Business Intelligence and Analytics

the challenge

A Nairobi-based microfinance institution specializing in car finance and other credit services sought to create a predictive model that identified:

  • The rate at which customers would apply for loans based on past behavior.
  • The volume of transactions that a customer is likely to partake based on previous transactions.

Solution

Using Arbutus Analyzer, we were able to model the logic using a script, utilized by a combination and functions, to identify a pattern which our client would use to study the frequency at which their customers accessed their loan services.

Arbutus was also able to predict the volume of loan uptake a customer with respect to previous transactions.

Results

The client is now able to understand the customers’ behavior in borrowing loans, payments and even predict how long it would take to pay with interest based on previous experience with the customer.

 

This enables the firm to make better decisions in terms of long-term viability in customer retention and behavior.

Start by doing what’s necessary; then do what’s possible; and suddenly you will have solved the problem and doing the impossible.

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St Francis of Assisi
1181 - 1226

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