2030 beckons. Is the industry listening?
What will banking products and technologies look like in 2030? And how can banks prepare for it? Here are some brief insights from this year’s Infosys Finacle-Qorus ‘Innovation in Retail Banking’ research by Rajsri Rengan, VP - Head of Product Development at Infosys Finacle.
Every year, we track future expectations for banking in our Innovation in Retail Banking survey. Halfway through this decade, one thing is certain – that there is dramatic change to come. As Sophie Heller, Chief Transformation Officer at CPBS at BNP Paribas says in the report, “The bank in five years will have almost nothing to do with the bank we know today. The pace is so quick that the transformation will be radical.”
What will banking products and technologies look like in 2030? And how can banks prepare for it? Here are some brief insights from this year’s Infosys Finacle-Qorus ‘Innovation in Retail Banking’ research by Rajsri Rengan, Vice President - Head of Product Development at Infosys Finacle.
Winning the deposits battle: From static accounts to dynamic value
62 percent of bankers agree that innovative deposits, especially those that are usage-based and dynamically priced, will corner a bigger share of new business than traditional fixed-rate products by 2030. Deposits will become more intelligent, adapting price to behavior, liquidity needs, and market realities.
To seize this opportunity, banks need a modern, cloud-native architecture, built on microservices, APIs, and real-time data. However, 60 percent of respondents rate their cloud-native adoption for deposit systems below 50 percent; nearly the same number say their core deposit platforms are still largely monolithic, with limited modernization at the periphery. High technical debt and fragmented architectures are the major obstacles to digital readiness.
The good news is that banks are making serious efforts to dismantle these barriers. Nearly half the banks say that they are prioritizing real-time digital onboarding and KYC to provide seamless experiences and capture deposits at the moment of need. For 21 percent, AI-driven deposit personalization is the way forward. Roughly one in seven respondents (13.6 percent) confirms adopting dynamic pricing and rate management in the hope of achieving significant improvement in deposit growth.
Inside the lending shake-up: Imperatives for banks
Fully automated retail and SME lending – taking less than 60 seconds from application to disbursement – will become reality by 2030, according to 69 percent of banking leaders. While banks have modernized lending products more than deposits, they still have some way to go. Only origination and decisioning processes have shifted to microservices-based architectures, leaving servicing, restructuring, and collections to legacy systems. A third of respondents estimate that their microservices adoption for end to end lending platform falls in the 26-50 percent range, clearly a work in progress.
But the pace is picking up. A full 86.5 percent of banks are prioritizing AI-driven credit scoring and underwriting to cut decision times and improve risk estimation. To unlock real gains, they need to scale explainable AI models, expand data partnerships, and embed automated decisioning throughout the lending lifecycle.
For just over 50 percent of banks, providing personalized credit and dynamic pricing is the way to meet customer expectations for tailored offers. Other initiatives worth considering include real-time pricing engines, behavioral scoring, and next-best-offer analytics.
Ecosystem lending innovations figure high in the three-year lending strategies of half the banks in our survey. While platform-based distribution and embedded finance are mainstream, banks are also expanding embedded lending partnerships, refining BNPL risk models, and exploring B2B2C ecosystem channels.
At the epicenter of payment disruption
Expectations for real-time cross-border payments run high with 82 percent of bankers saying they will be as seamless and affordable as domestic transactions by 2030, thanks to global interoperability and the growth of stablecoins and CBDCs. This expectation stems from banks’ advantageous positioning at the center of borderless ecosystems and their steady adoption of integrated, intelligence-led propositions.
Banks are according nearly equal priority to embedded payments, value added services, and API monetization in their near-term strategy, because they are all equally critical to payments innovation; banks rightly understand that they must be present in all these spaces to remain relevant across different ecosystems. However, they should take an integrated approach, harmonizing all their initiatives rather than treating them as isolated projects.
High hopes for embedded banking
Banking has been undergoing a major structural shift with embedded banking partnerships, executives expect it to be contributing at least 25 percent of universal bank revenues by 2030. Think embedded payments, credit at checkout, banking services embedded within SME apps and B2B platforms, etc. Although banks are embedding more offerings, they may not achieve the expected revenue contribution for 2030 without accelerating monetization maturity and investing in unified developer platforms and enterprise-grade compliance toolkits. However, maturity still lags here with only 3.2 percent of the banking executives claiming to have reached full commercial maturity where APIs generate measurable revenue and support cross-industry ecosystem models.
Cloud on the up
Banking technologies will likely see even more change than products through 2030. 77 percent of bankers believe that by that time, four out of five banks worldwide will run at least half of their mission-critical workloads in a multi-(public) cloud environment. While cloud-native foundations are advancing steadily, with a sizeable proportion of banks achieving scale or close to it, adoption is fragmented across systems; digital channels and lightweight services are transitioning faster than core systems, risk engines, and financial processing workloads. Banks need to address this by re-platforming using cloud-native design patterns. Viewing architecture as a strategic capability, banks should shift from one-off upgrades to unified modernization spanning data foundations, resilient cloud-native patterns, headless experience layers, and event-driven systems.
AI yet to progress
By 2030, generative AI and agentic AI will handle more than 80 percent of customer interactions and internal knowledge tasks, albeit under human supervision, say 65.5 percent of respondents. Aside from this optimistic prediction, the study reports mixed findings around AI: although banks are experimenting a lot, few have managed to scale projects successfully. Just one in ten initiatives across application areas achieve full scale, with a quarter to half making partial progress. Worryingly, one- fifth of implementations do not measure results perhaps due to a lack of visibility or governance. On the positive side, banks are managing to scale operational efficiency use-cases (for example, automation of document intelligence and workflow optimization) with more success, with 27.3 percent of such initiatives achieving a “POC to deployment” success rate ranging between 51 percent and 75 percent.
Banks need to avoid being stuck in pilot purgatory by evolving select priority AI initiatives across lending, payments, servicing, risk, and operations, and ensure they progress along a technological maturity continuum to actual deployment. Those in the early stages of the AI journey should look at improving outcomes from AI-assisted, human-led models; for institutions looking to make further progress, the goal will be to scale AI-powered workflows or experiment with AI-native reimagination. Leading banks will achieve high productivity gains with agentic AI, as they redesign processes around agents and embed services into partner platforms through agentic ecosystems.
While the pace of evolution of AI journeys will vary across institutions, and indeed within an institution itself, one thing is common to all – every bank has to move forward along the AI continuum to survive.
Resilience is paramount
80.5 percent of bankers agree that resilience will progress beyond recovery to real-time engineering, and that continuous-resilience engineering, chaos testing, self-healing, and zero-downtime patching will become mandatory for systemically important banks.
As threats and disruptions continue to grow, banks need to build resilience in several areas. First, infrastructure should be made resilient by design; the current focus on compute redundancy, database backup, and disaster recovery should extend to building resilience in eventing/messaging architecture and platform supply chain components.
Regulations, such as Digital Operational Resilience Act (DORA), NIS2 Directive, and Cyber Resilience Act, are reshaping the information and operational resilience landscape. Today, the expectation is that information security resilience should extend to securing deployment, ensuring data privacy and regulatory compliance, and protecting data both at rest and in transit.
Banks also need to build resilience in applications by engineering them to handle code failures through graceful degradation, disciplined timeouts/retries, circuit breakers, continuous resilience testing etc. ensuring critical journeys remain stable even when dependencies falter.
Banks have high hopes for their business in 2030. But to realize those dreams, they need to address several challenges and build new capabilities as listed above. Starting today.
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