April, 2024
2.2K
March, 2024
4.5K
Total in 3 months : 14.9K
United States
Sweden
Poland
goscore brings a human credit scoring to private customers using modern ML technology and data enriched with PSD2 customer transactions. We deliver solutions and services to banks, insurance, retail companies to help them make the right credit decisions, personalize existing and develop new products, get more customers without marketing budget changes, reduce loan default rate. Our solutions made customer-centric and user-friendly and easy to integrate into the existed flow. We do 3 main things to fix the broken credit scoring: - data enrichment - Better algorithms - calculation transparency We use more data sources and utilise consumer data (with their explicit consent, obviously) incl. PSD2 transactions, Mastercard dataset, Google maps and various local data sources (structured data), such as business and other public registers. The next essential step is to use unstructured data, such as LinkedIn profile to analyse your position on the job market and by that predict your income and its stability. Better ML algorithms based on decision trees and neural network gives us an opportunity to find more complex relationships and correlation between different data points collected to build and analyse a comprehensive consumer profile. We share the score and explain it in the simplest terms to consumers, so they could understand: - why they got this exact CS - what could they do to make it better - how it affect their loans and creditworthiness Our first tier customers includes banks, leasing companies and retails stores. Goscore provides them hot leads and various data insights about new users for simpler onboarding as well as for existed customers.
goscore brings a human credit scoring to private customers using modern ML technology and data enriched with PSD2 customer transactions. We deliver solutions and services to banks, insurance, retail companies to help them make the right credit decisions, personalize existing and develop new products, get more customers without marketing budget changes, reduce loan default rate. Our solutions made customer-centric and user-friendly and easy to integrate into the existed flow. We do 3 main things to fix the broken credit scoring: - data enrichment - Better algorithms - calculation transparency We use more data sources and utilise consumer data (with their explicit consent, obviously) incl. PSD2 transactions, Mastercard dataset, Google maps and various local data sources (structured data), such as business and other public registers. The next essential step is to use unstructured data, such as LinkedIn profile to analyse your position on the job market and by that predict your income and its stability. Better ML algorithms based on decision trees and neural network gives us an opportunity to find more complex relationships and correlation between different data points collected to build and analyse a comprehensive consumer profile. We share the score and explain it in the simplest terms to consumers, so they could understand: - why they got this exact CS - what could they do to make it better - how it affect their loans and creditworthiness Our first tier customers includes banks, leasing companies and retails stores. Goscore provides them hot leads and various data insights about new users for simpler onboarding as well as for existed customers.
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