Chief Product Officer
CredoLab uses smartphone device data to generate a behavioural score for the customer that predicts her probability of defaulting. By accessing anonymised, metadata of the device, our AI-powered algorithm sends the financial institution the score of the applicant in a matter of seconds. In doing so, not only do we open a whole new segment of customers for banks and lenders, but we also bring down their cost of risk, speed up the processing time, and increase their overall Gini Coefficient.
Core to CredoLab’s algorithm is its modelling pipeline. The data processing pipeline consists of a series of automated steps, rooted in machine learning techniques, that ultimately outputs a predictive model for credit default.
CredoLab offers a set of easy to integrate, plug-and-play solutions that give decision makers all the information they need in real-time. The data collection is done through either a standalone mobile app, the CredoApp, or through a light CredoSDK library that integrates seamlessly with the financial institution’s existing app. Once installed, and the explicit data privacy consent is given by the customer, the app proceeds to analyse the anonymous data.
What Sets Us Apart:
- Data sources: CredoLab uses permissioned metadata to arrive at the credit score. No private nor sensitive information of the applicant is accessed or moved out of the mobile phone.
- One-time analysis: Unlike many alternative data-based scoring solutions, CredoLab’s algorithm analyses data only once, at the time of application after explicit consent is received from the applicant.
- Scalability: The AI-based algorithm learns and becomes more accurate and predictable as more data is fed into it. Therefore, the larger the set of data observed, the better the scoring.
- Privacy: CredoLab’s app does not proceed with any credit analysis unless the privacy consent and the necessary mobile Operating System’s permissions are given.