Finance sector

Automated real-time models for monitoring, prediction and optimisation reduce risks and free up time for strategic and more multi-dimensional tasks.

  • Dynamic prediction of credit loss: Model that predicts the expected credit loss of outstanding credit.
  • Modelling of credit decision process: Analytical algorithm that maximises credit granting while minimising credit losses.
  • Flexible interest rate: Optimisation of interest rates based on customer data.
  • Share of wallet analysis:  Based on the modelling of your customers’ purchase behaviour. The analysis provides share-of-wallet percentages for your offering, in other words, your market share in selected segments. Analysis describes the amount of additional potential in the market.
  • Fraud detection: Detection of fraud through analytics by automatically listing deviating patterns and values of action.
  • Prediction of customer attrition:  Predictive analysis of customer attrition describes the attrition risk regarding customer segments and causes of attrition on both the individual and segment levels.
  • Cross- and up-selling:  Predictive analytics is used to find the most potential customers and the products targeted at them.
  • Personalised newsletter:  A newsletter based on the customer’s purchase behaviour that contains personalised content and other topical content.
  • Marketing monitoring analyses:  Monitoring analyses and reporting of targeted marketing provide the foundation for continuous improvement of customer communications.



Juha Raunama
Director, Customer Solutions
Houston Analytics Oy
tel. +358 400 845 908

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Houston Analytics Ltd
Konepajankuja 1, 00510 Helsinki
c/o Pedab Denmark 2. sal, Vibeholms Allé 16, 2605 Brøndby
Business ID: 2574184-1

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