in their operations:  

AI-powered personalisation in retail banking: OCBC has been recognised for the Best Personalisation Initiative in Asia Pacific, leveraging AI-driven analytics to deliver tailored financial recommendations based on real-time behavioural insights. Its AI-powered personalisation engine generates a unique financial offer daily per customer, enhancing relevance and engagement. This initiative has significantly increased customer engagement and conversion rates, balancing hyper-personalisation with strict privacy and compliance standards.

AI and smart contracts in digital lending: China Merchants Bank leads the way in retail digital currency integration by embedding AI and smart contracts into its e-RMB lending ecosystem. AI automates the digital loan disbursement, enabling instant approvals without human intervention. Smart contracts also play a role in post-loan monitoring and fraud prevention, setting new industry benchmarks for risk management.

AI-driven social banking for financial inclusion: TPBank has redefined social banking by integrating AI-powered conversational banking into widely used messaging apps. Through ChatPay, customers can open accounts, perform transactions and apply for credit using a chatbot-driven interface. The initiative enhances financial inclusion, particularly for younger and underserved customers who prefer mobile-first interactions.

AI for enhanced digital onboarding and customer experience: ICBC has revolutionised digital onboarding with an AI Custom Card initiative, allowing customers to personalise debit cards with real-time AI-driven image background removal and facial recognition. Seamless integration with WeChat authentication enhances security while providing a frictionless customer onboarding journey, significantly reducing processing times.

These examples highlight AI’s role as a core driver of innovation, efficiency and customer engagement. Financial institutions that integrate AI effectively are seeing tangible benefits in customer acquisition, operational efficiency and overall business performance.

World’s best retail banks in 2025

The ranking of the world's top retail banks in 2025 is based on a comprehensive evaluation of multiple performance dimensions, including financial performance, customer base, digital capabilities and operational efficiency. These banks have demonstrated strong resilience, profitability and innovation in retail banking.

Top three retail banks in 2025:

JPMorgan Chase remains the largest retail revenue generator worldwide, with retail revenue growing 28% to $70.1 billion in 2023. Its consumer banking division serves over 80 million customers and six million small businesses. With 76% of customers digitally active, JPMorgan Chase has maintained its leadership position by enhancing customer engagement and digital transformation.

Emirates NBD achieved a pre-tax return on assets (ROA) of 5.6%, the highest among leading retail banks. The bank's aggressive digital strategy, including 94% digital customer onboarding and 98% automated transactions, has significantly enhanced efficiency and customer experience.

Standard Chartered Hong Kong strengthened its retail banking segment with a focus on digital-first banking. The bank saw an increase in non-interest income to 31% of total retail income, driven by digital transformation initiatives like myWealth, which provides AI-driven investment insights.

Other banks that made it to the top 10 of the ranking:

Commonwealth Bank of Australia showed strong performance in mortgage lending and digital banking.

CaixaBank led retail banks in Spain with a strong digital presence.

Bank of China (Hong Kong) is a dominant player in the Greater China region while CTBC Bank has strong customer engagement and cross-border banking in Taiwan.

HSBC has expanded its wealth and retail banking services in Asia.

United Overseas Bank (UOB) has a high digital adoption rate in Southeast Asia; and First National Bank is a leader in financial inclusion and mobile banking.

These institutions have excelled in retail banking, showcasing their ability to balance financial growth with customer-centric innovation, setting them apart in a competitive market.

World’s leading digital banks in 2025

The 2025 ranking of the world’s top digital banks is based on a comprehensive evaluation of their financial performance, digital capabilities, customer engagement and business scale. These top banks have demonstrated exceptional growth, profitability and resilience in the evolving financial landscape.

Top 10 digital banks in 2025 by performance, profitability and digital adoption:

Nubank rose from fifth in 2024 to first place in 2025, reflecting its remarkable financial turnaround and customer growth. It reported an 85% revenue surge in fiscal year (FY) 2023, supported by a 119% rise in net interest income and a 28% increase in fee and commission income. Nubank’s cost-to-income ratio (CIR) significantly improved from 66% in FY2022 to 36% in FY2023. Despite increasing non-performing loans, the bank effectively managed credit risks, achieving a 10.2% risk-adjusted net interest margin.

ING is the largest digital bank by assets.It has maintained its leadership in Europe with AI-powered financial planning tools.

WeBank is the world’s largest digital bank by customers.It has over 399 million customers, adding approximately 3.2 million new customers per month in 2023.The bank reported a CIR of 32% and a pre-tax ROE of 30%, showcasing its robust profitability and efficiency. WeBank continues to focus on AI-driven lending for SMEs, using advanced risk assessment models.

Tinkoff Bank is a leader in digital wealth management.It has evolved into a full-fledged digital financial services provider, integrating AI into wealth management and retail banking. It maintains high margins due to its strong credit card and investment platforms.

KakaoBank isSouth Korea’s top digital bank. It has successfully scaled its mobile-first banking model, focusing on lending and payments.

Ally Bank, North America’s best-performing digital bank. Specialising in auto loans and retail banking, it continues to expand its AI-driven financial services.

ING, one of the first digital banks has maintained its leadership in Germany with AI-powered financial planning tools.

MyBank is a key player in SME lending. It leverages AI-driven risk modelling to serve small businesses and rural enterprises.

Toss Bank has a rapidly growing customer base. It has gained market share with AI-powered credit assessments.

Su Merchants Bank is expanding its digital financial services. It focuses on integrating AI into digital lending and asset management.

These top 10 digital banks have an average pre-tax ROE of 22% and a CIR of 40%, highlighting their ability to sustain strong profitability and operational efficiency.

World’s leading financial platforms in 2025

In the World’s Best Digital Banks and Financial Platforms Rankings, the leading financial platforms were assessed based on multiple performance dimensions, including customer reach, engagement, financial performance, ecosystem strength and strategic vision.

Top 10 financial platforms for 2025:

Alipay, the world's largest financial platform, leverages its vast ecosystem and seamless integration with retail and payments in China.

Revolut, a rapidly growing European financial platform excels in global reach, user engagement and product innovation.

WeChat is a dominant force in China, embedding financial services into everyday transactions through mini-programmes.

Apple Pay is a global leader in digital payments with a strong user base and deep integration into Apple’s ecosystem.

PayPal, a long-standing giant in global digital payments is continuing to expand into new financial services.

Mercado Pago, Latin America’s leading financial platform offers digital wallets, lending, and merchant services.

Wise specialises in cross-border payments, transforming the way individuals and businesses move money globally.

GCash, a dominant financial platform in the Philippines brings mobile banking to millions of underserved consumers.

M-Pesa, a pioneer in mobile money is driving financial inclusion across Africa.

DANA, a fast-growing digital financial platform in Indonesia, provides mobile payments, lending and investment services​.

These platforms represent the evolution of financial ecosystems, integrating payments, banking, lending and investments into seamless digital experiences. Notably, half of the top 20 financial platforms primarily serve the Asian market, underscoring the region's leadership in digital finance.

These platforms will continue leveraging AI, machine learning (ML) and predictive analytics to enhance hyper-personalisation, fraud detection and secure transactions, while expanding financial services and access to underserved populations.

AI widens financial inclusion and enhances risk management in SME banking

SME banking has been a critical area of focus in TAB Global’s research, particularly as financial institutions continue to expand their digital capabilities and improve financial inclusion for small businesses. The benchmarking programme highlights key trends in SME banking and how AI is transforming the landscape.

AI-powered credit assessment: One of the biggest challenges in SME banking has been the lack of financial data for traditional credit scoring. AI is now helping banks assess SME creditworthiness through alternative data sources, such as transaction histories, cash flow patterns and supplier relationships. For example, WeBank in China uses AI-driven credit models that enable instant loan approvals for SMEs without requiring traditional collateral.

Lifecycle support and financial inclusion: IBK (Industrial Bank of Korea) has pioneered a lifecycle-based SME banking approach that provides financial and advisory support at every stage of an SME’s growth. This includes AI-driven succession planning and merger and acquisition (M&A) support, ensuring business continuity for SMEs that struggle with generational transitions.

