Statistical analyses are getting more important in the finance sector. The larger and more complicated databases not only allow but require analytical tools. The competition is getting stronger, the number of products are also increasing. Cross-sell and up-sell possibilities are in focus. It may be crucial that the banks and other players know the needs of their customers. Results can help the managers making better decisions. Data mining is present in areas such as: CRM, product pricing, product development, marketing campaigns, etc.

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Intelligent Pricing Seminar – Optimal Package Calculator | SPSS Hungary organized an “Intelligent Pricing Seminar” on 27th November, 2009.
We successfully introduced a product propensity model system to support cross-sell sales activity of | We successfully introduced a product propensity model system to support cross-sell sales activity of T-Mobile brand at Magyar Telekom in 2006.
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We accomplished a churn project successfully at T-Mobile Macedonia. The project started in February, | We accomplished a churn project successfully at T-Mobile Macedonia.
Project in USA |  We performed a successful project in the USA.

Career | Datawarehouse architect, Data mining analyst, Oracle developer...
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Skiing in Austria | Company ski weekend.

• Customer Profitability (CV customer value analysis)The profitability model calculates financial value for each customer month by month to support front-end customer interactions
• Price SensitivitySupporting decision-making concerning new service introduction and price modification by revealing relationships between pricing and expected customer behavior
• Churn, retention Estimating churn probabilities for each customer thus identifying likely leavers to increase their lifetime by proactive interactions
• CannibalizmMeasuring the effect of new service introduction to other sources of profit
• Disloyalty AnalysisAiding customer retention campaigns by identifying customers most likely to leave, and generating attractive retention offers
• Campaign EffectivenessTarget-group selection for better response rates; measure success
• Price-Sensitivity ModelsCreating mathematical models of price-sensitivity and customer attrition to determine new pricing strategies for insurance companies
• Measuring Regional PotentialsCreating motivation systems for branch managers, measuring market share based on regional statistical data
• Need-based customer segmentation
• Product-portfolio analysis
• Customer retention
• Optimalized product calculation (to acquisition and retention campaignes)
• Credit risk analysis
• Collection-Scoring