FinBox: Powering the Complete Lending Value Chain
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New to Credit Customers – The Largest Opportunity Today, there are more than 60 percent Indians without access to formal credit. Moreover, there are millions of micro, small, and mid-sized enterprises with unmet financing needs.
This is due to the New-to-Credit or Thin file nature of the Indian borrower i.e. traditional way of relying on bureaus constrains lenders to serving a few ‘good’ segments only. Lenders are not adequately equipped to deal with this under served market segment as it requires substantially different capabilities compared to what they have today.
Solutions emerge from the Startup Space
From digital lenders to pay day loan companies, there are multiple startups working in bringing finance to the new-to-credit segment. However, there are only a handful which are building solutions for Banks and NBFC’s using state of the art technology.
FinBox is one such Bangalore based company. FinBox’s API and Data platform connects multiple traditional as well as alternative data sources to provide machine learning based credit scores(FinBox Inclusion Score). Through the Financial Inclusion Score, FinBox powers credit decisions of more than a million loans per month across lenders.
“FinBox is the leading alternative data aggregation and Machine Learning platform which empowers the BFSI players to digitize their processes and improve the efficiency of their existing digital solutions. We aim to make these organizations data rich and Machine Learning enabled in order to thrive in the digital economy”, states Anant Deshpande, Co-founder & COO at FinBox.
Unmatched Performance of Alternative Data Credit Scoring
Alternative data based credit scoring has remained a buzzword in the credit space for quite some time. These scores had lacked benchmarks until the widespread adoption by consumer durable NBFC’s, small ticket size digital lending startups etc.
Anant (FinBox COO) says that in an about to be unveiled case study FinBox demonstrates how their Inclusion Score performed 200 percent better than the traditional bureau scores and resulted in a 40 percent reduction in the client’s credit losses. The FinBox Financial Inclusion Score (FIS) is currently used to assess a combined loan portfolio of INR 19,000 Crores, of which 55 percent are NTCs (New to Credit).
Supercharging Customer Acquisition
Borrowers are increasingly discovering and consuming credit products online. This trend is being capitalized on by digital lenders, who have expanded their presence rapidly. For its BFSI customers, FinBox is enabling digital lead generation by connecting them seamlessly to digital properties of third parties. This enables lenders to grow their books by accessing qualified leads with in-depth information about borrowers from multiple sources. The FinBox platform also enables easy interpretation of the data and integration of its analytics with existing lending processes. As for the borrower, the unified platform provides access to the loan quickly and of the amount that justifies his/her true borrowing potential
ML Driven Future of Lending
According to Anant – “Lending is a very complex, data driven activity that can benefit tremendously from application of machine learning and data science”. According to him, FinBox will continue to build a comprehensive machine learning solution that will target customer on boarding, assessment, cross selling and collections. FinBox as an AI first company is betting that lenders will rapidly modernize their lending stack to include AI and ML in their decision making systems and FinBox will be at the forefront in supercharging this journey for its customers.
"The FinBox platform also enables easy interpretation of the data and integration of its analytics with existing lending processes"
Supercharging Customer Acquisition
Borrowers are increasingly discovering and consuming credit products online. This trend is being capitalized on by digital lenders, who have expanded their presence rapidly. For its BFSI customers, FinBox is enabling digital lead generation by connecting them seamlessly to digital properties of third parties. This enables lenders to grow their books by accessing qualified leads with in-depth information about borrowers from multiple sources. The FinBox platform also enables easy interpretation of the data and integration of its analytics with existing lending processes. As for the borrower, the unified platform provides access to the loan quickly and of the amount that justifies his/her true borrowing potential
ML Driven Future of Lending
According to Anant – “Lending is a very complex, data driven activity that can benefit tremendously from application of machine learning and data science”. According to him, FinBox will continue to build a comprehensive machine learning solution that will target customer on boarding, assessment, cross selling and collections. FinBox as an AI first company is betting that lenders will rapidly modernize their lending stack to include AI and ML in their decision making systems and FinBox will be at the forefront in supercharging this journey for its customers.
