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Big Data Scoring is a cloud-based credit decision engine that helps banks, telecoms and consumer lenders improve credit quality and acceptance rates through the use of big data. Our team has over 30 years experience in developing credit scoring solutions. We develop and deploy custom scoring models that combine a lender’s internal data with thousands of pieces of external data such as location based information, web search results, behavioural tracking, device technical details, mobile app data and much more. This enables lenders to accurately predict borrower payment behaviour, helping then make informed and more profitable credit decisions in real time. More accurate underwriting helps lenders issue more loans, better manage credit quality and fight fraud. The fully automated scoring engine returns credit decisions in real time and removes the risk of human error or personal judgement. We work with lenders of all kinds – some of the largest banks in the world, payday lenders, P2P lending platforms, microfinance providers, leasing companies, insurance providers, e-commerce platforms and telecoms. In the field of consumer lending and where online channels play an important role in client acquisition, we can improve credit quality and loan acceptance rates.

Big Data Scoring Questions

The Big Data Scoring annual revenue was $5 million in 2026.

Oscar Koster is the Regional Director of Big Data Scoring.

6 people are employed at Big Data Scoring.

The NAICS codes for Big Data Scoring are [56, 561].

The SIC codes for Big Data Scoring are [732, 73].

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