FINANCIAL MODELS

 
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Churn prediction

Since 2012 about 20% of clients in financial sector are leaving their service providers annually. On base of long term and recent history data the clients intending to leave are identified with up to 96% accuracy depending on available data. The identification serves as the basis for targeted communication and marketing in aim to prevent the individual clients to leave.

The cost of acquiring a new client is several times higher than the cost of retainment of existing clients.


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Propensity to buy

Analysis of available data gives result for individual clients how likely they are buying a particular financial product. The model outcome directs the financial institution to right time offerings to individual clients or customer segments.


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Pricing

Optimal product pricing determines the optimal price for individual financial products in aim of different client segments or individual client's expectations.


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Product recommendation

Recommendation engines basically use algorithms and data to recommend the most relevant items to a particular individual client or customer segments.