Cignifi has developed a technology to recognize patterns in the usages of mobile device. The system recognizes phone-calls, text messages and data usage and based on this information it can recognize someone’s lifestyle and his corresponding credit risk profile. The service just started with a pilot in Brazil and focuses on the 100 million people middle class who have limited access to financial products such as mortgages or loans as they do not have traditional credit data available.

The system processes and analyses billions of call data records and delivers a secure and easy-to-deploy solution for companies who want to offer financial services to people with a mobile phone but with no access to formal financial services. With 2.7 billion people worldwide who are part of this target group, it is clear that Cignifi offers a solution for a very large group of customers.

The patent pending analytics platform of Cignifi uses mathematical behaviour models to turn the available mobile data into information and insights. The predictive model uses hundreds of variables to define several consumers’ scores such as risk scores predicting the likelihood of default or delinquency or the response scores providing information about the likelihood that consumers will use certain financial products.

The analysis will happen over a period of time and respective scores will therefore evolve dynamically with the behaviour and activity of the user. Instead of a long period of payment history, Cignifi’s predictive models only need four weeks of data. This is especially relevant for emerging markets, where there is not yet big data available. A major aspect can be the privacy issue.

Cignifi states that scores are optimized to protect the privacy. Scores are not based on geo-data or content data and it only uses a combination of behavioural and time-related attributes.



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Head Office

101 Main St.
Cambridge, MA
United States

Countries Supported

Brazil, Ghana, Mexico, United States


Financial Services, Telecom



Size of Customers

Large, Global Enterprise, Medium

Year Founded



Funding Received from Investors

$ 2.1 million


Omidyar Network

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