The Rise of Fintechs and Shifting Customer Expectations
The banking sector faces intense competition from a dynamic ecosystem of fintech companies and neo-banks, which are often the true innovators in the space.
These newer players, unburdened by legacy infrastructure, can build on modern technology stacks from scratch, offering services that are inherently faster, more accessible, and often lower cost. For example, a company like Revolut, unknown 10 years ago, has become one of Europe’s largest institutions by leveraging this agility.
Customer expectations have dramatically shifted. Individuals now expect to access their financial services instantly, 24/7, through mobile applications. They demand quick, low-cost, or even no-cost payments and increasingly seek sophisticated investment products.
Many customers, particularly for investments, are opting for neo-brokers over traditional banks due to superior service and user experience. This gap between what traditional banks can offer with their legacy systems and what customers now expect creates a growing vulnerability, as neo-banks continue to grow exponentially by meeting these demands.
Artificial Intelligence: Beyond the Surface
The advent of artificial intelligence, including generative and agentic AI, is widely discussed as a potential game-changer for banking. AI holds the promise of
- Enhancing customer experience
- Automating processes
- Providing deeper insights
However, its true potential can only be realized if banks have the right data foundation. AI solutions require high-quality, real-time data that is readily available and integrated.
For banks operating on legacy systems with siloed, fragmented, or “rubbish” data that is not available in real time, simply adopting AI tools as an overlay is insufficient. Such an approach can simulate innovation but will still necessitate manual workarounds and fail to deliver the full benefits of AI.
To genuinely leverage AI’s power, banks must first ensure their core infrastructure can provide the clean, centralized, and instantly accessible data that these advanced technologies depend on. Without this foundational shift, AI adoption risks becoming another layer of complexity on an already struggling system, rather than a transformative force.
Open Finance and the Demand for Real-Time Data
The move towards open finance, often referred to as “Feeder,” represents a significant expansion beyond earlier initiatives like PSD2. While PSD2 focused on instant data transfer between specific players, open finance aims to make data available across virtually every area of financial services.
This requires banks to provide instant access to customer data, not just for regulatory compliance but also for collaboration with other financial entities and to empower customers with greater control over their financial information.
The current reality for many banks, however, is that data is fragmented across various systems and often processed in batches. Even with T+1 settlement cycles in Europe, which theoretically allow for overnight processing, the need for instant data for exception management and real-time operations makes overnight processing insufficient.
To participate effectively in an open finance ecosystem and support instant payments, banks need a core system that centralizes data, ensures its quality, and makes it available within seconds.
The outdated concept of Extract, Transform, Load (ETL) layers, which involve extracting data to ingest it into new solutions, is no longer viable. Instead, banks need reliable APIs that allow data to flow instantly between systems.
Modernizing the Core: A Strategic Imperative
The path forward for banks lies in comprehensive core banking modernization. This is not an easy undertaking; it is a risky and complex exercise that involves migrating potentially 30 years of legacy data.
Unlike fintechs that start with a “white piece of paper” and can build on new technology stacks, incumbent banks must contend with existing infrastructure and vast amounts of historical data. There is often resistance within the industry, partly due to the perceived risk and the lack of immediate, visible “celebration” for such internal projects.
However, the alternative is to fall further behind. Core modernization means moving towards a service-oriented architecture with real-time capabilities, a single database, and hundreds of APIs to communicate with the broader financial ecosystem.
Some core banking providers have already made this transition, investing heavily – over a billion euros in some cases – to transform their solutions to be instant and API-driven, drawing on 35 years of experience while constantly innovating.
This demonstrates that it is possible to combine deep industry knowledge with cutting-edge technology. For banks, understanding that the core needs fundamental attention, rather than just superficial upgrades, is the most important first step on this journey towards competitive survival and future growth.
