Industry insights

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.

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 behaviour 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.

The financial industry has undergone a pretty radical transformation in the last decade, with mobile banking becoming a primary interface between banks and their customers. As highlighted by recent research from Branch, the mobile app industry has been seeing significant growth during the past several years and this trend extends to the financial sector.

Have you ever been in a meeting or conference, nodding along as industry experts toss around terms and abbreviations that sound like a foreign language? It can feel overwhelming, especially in the financial world, where terms and slang evolves fast.

This gathering of experts and professionals not only provided a valuable opportunity for us to learn about the latest trends and developments within the industry but most importantly, our Head of Partnerships, Simon Koci, had a chance to host and moderate a panel discussion on the topic of Cooperation Between Banks and Fintechs.

User experience (UX) today goes beyond a nice-looking interface or a conveniently usable application; it is about making data actionable, intuitive, and applicable in whatever interaction is made by the user.

Following the updates to the AI Act, it’s essential for banks to ensure their AI systems comply with these new regulations. This guide breaks down the process into manageable steps, making it straightforward for digital banking experts to follow and ensure compliance.

Automated Teller Machines have evolved significantly since their introduction in the 1960s. Initially designed to dispense cash outside banking hours, ATMs now offer a range of services, from depositing checks to transferring money between accounts. Today, there are over 3.5 million ATMs worldwide that are visited by users on average at least 8-10 times a month. Even cryptocurrency ATMs are on the rise, with more than 39 000 used worldwide.

AI in banking in 2027 is not a question of adoption, but how far it goes beyond efficiency. More than 80% of financial services firms are adopting AI at some level, and 52% are already experimenting with agentic AI. So far, the payoff is efficiency gains rather than business model transformation, according to the Cambridge Centre for Alternative Finance. The regulatory picture has also shifted since the AI Act was adopted. Here is what banks are actually doing with AI now, and what changes over the next 12 months.

The market for digital lending from non-bank credit card issuers and fintech firms is becoming increasingly popular among consumers. It is a modern and innovative form of financing that provides a faster and more accessible alternative to traditional methods. The long queues at bank branches have come to an end. Customers want a loan in a few clicks and they want a card full of benefits to go with it. The BNPL trend with players like Klarna, Zip and Twisto shows this.