Algo360, a leading alternate data-based credit assessment platform has crossed over 60 million lending decisions serving the underbanked population including both individuals and MSMEs.
About 40 percent of Indians do not have access to formal financial services which is especially prevalent in tier 2 and 3 cities and rural areas. NTC customers and unorganized MSMEs have struggled with traditional underwriting processes for a long time due to lack of credit history.
Today, AI and ML have enabled us to mould traditional lending methods used by banks to break the chain of discriminated financial accessibility across geographies and demographics. Augmenting traditional credit history and credit bureau data with the right alternate data points allows banks and other lenders to understand the creditworthiness of borrowers in a comprehensive manner.
Alternate data brings into picture utility payments history, financial etiquette, consumption patterns, investment behaviour and more, that gives us a robust view of a borrower's ability to responsibly manage debt. Algo360, an alternate data-based credit underwriting and insights solution, generates more than 800+ insights from a credit applicant's digital footprint in less than 3 minutes. The solution is built on a foundation of constantly changing data libraries, proprietary machine learning algorithms, unique risk and marketing scores, simple integration layers, and decades of analytics expertise.
Algo360 is the flagship product of . Commenting on their growth trajectory, Amit Das, CEO and Co-founder of Think360.ai, said, "We have always been on the lookout to integrate technologies to address current challenges in the Indian financial ecosystem to improve financial access for the masses. Digital lending has been on the rise as it democratizes distributional channels and loan procurement. According to a report by PWC, India's digital lending market will log a CAGR of 36% by 2023. Alternate data has a significant role to play in bringing financial inclusivity."
Monish Salot, Co-founder, Think360.ai, further added, "Digital lending has taken a spin with the arrival of credit emergency for individuals and businesses amidst the pandemic. The tested time has proved that cash flow, liquidity and access to credit are pillars for economic growth. We are grateful we could bring solace to the underbanked population in difficult times through Algo360."
MSMEs are in constant need of working capital for smoother operations. However, the lack of credit products leads to a cash crunch and hence, difficulty in timely payments which disrupts the economic cycle. Not just micro businesses, the absence of credit score has become a pain point for NTC, NTB and thin-file category individuals as well. CIBIL has stated that there could be 100 million NTC customers that apply for loans for the first time every year. These facts and figures highlight the urgency to relook the traditional ways of the lending industry and implement methods that can make the mainstream economy inclusive for MSMEs and NTCs.
With its product Algo360, Think360.ai has extended its services to around 50+ BFSI clients, enabling them to evaluate the credit-repayment abilities of this population segment, left-out by traditional banking practices, and make informed lending decisions to create financial equality among various classes. IDFC First Bank, BharatPe, KreditBee, Ola Money and Navi are a few of the organizations that leverage Algo360 for lending insights and instant decisioning for complex credit policies.
Algo360, a flagship product of Think360.ai that is revolutionizing digital lending using alternative data AI/ML. Algo360 provides score and insights to banks and fintechs that can increase credit approval rates and welcome more new-to-credit (NTC) category under the ambit of lending and borrowing.
The alternate data-based credit scoring platform uses smartphone data without compromising data privacy and personal information, (pre-approved by the customers) to help find creditworthy customers for unsecured lending products.
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( With inputs from ANI )
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