Monsoon CreditTech: Democratizing Machine Learning for Banks & NBFCs, Raises Funding from Angel Investors
Monsoon CreditTech’s Machine Learning Access Program (MLAP) is meant to give the top management of banks and NBFCs a risk-free way to try Monsoon’s proprietary machine learning-powered technology on their loan books irrespective of loan-book size or in-house technology expertise.
With the objective of democratizing machine learning among India’s NBFCs, banks and FinTech enabled lenders, Monsoon CreditTech has launched a Machine Learning Access Program. The company have also raised an undisclosed amount of funding from marquee investors like super angel Sunil Kalra, former senior Microsoft executive Rishi Srivastava, Google India’s Rajan Anandan and Aditya Singh. The newly launched program enables lenders to leverage the power of advanced machine learning techniques on their loan datasets without having to commit significant resources to the endeavour before the success of the model is proven on their data.
Why Machine Learning?
Machine learning presents tremendous potential in the areas of loan underwriting & decisioning. By identifying and exploiting subtle patterns in borrower data and repayment data, machine learning powered systems can lead to significantly higher loan approval rates, lower delinquency rates, shorter turnaround times and higher profits.
The need for such technology could not possibly be more acute than it is today, when the system-wide Non-Performing-Assets ratio (NPA) is at 9.6% today and is likely to rise to 10.2% in the near future according to RBI. In stark contrast to the perception among some, this is not a problem limited to PSU banks as private banks have an NPA ratio of 3.91% , representing more than a 100% jump over the last year’s figure.
Machine learning shows significant promise in this area and has been shown to do a superior job of underwriting loans compared to traditional processes followed today. Case in point - The FinTech revolution in developed economies has been powered in large part by machine learning, leading to the creation of companies with astronomical valuations like SoFi ($4.3 billion), Kabbage(>$1billion), Affirm ($576 million) and Kreditech(>EUR 300 million).
The need for a program such as the Machine Learning Access Program: MLAP
Bankers, almost universally, recognize the potential that machine learning presents. However, they often grapple the following questions which often slows down decision-making and therefore the adoption of ML by lenders:
1. How can I be sure that machine learning will work for my data, in my business context?
2. Does my organization have the in-house technical expertise necessary to translate machine learning technology into tangible business outcomes?
About the Machine Learning Access Program
Monsoon CreditTech’s Machine Learning Access Program (MLAP) is meant to give the top management of banks and NBFCs a risk-free way to try Monsoon’s proprietary machine learning-powered technology on their loan books irrespective of loan-book size or in-house technology expertise. In most cases, our technology is likely to lead to up to a 24% increase in loan approval rates and up to a 20% decline in delinquency rates- something that can be verified by comparing our risk scorecards with the loan outcomes of historic loans hidden from us.
Says Founder Ashwini Anand, CFA, “Since it is a success-based model, there is no significant upfront investment of manpower or resources, thus giving lenders the flexibility to embrace machine learning without jumping through hoops. It is like a call option – there is unlimited upside and virtually no downside.”
About Monsoon CreditTech
In stealth mode till recently, Monsoon CreditTech is powered by a team of data scientists and financial analysts who were with marquee organizations like Merrill Lynch, Bank of America, The World Bank and American Express. Monsoon is backed by prominent FinTech investors and currently works with a range of private banks, NBFCs and new-age lenders to help them leverage the power of machine learning to maximize loan approval rates, minimize delinquencies and optimize loan-loss adjusted net interest income.
"Monsoon, unlike the others is this space, is focused on doing just one thing- building world class machine learning technology that can turn around the performance of loan books. This enables them to focus on credit decisioning- their core competence, without worrying about things like lead acquisition, regulatory compliance and collections," says Rishi Srivastava.
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