Data-Driven Banking and the Analytical Framework of Finnova.
Data-Driven Banking and the Analytical Framework of Finnova.
Data is the new currency – this is also true for the trend-setting technologies and solutions we are developing at Contovista for the financial industry. Approaches such as artificial intelligence (AI) and machine learning (ML) create new possibilities for analysing data, for example through predictive and prescriptive analytics. Dynamic, data-driven market developments and applications around generative AI (GenAI) are changing the game, and Contovista is continuously working on integrating these innovations into the services we offer our customers.
Over the past few months, a lot has been going on behind the scenes, and we would like to share some updates. The product team for the Finnova Analytical Framework has been completely integrated into the Contovista teams. The teams continue to grow together – and so do the products: The data-driven Analytical Framework by Finnova perfectly matches Contovista’s data-driven banking strategy. In the future, the Analytical Framework will be focused even more on the topics of fraud and compliance.
«At a time when open and interconnected banking increasingly gains importance, Contovista is spearheading the movement towards a data-driven financial industry.»
René Kohler, Head of Contovista
Data-driven financial services are revolutionising banking in at least two important dimensions: they allow a much more precise insight into bank customers’ needs, and they enable an increasing interconnection of institutions, users, and third-party providers within the Open Finance ecosystem. From the perspective of end customers, it is key that they benefit from multibanking with innovative, personalised value-added services – thanks to our accurate transaction data analysis enriched with metadata.
Furthermore, customers enjoy an excellent user experience thanks to Contovista’s UX expertise and the seamless integration into digital banking. The bank benefits as well, since data-driven banking improves customer relationships, satisfaction, and engagement. At Contovista, we not only ensure technological abilities and easy-to-implement solutions for the financial ecosystem of the future; in line with our data-driven banking strategy, we also actively participate in the Open Banking community and seek out discussions in shared projects and current events.
Most of all, we also combine our expertise in aggregating, structuring, and enriching data with a deep understanding of the financial industry and comprehensive compliance know-how. This is of critical importance, since the customers’ trust is an essential element for the successful growth of the Open Finance ecosystem.
Gaining this trust requires the highest standards regarding compliance topics, such as fraud and anti-money laundering, as well as fundamentally responsible handling of the users’ data (data security, revision safety, traceability of results). We now also demonstrate our competencies in this area with the use of the Analytical Framework, which particularly targets fraud and compliance.
The Analytical Framework is a versatile, holistic analytical instrument, which enables a 360-degree view on customers from a risk perspective.It facilitates insights to customer behaviour and needs, while it also helps to optimise compliance with regulations and improves hazard protection.
The Analytical Framework contains advanced abilities in predictive and prescriptive analytics, which is why it significantly exceeds static models. The Analytical Framework is able to recognise patterns, provide forecasts, and derive recommendations. Automated, self-generated business rules ensure the constant calibration of the model and thus consistently achieve high-quality results. Due to its modular structure, it is possible to define very comprehensive analyses. In combination with (real-time) data sources, the Analytical Framework forms the foundation for knowledgeable and precise decision-making.
In concrete terms, we are introducing real-time compliance filter checks for payments in the Analytical Framework. This, together with reviewing customer master data, substantially improves performance and precision. The result is enhanced compliance, while simultaneously reducing false positives, and ultimately: more effectiveness with increased efficiency.
