Temenos report says five trends will reshape banking

Temenos has published a banking technology report with Bain & Company outlining five trends it says are set to reshape banking across retail, SME, corporate, wealth and payments.

The report argues that banks are entering a period in which technology choices will have a lasting effect on their ability to compete.

Many lenders have spent years improving digital front ends, but progress in underlying systems has slowed, according to the study. It points to increased investment in cloud core modernisation, data architecture and artificial intelligence, while arguing that weak foundations are holding back broader transformation efforts.

The findings draw on perspectives from Temenos and Bain, alongside insights from the Temenos Value Benchmark. The assessment examines how banks are changing their technology priorities as they seek to update core systems, make better use of data and find new revenue from digital services.

Five Trends

One of the report's central themes is the use of artificial intelligence under tighter governance. It highlights approaches such as the Model Context Protocol, which allows AI systems to retrieve context and data from core systems and external services without duplicating data or embedding logic into models.

A second trend is the shift towards cloud-native architecture, software-as-a-service platforms and data mesh structures. Banks are trying to reduce dependence on legacy systems, but still face fragmented, hard-to-access data, the report says. It adds that 21% of data is duplicated.

Corporate and commercial banking is another area flagged for change. AI agents are beginning to take over workflows including deal structuring, compliance checks and documentation, replacing manual and highly customised processes, the study says. It also points to demand from treasurers for real-time visibility into liquidity and payments, which is pushing banks to update API-driven channels and core infrastructure.

Stablecoins also feature prominently. The report argues that they are moving beyond crypto market infrastructure and becoming a more credible settlement and liquidity rail for some banking and payments flows, particularly in cross-border, liquidity and wholesale use cases.

The fifth trend is hyper-personalisation in retail and SME banking. Banks are using AI and behavioural data to make offers more relevant and timely, with the aim of increasing customer engagement and expanding the number of products each customer holds. The report puts the current average at 2.59 products per customer.

Core Systems

The report presents core banking modernisation as a recurring requirement behind each of these trends. It argues that institutions looking to scale AI safely or monetise digital channels will need cleaner data structures, stronger governance and more flexible infrastructure.

That reflects a broader shift across the sector. Over the past several years, many banks have focused on customer-facing apps and digital channels while leaving older back-end technology in place. The assessment suggests this model is becoming harder to sustain as banks try to support real-time services, greater automation and new forms of settlement.

William Moroney, Chief Revenue Officer at Temenos, said: "Technology has become central to how banks earn trust, compete, and grow. Those treating technology as a strategic asset are pulling ahead, while others are finding it increasingly difficult to keep pace. This report highlights where value is emerging and outlines the technology decisions shaping the future of banking."

For Bain, the emphasis is as much on architecture and controls as on adoption. The consulting firm says banks that do not address core systems and data quality may struggle to move AI beyond pilots or isolated use cases.

Joseph Edwin, Partner at Bain & Company, said: "Banks are entering a decisive period where technology choices will determine competitiveness for years to come. Bain's work across the sector shows that the winners will be those that modernise the core, adopt cloud-native architecture, and build governed data and security foundations that allow AI to scale safely."