AI Case Study

Kreditech determines credit worthiness of thin file customers by analysing the way they use internet, social media data, location data and past behaviour, using machine learning

Kreditech offers tailored banking products to customers with little credit history and analyse behavioural patterns to classify them based on risk. Their machine learning algorithms analyse the way customer is using websites, browsing history, location history, social media data, shopping data etc to arrive at a decision.

Industry

Financial Services

Banking

Project Overview

"Kreditech has developed a globally unique technology for scoring thin-file customers. Our USPs are the enablers for becoming the “Digital Bank for the Underbanked”. Our unique technology aims to provide a friendly and fast service for the consumer. For this, we have developed a proprietary credit scoring technology which uses artificial intelligence and machine learning to process up to 20,000 data points per application. It allows us to score a customer within less than one minute and determine credit risk with higher precision than traditional credit-bureau based systems, especially for thin-file customers. The technology hence enables us to serve credit to customers across all channels and segments. It includes the underbanked, those who are rejected or badly served by traditional banks.

Kreditech analyses all the customer interactions with the website including key strokes, copy-pasting the name Vs typing the name, how much time is spent on the website, browsing history, shopping habits, location data, social media history etc."

Reported Results

Serves more than 700,000 customers worldwide with revenue over 45m Euro

Technology

Function

Strategy

Data Science

Background

Kreditech aims to offer banking access to customers with little or no credit history

Benefits

Data

Processes up to 20,000 data points per application