Many companies still approach AI in customer service as a plug-and-play tool: implement, automate, scale. In banking and insurance, however, this approach quickly leads to regulatory and reputational risks. Because a different logic applies here: The more sensitive the request, the higher the requirements — and the clearer the limits of automation. A recent McKinsey study shows
Banks are sitting on one of their most valuable, yet least exploited resources: transaction data. Millions of bookings provide daily insights into consumer behaviour, life situations, risks and opportunities — but mostly in a form that is not directly usable. “Transaction Data Enrichment” describes the process of systematically refining this raw data: through AI, classification
How intelligent AI agents are transforming the front-end of banks – and why the new book “Digital Dimensions in the Financial Industry” is being published at exactly the right time. The financial sector is in the midst of a decisive transformation. The new book “Digital Dimensions in the Financial Industry” from Frankfurt School confirms this
Public administration faces increasing workload, limited resources, and rising expectations from citizens. Decision makers must ensure efficient service delivery, consistent and reliable information, and strict compliance with data protection laws — all at the same time. This is where the Acceleraid AI Assistant creates strategic value. It supports staff, reduces processing times, and ensures consistent,
The industry talks about personalization – but usually means segmentation For years, personalization has been one of the most frequently used terms in insurance marketing. In practice, it often translates into finer target groups, more segments, and better clusters. What the market expects today is something fundamentally different. Not better-defined audiences, but relevance at the
In many markets, the credit card business has reached a point of saturation. The number of issued cards continues to grow, but the real growth potential no longer lies in issuing more cards. It lies in how actively those cards are used. For credit card issuers, competitive advantage today is no longer defined by reach,
Banks have invested heavily in digital transformation. Yet one of the most powerful personalization assets is often underutilized: transaction data. Every bank account transaction, every credit card payment and every merchant category provides direct insight into customer behavior, needs and life situations. From Raw Transactions to Transaction Intelligence Transaction data is not just accounting information.
Artificial Intelligence is no longer a future promise in banking — it is ready for production. Yet many institutions remain stuck between pilot projects and real-world deployment. The reason is rarely technology. It is security, compliance, and governance. While GenAI and Agentic AI offer massive efficiency gains, banks hesitate because the regulatory framework feels unclear
Hardly any boardroom discussion in banking today takes place without mentioning artificial intelligence. Expectations are high: more efficient processes, better customer experiences, smarter decisions. But how far along are banks really? And where does the gap between ambition and execution lie? A look at the recent Cofinpro study “AI in Banking” reveals: the potential is
By Michael Altendorf, CEO of Acceleraid. Gartner has released its list of the top 10 technology trends for 2026. For many organizations, terms such as Multi-agent Systems or Confidential Computing still sound like a distant future. At Acceleraid, they are already part of our daily operations. Gartner’s predictions can be structured into three strategic pillars: