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New Delhi [India], July 2: There are over 6.3 million MSMEs in India, with unmet credit demand close to $120 billion. Accessing small loans for MSMEs is often a long and uncertain process. The MSME credit landscape faces challenges in credit underwriting required for loan approval and disbursement. Credit underwriting requires the applicant's financial data from a large number of documents, such as balance sheets, cash flow and income statements, to assess the applicant's risk and financial health. MSMEs often lack documentation and have limited credit history, making it difficult for lenders to process their loan applications.
Many fintech companies work with lenders to improve lending processes through digital lending, loan origination systems, and automation leveraging machine learning and intelligent systems . However, MSME lenders are struggling to adopt systems that work with standard and comprehensive documentation for credit underwriting. MSME lenders have to rely on year-long bank statements to analyze the financial health of their applicants. These bank statements take up hundreds of pages due to low value transactions and often between different bank accounts. It takes an average of 1 to 2 days for the credit operations teams of such lenders to analyze these bank statements. Therefore, MSME lenders need faster processing systems to address the underserved MSME segment. Finuit, a fintech division of Quantrium, worked with a growing regional MSME lender in Tamil Nadu last year to study your subscription process. They developed a set of smart document processing tools that cater to the specific needs of MSME lenders based on available documents such as balance sheets, bank statements, profit and loss statements, etc. Arun S Iyer, Chief Business Officer, Finuit, said: "The lending needs of MSMEs are complex. We created a solution that is versatile enough to address unstructured financial data across multiple data sources. The overall objective was to make the process of getting crucial information from bank statements faster and easier. We achieved this by integrating AI, NLP tools and analytical capabilities.
Finuit's Bank Statement Analyzer processes bank statements to enable faster underwriting processes and credit decisions. The analyzer leverages artificial intelligence and machine learning technology to extract data from bank statements of the applicant's bank accounts to analyze key credit indicators, such as income and expense patterns, unusual or irregular transfers, identification of suppliers and distributors, etc. The bank statement analyzer's easy-to-use interface processes images of bank statements and passbooks across multiple bank accounts to derive applicant cash flow histories within 5 minutes.
The bank statement solution provides authoritative indicators of creditworthiness, such as income and expense patterns, unusual or irregular transfers, and payments to suppliers and distributors. The bank statement analyzer uses a dedicated and in-house trained LLM to identify key pieces of information from transaction details such as counterparty, transfer type, counterparty type, UPI ID, etc. Income and expense patterns are identified from details and information. extracted, through an ML model.M V Ramarao, Product Manager at Finuit, explains: "To ensure that the solution produces accurate and reliable results, we have established hundreds of rules. These rules are meticulously designed to guide the solution, improving its ability to provide accurate classifications and transaction information.
Finuit uses data encryption measures to ensure data integrity and confidentiality. Strict access controls are in place to protect data from potential breaches. As an evolving fintech company, they continually explore new security measures and mechanisms to update their security protocols.
"What we were looking for was a significant reduction in processing time without the need for additional resources. And our customers are delighted with the results. They complete in two days what previously took them a week," said Ramarao. Conclusion:
Finuit is the fintech division of Quantrium, an AI-ML IT products and services company based in Chennai, India. Finuit specializes in creating innovative AI-powered applications for global organizations. The company is run by accomplished professionals with decades of experience. Finuit's Document Intelligence suite includes Financial Statement Analyzer, Payslip Analyzer, Passbook Analyzer, Company Deep Forensics Tool and KYC Validator, solutions that address the critical business needs of the financial services industry.
New Delhi [India], July 2: There are over 6.3 million MSMEs in India, with unmet credit demand close to $120 billion. Accessing small loans for MSMEs is often a long and uncertain process. The MSME credit landscape faces challenges in credit underwriting required for loan approval and disbursement. Credit underwriting requires the applicant's financial data from a large number of documents, such as balance sheets, cash flow and income statements, to assess the applicant's risk and financial health. MSMEs often lack documentation and have limited credit history, making it difficult for lenders to process their loan applications.
Many fintech companies work with lenders to improve lending processes through digital lending, loan origination systems, and automation leveraging machine learning and intelligent systems . However, MSME lenders are struggling to adopt systems that work with standard and comprehensive documentation for credit underwriting. MSME lenders have to rely on year-long bank statements to analyze the financial health of their applicants. These bank statements take up hundreds of pages due to low value transactions and often between different bank accounts. It takes an average of 1 to 2 days for the credit operations teams of such lenders to analyze these bank statements. Therefore, MSME lenders need faster processing systems to address the underserved MSME segment. Finuit, a fintech division of Quantrium, worked with a growing regional MSME lender in Tamil Nadu last year to study your subscription process. They developed a set of smart document processing tools that cater to the specific needs of MSME lenders based on available documents such as balance sheets, bank statements, profit and loss statements, etc. Arun S Iyer, Chief Business Officer, Finuit, said: "The lending needs of MSMEs are complex. We created a solution that is versatile enough to address unstructured financial data across multiple data sources. The overall objective was to make the process of getting crucial information from bank statements faster and easier. We achieved this by integrating AI, NLP tools and analytical capabilities.
Finuit's Bank Statement Analyzer processes bank statements to enable faster underwriting processes and credit decisions. The analyzer leverages artificial intelligence and machine learning technology to extract data from bank statements of the applicant's bank accounts to analyze key credit indicators, such as income and expense patterns, unusual or irregular transfers, identification of suppliers and distributors, etc. The bank statement analyzer's easy-to-use interface processes images of bank statements and passbooks across multiple bank accounts to derive applicant cash flow histories within 5 minutes.
The bank statement solution provides authoritative indicators of creditworthiness, such as income and expense patterns, unusual or irregular transfers, and payments to suppliers and distributors. The bank statement analyzer uses a dedicated and in-house trained LLM to identify key pieces of information from transaction details such as counterparty, transfer type, counterparty type, UPI ID, etc. Income and expense patterns are identified from details and information. extracted, through an ML model.M V Ramarao, Product Manager at Finuit, explains: "To ensure that the solution produces accurate and reliable results, we have established hundreds of rules. These rules are meticulously designed to guide the solution, improving its ability to provide accurate classifications and transaction information.
Finuit uses data encryption measures to ensure data integrity and confidentiality. Strict access controls are in place to protect data from potential breaches. As an evolving fintech company, they continually explore new security measures and mechanisms to update their security protocols.
"What we were looking for was a significant reduction in processing time without the need for additional resources. And our customers are delighted with the results. They complete in two days what previously took them a week," said Ramarao. Conclusion:
Finuit is the fintech division of Quantrium, an AI-ML IT products and services company based in Chennai, India. Finuit specializes in creating innovative AI-powered applications for global organizations. The company is run by accomplished professionals with decades of experience. Finuit's Document Intelligence suite includes Financial Statement Analyzer, Payslip Analyzer, Passbook Analyzer, Company Deep Forensics Tool and KYC Validator, solutions that address the critical business needs of the financial services industry.