Industry insights

Business banking product teams have spent the last few years arguing about SME banking trends and UX while the regulatory and competitive ground shifted. Mastercard AN4569 is live. Visa’s mandate hits in 2027. CCD2 is moving the BNPL in a new direction. And challengers that were niche five years ago are now credible.

Every card payment processing triggers a chain of events - money moves between banks, transaction records are created, and what customers see in their banking app is shaped by decisions made long before they tapped their card.

Every time a card is tapped, swiped, or entered online, a stream of raw transaction data is generated behind the scenes. Banks, payment processors, and fintechs all receive this data - yet very few of them can make it immediately useful.

For most payment teams, the card-present vs card-not-present transactions distinction gets filed under processing operations. It determines routing, compliance checklists, and interchange rate categories. But this framing is becoming a liability.

Transaction UX used to be a product decision. Some banks invested in recognisable merchant names and clean feeds. Others shipped raw descriptor strings and MCC codes. Today, Visa and Mastercard are increasingly turning transaction clarity into issuer requirements, and the minimum bar is rising for everyone.

SME clients have higher expectations than retail clients, and for good reason. Banking is not a background activity for them - it is part of their daily operations, reporting cycles, and financial planning. Transaction categorisation is not a visual convenience. It directly influences cost control, tax handling, internal reporting, and how accurately a business understands its own financial position.

Mobile banking has crossed the threshold from a convenient channel into the primary interface through which most people manage their financial lives. According to SQ Magazine, there are over 2.17 billion mobile banking users worldwide as of 2025, with Europe reaching 76% penetration and Nordic countries exceeding 87%.

As banking gets more digital, the need for simplification and automation is becoming more apparent. A significant part of that leads to the adoption of APIs in banking. While APIs (Application Programming Interfaces) have been here for a long time, the current surge in digital banking is driven by the demand for real-time payment solutions, advances in open banking regulations, and the necessity for enhanced customer engagement.

Key Performance Indicators (KPIs) serve as crucial tools, allowing banks to measure how effective their digital banking apps are in engaging customers. In this guide, we'll explore seven essential customer success KPIs, complete with straightforward formulas, designed to help banks improve customer engagement, foster loyalty, and reduce churn rates.

The fintech industry can be a crowded place. As it continues to grow and evolve, staying updated on the latest trends and innovations becomes more important than ever. LinkedIn is a goldmine for discovering influential thought leaders who provide valuable insights, news, and ideas that shape the sector.

Digital banking in 2026 will be defined by tighter regulation, higher UX expectations, cleaner data structures, and the slow disappearance of card-centric logic. Banks that treat data quality and transaction clarity as their core product layer move faster than institutions that still operate through legacy feeds and fragmented interfaces.

Fintech and digital banking event lists exist, but they are often fragmented, incomplete, or hard to compare. Relevant conferences are spread across multiple sources with little structure. This curated overview brings them together in one place for 2026.

Transaction enhancement services increasingly rely on AI and machine learning to automatically categorise transactions, enrich merchant data, and normalise transaction descriptions. These services analyse transaction strings, merchant identifiers, MCCs, geolocation, and historical behavior to assign accurate categories. AI-driven categorisation improves accuracy compared to rules-based systems and is widely adopted by banks, fintechs, and expense platforms to power insights, budgeting tools, fraud detection, and reporting.

Transaction data is only valuable when it’s clear and usable. It helps banks and fintechs transform raw payment strings into meaningful insights customers can instantly recognise - improving trust, experience, and engagement. Let’s dive deeper.

Banking is stretching its legs. Its main mission might still be balances and bills, but it’s also phones, travel data, game culture, groceries, even sports pits. In Europe, the most interesting shifts are practical, a little playful, and surprisingly useful.

On paper, building your own data enrichment solutions sounds smart. You’ve got capable engineers, a decent data science team, and a roadmap that seems to allow for it. But here's the thing: enriching transaction data isn’t just a technical project, it’s a constantly evolving project. And for many banks and fintechs, what starts as a quick fix turns into a long-term liability.

If you've ever looked at a bank statement and seen chaotic strings of data, you’re not alone. Customers expect clarity. They want to know what they spent, where, and on what. On the other hand, the backend needs to know how to handle data correctly so both sides are happy.

In recent years, more and more banks and financial institutions focus on sustainability as a core component of their operations. This shift towards responsible banking (also known as ethical banking) is mostly a response to the pressing global challenges of climate change, social inequality, and environmental degradation.