In this exclusive interview with “Bilanz”, our Unit Head René Kohler outlines how Contovista’s innovative solutions create added value for both financial institutions and their customers. In the conversation, René explains how we analyze large amounts of data using AI and thereby not only simplify banking, moreover, we make it more predictive and smarter.
René: Our vision is to transform the financial industry into a seamless, secure, and intelligently connected ecosystem – empowering banks and their customers to reach their full potential. At Contovista, we harness the power of financial data by leveraging AI to aggregate, enrich, and translate it into meaningful customer value. Achieving this requires forward-thinking and the ability to anticipate which topics will matter most to banks and their customers.
Artificial intelligence offers tremendous potential in this context, enabling the extraction of valuable insights from transactions and account data.
Wouldn’t it be amazing if your bank account could think for itself, anticipate your financial needs, and help you achieve personal goals?
René: That is indeed a challenge. For us, it’s crucial to focus on the areas that are truly relevant to us and our customers. After all, it’s impossible to cover the entire AI landscape. That’s why we continuously invest in ideation and development, and work closely with external partners. Our modular product approach allows us to integrate new AI features quickly and flexibly.
One of our latest developments is natural language search, which allows banking customers to type questions directly into their mobile app. The system can then search financial data from various sources to find the answer to the query.
René: When developing our applications, we always focus on how we can use and process data in a way that creates added value for everyone involved – both for the bank and end customers. AI plays a central role here, particularly in harmonising heterogeneous data streams and consolidating various data sources such as credit card platforms, e-banking systems, or portals like bLink.
The result is a consolidated overview of a customer’s financial situation, which can be seamlessly integrated into digital banking. By using AI, we’re not only able to categorise and enrich transactions automatically and efficiently – for example, with merchant logos, “pretty names”, location data, and semantic tags – but also to take data quality and clarity to a whole new level. Especially in the context of multibanking, this transforms fragmented information into a consistent, customer-centric experience.
Our solutions operate independently of the core banking system, follow a modular structure, and integrate flexibly into existing infrastructure.
Interview with René Kohler, Unit Head Contovista
René: As a company operating in the data-driven banking sector, this is an absolute priority for us. After all, data protection and data ethics are core principles that run through our entire process chain. We consistently follow a Privacy by Design approach right from the very outset, which means our AI models are developed with data protection in mind. For example, customer and transaction data are always processed separately, since transaction data alone is often sufficient to generate meaningful insights. What’s more, all data is processed locally in Switzerland. Beyond that, we are committed to clear AI principles: the highest level of security, consistent compliance, transparent communication, and fairness towards all users. Our AI models are explainable, regularly checked for bias, and follow a human-in-the-loop approach – meaning that critical outcomes are always validated by human expertise. This ensures that our solutions are not only technologically advanced but also ethically responsible and trustworthy.
René: Our primary drive is to create real value for our customers. To achieve this, we need to draw the right conclusions from the available data and deliver the right information at the right time. In practice, this might mean recognising a customer’s income and expenses to provide a clear picture of their financial situation and then offering specific, personalised recommendations. A particularly exciting example of an end customer application is our “Smart Balance Optimiser”. This analyses where the customer’s money is held, assesses the interest rates available, and, if appropriate, suggests transferring part of the funds to a better-paying savings account. Ongoing subscriptions are identified, tax-relevant expenses are processed automatically, and budget deviations are detected early on.
«With our AI Finance Management solutions, we are creating a digital banking system that “thinks for itself” and identifies subscriptions, automatically categorizes tax-deductible transactions and provides personalized insights.»
René Kohler, Unit Head Contovista
With geolocation features, transactions can be visualised on a map, providing additional clarity. Thanks to intelligent, customisable categories, customers can fine-tune their financial behaviour in great detail. Banks directly reap the benefits as well. Through integrated Client Analytics, they gain deep insights into their customers’ financial behaviour – anonymised and aggregated. These insights help banks to develop their digital offerings in a targeted manner, proactively offer relevant products, and boost customer satisfaction and loyalty. This creates a double benefit: hyper-personalised digital banking for end customers combined with data-driven decision-making for banks.
René: We use both AI and traditional algorithms to analyse all transactions in real time. We identify the underlying products and services, categorise them, and then link them to market-specific CO2 values to calculate the individual carbon footprint. Modern AI systems are essential for this detailed analysis. We provide users with tools such as gamification elements, personalised tips, and, most importantly, transparency, by educating them about their CO2 consumption. These features support behavioural change and help raise awareness.
René: Our Business Finance Manager is an intelligent 360-degree cockpit specifically tailored to the needs of SMEs. It provides a comprehensive overview of all accounts and can analyse every transaction. This enables it to recognise seasonal and industry-specific patterns and generate various scenarios: what income can be expected? What expenses are upcoming? How does liquidity look for planned investments – or is there a risk of a shortfall?
The key difference compared to traditional tools is that we don’t just provide analyses, but also offer specific recommendations for action. For example, it might be beneficial to delay certain payments while bringing forward others to optimise liquidity management. For banks, the BFM creates a data-driven platform to better understand and support their SME customers individually – whether through targeted cross-selling or well-informed advice on financial stability.
René: Connectivity, driven by the principles of open banking, is emerging as a cornerstone of the financial ecosystem of the future. Customers are increasingly engaging with services from multiple institutions and third-party providers (TPPs) within a unified, holistic ecosystem – a trend that is already gaining clear momentum. Another key development, especially in the realm of AI, is the transition to the next phase: agentic AI. In this model, AI agents autonomously carry out specific tasks – from optimising banking processes through independent data sourcing and preparation, to developing financial assistants capable of handling tasks on their own. These are areas we are actively exploring.