Sector-specific financing solutions: AI is allowing banks to offer more tailored SME financing solutions.

Empowering women-led businesses: Many banks are using AI-driven risk profiling to support women-led enterprises, which have historically faced financing challenges. AI ensures a more objective risk evaluation, allowing for greater financial inclusion.

Streamlining approvals and onboarding:  AI-driven automation is reducing processing times for SME loans. First Bank of Nigeria, for instance, has implemented an AI-powered credit approval process, significantly cutting down the time required for SMEs to access funding.

Cross-border trade facilitation: AI is also helping SMEs navigate cross-border transactions. AI-driven fraud detection and compliance solutions are enabling small businesses to expand internationally with greater ease.

SME banking is evolving rapidly, and financial institutions that effectively leverage AI to enhance SME banking services are seeing significant competitive advantages.

AI transforms client engagement in wealth management

Wealth management is undergoing a profound transformation, driven by AI, digital advisory tools and the changing expectations of affluent clients. Submissions from the benchmarking programmes highlight several key trends shaping the future of the industry:

Rapid growth of affluent wealth segments: The strongest growth in wealth management is being observed in China, India, and Southeast Asia. Financial institutions in these regions are expanding coverage and adopting AI-powered solutions to meet the needs of affluent and high-net-worth individuals.

Hybrid human-robo advisory models becoming the norm: AI-driven wealth advisory is no longer just an experiment. The shift toward hybrid models, where AI supports human advisors, is accelerating. Banks like OCBC and Cathay United Bank have successfully integrated AI into their digital wealth platforms, offering real-time, personalised financial planning and portfolio recommendations.

Intensifying competition between traditional banks and digital-first platforms: The entry of digital-first players into wealth management is reshaping competition. Financial institutions are leveraging AI-powered insights and automation to provide hyper-personalised investment solutions. This is evident in ICBC’s AI-driven wealth management ecosystem, which integrates market intelligence, customer engagement and community-driven insights.

AI-powered portfolio recommendations and risk profiling: Predictive analytics is playing a growing role in wealth management. AI is helping banks assess client risk profiles more accurately and deliver tailored investment options. Bank of China (Hong Kong)’s AI-powered RM Chat platform is an example of how institutions are using AI to enhance advisory experiences and engagement.

Predictive analytics for client churn prevention and cross-sell opportunities:  Banks are increasingly using AI to identify customers at risk of attrition and develop proactive retention strategies. Maybank’s AI-powered Wealth 360 platform is one such initiative, offering predictive analytics to personalise client interactions and optimise investment recommendations.

AI is not just a tool for automating processes; it is becoming central to how wealth management firms engage clients, deliver personalised advice and drive operational efficiency.

AI is now a strategic necessity for banks

AI is no longer a future consideration—it is already a defining force in banking today. Analysis of the top-performing banks and financial platforms reveals clear strategies for success in AI adoption.

Scale AI investment across core banking functions: Banks must go beyond pilot AI projects and fully integrate AI into lending, wealth management, compliance and customer service.

Enhance AI governance and ethical AI usage: Transparency and fairness in AI-driven decision-making are critical as regulatory scrutiny increases.

Leverage AI for financial inclusion: AI-powered credit risk assessment models must continue to evolve to serve underbanked and SME customers more effectively.

AI-driven hyper-personalisation: Customer engagement strategies must evolve to leverage AI for personalised recommendations and advisory services.

Cybersecurity and risk mitigation: With the rise of AI-driven financial services, institutions must fortify AI-driven fraud detection and cybersecurity protocols to protect digital banking ecosystems.

AI is a strategic necessity for banks, not just a competitive advantage. The institutions that scale AI responsibly, integrate AI across multiple business lines and maintain customer trust will emerge as leaders in the next phase of banking transformation. The next decade will see AI become more agentic, enabling banks to operate with higher efficiency, customer-centricity and resilience.