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Tietoevry Banking’s solutions help banks to stay competitive

Large number of POVs (Proof of Value) in credit area with focus on data and AI technology.

Aleksandr Peussa / June 06, 2023

Next step is to conduct extensive research on how external data will make the product concept even better – searching for new partners.

In recent years, squeezed margins and increased competition have significantly changed the banking business credit area. As a result, to remain competitive banks must invest more and more resources into cost optimization and new revenue generating models.

From its pole position, Tietoevry Banking has acknowledged three crucial factors that we think should be accommodated in the business models of banks to stay competitive. First of all, banks have to review the components affecting the pricing. Instead of looking mainly at credit risk, they should consider components such as ROI, churn risk, and price elasticity. Second, instead of averaging the pricing by big segments, banks need to consider more individualized approaches that use pricing components which enable more accurate predictions. And third, banks should consider new technological aspects of the solutions available through public cloud providers.

Tietoevry Banking’s solutions take all these three aspects into account. Our individualized approach utilizes the most modern data science techniques capitalizing on high intensity public cloud computational power and storage capacity. This means that instead of high-level segmentation typically used in the banking industry, our applications can analyze and predict the outcome at the individual level of each end customer of a bank. We aim to create products that are scalable and can be applied in different banks with minimal modifications.

Holistic approach to solutions

Tietoevry Banking has done extensive research in the credit area, covering the full life cycle of the loan process optimization. Our proof-of-concepts stand on a solid academic foundation with a strong business acumen. Based on our holistic approach, we tackle the problem from different angles, addressing the issues from the initial customer acquisition phase up till the portfolio management of the existing customer base. Some examples of our POC investigations covering various parts of credit domain include:

  • Churn risk: predicting the customer’s churn probability and recommending an optimal interest rate based on a bank’s existing customer behavior data.
  • Credit hungriness: proactively recommending top-up loans by quantifying an existing customer’s willingness to apply for another loan using machine learning methods.
  • Price elasticity: keeping the optimal portfolio profitability, while maintaining sales volume at a desired level. The idea is to target customers more elastic to interest rate changes to balance sales volume by impacting only a small share of potential customers.

Good basis for new product offering creation

Our current solutions build on the conventional data sources utilized in banking related to accounts, transactions, socioeconomic factors, and risk related predictions. As our empirical investigations with additional data sources support, we believe that we can improve our solutions by enriching the data sources with completely new ones. However, the conventional data sources can be complemented as well with additional records.

Inviting new partners to our ecosystem

The work we have done so far has increased our competence and improved market positions in the credit area. With the strong fundaments in place, we can accelerate the development and productization of the concepts through co-operation with various players in areas like banking and modern cloud technologies.

Through the ecosystem of Trusted Digital Societies programme we are looking for partners who can bring additional know-how in the technological side of solutions, who possess data that can improve our solutions, or the ones who know how to create data that is currently not even existing on the market. Please get in touch with us to discuss the possible co-operation in banking business with the aim to increase Finland’s competitiveness on the global market. The Trusted Digital Societies programme is part of the Business Finland funded Veturi initiative.


Intrested in learning more about the Venturi initative? 

Read more here about Tietoevry Veturi - Trusted Digital Societies

Read more here about Veturi solutions to future challenges

Read more from Aleksandar Peussa and the Veturi research AI regulation for banking here


Aleksandr Peussa
Head of Data & AI, Tietoevry Banking

Aleksandr leads whole Tietoevry Banking's software portfolio development of data and Al to transform it from "system of records" to "system of insights". He has worked in several international banks within risk management and business development, with a strong track record of business growth and intensifying corporate performance in Nordics, Baltics, and Poland.

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