技术趋势-重新定义银行业

An overview across Contents Technology as a strategic advantage For banks, operating under pressure is nothing new. High running costs, tight margins and regulatory complexityhave long shaped the industry. In this environment, technology has often been viewed as a cost center rather Whathaschanged is the pace of innovation, and the consequences of falling behind. Banks are recognizing that technology is central to their ability to build trust, compete and grow. Those treatingtechnology as a strategic asset are pulling ahead, those that don’t are finding it increasingly difficult to keep This report examines the forces shaping banking across Retail, Corporate, Wealth and Payments. Banks arenavigating heightened regulatory scrutiny, escalating cyber threats, rising customer expectations and intensifyingcompetition. At the same time, meaningful growth opportunities exist across verticals, but only for banks who Many banks are attempting to respond to these challenges and opportunities with platforms that were neverdesigned for them. Legacy cores struggle to support modern security standards and real-time decision making.Nearly a third (28%) of legacy banking applications are undocumented, creating hidden operational risk and In practical terms, legacy environments make agility slow, change expensive, and innovation harder to deliver. A different approach is now taking hold. Cloud-native, composable core platforms provide the resilience,scalability and system integration required to build trust, progressively modernize and support sustainablegrowth. They allow targeted investments in AI and automation that deliver measurable value, including lower Across banking segments, the pattern is consistent. Banks that embed intelligence into a modern core, ratherthan layering it onto legacy, are better positioned. In the market, they’re increasing share of wallet, improvingcross sell, and using real-time, AI-driven capabilities to grow in areas such as DeFi and payments. Within thebank, gen AI is already compressing tasks that once took months into minutes. Meanwhile, agentic AI is In collaboration with Bain & Company, this report brings together industry research, market insights andTemenos Value Benchmark data to give banking leaders an evidence-based view of the trends shaping their The future of banking will be defined by institutions that treattechnology not just as a cost to be managed, but as a driver of growth, Will MoroneyChief Revenue Officer Technology Against a backdrop of high operating costs and squeezed margins,technology has traditionally been viewed as a cost center bybanks. Today, however, there is growing recognition of its strategic However, to fully leverage the potential ofinnovations such as generative and agenticAI, financial institutions must ensure they Tighter regulatory oversight of operationalresilience is also resetting technologypriorities, with many focusing more onbusiness outcomes, ensuring that technology investments truly add value and can evolve Ask, don’t navigate: Generative AI Like in many other sectors, naturallanguage interfaces are revolutionizingproductivity in banking. Generative AI ischanging how business users interactwith systems, replacing complex and potentially creating revenueopportunities. Crucially, the underlyinglogic or SQL is always visible, so outputs As global guidance and legislationcontinue to evolve, some financialinstitutions are gravitating tothe popular open-source ModelContext Protocol (MCP), whichprovides a mechanism for AI to tapinto context and data from coresystems and external services In a legacy technology environment,answering this type of query wouldnot be feasible, and could take weeksor even months of manual effort.By spending less time searching for Instead of navigating endless menusor writing SQL queries, business userscan ask for reports or actions in naturallanguage and get immediate results. Forexample, asking the interface to“Identifycustomers aged 34–50 who opened Beyond analysis, this natural languageapproach will bleed into how digitalexperiences are created and adapted. Agentic AI drives operational autonomy While generative AI creates contentbased on learned patterns, agenticAI combines these capabilities withgoal-driven actions to perform tasks.This is fundamentally transforming According to industry research, banksare most open to using agentic AI forreducing labor costs in operations(86%), followed by support (75%), andmaintenance (71%). On average, laboraccounts for almost half (49%) of corebanking total cost of ownership (TCO), In payments, AI agents can detect andrepair broken transactions in real time,identifying causes such as formattingerrors. With such issues much less In watchlist screening, AI agents canaction and resolve alerts as theyarise, reducing false positives andeasing workloads. Low-risk alerts are As deployments accelerate, financialinstitutions are expected to see clearer,more me