Credit risk automation platform Kaaj raises $3.8M seed from Kindred Ventures

Shivi Sharma, with a decade of experience in credit risk management at notable institutions like American Express and Varo Bank, identified a significant inefficiency in the loan assessment process. She observed that teams devoted equal time to analyzing loans of varying sizes, from $100,000 to $5 million, making the evaluation of smaller loans unprofitable and tedious for lenders. Along with her husband, Utsav Shah, they saw a clear opportunity to address this issue. "Many small business owners struggle to secure the funding they need for growth because traditional banking practices don't cater to their needs," Shah explained to TechCrunch. Leveraging their backgrounds in AI-driven decision-making and financial risk assessments, the couple founded Kaaj in 2024. Their mission is to automate credit risk analysis, significantly reducing the underwriting time from days to just minutes. Kaaj has already processed over $5 billion in loan applications, serving clients such as Amur Equipment Finance and Fundr. Recently, the company announced that it raised $3.8 million in a seed funding round led by Kindred Ventures and Better Tomorrow Ventures. The platform streamlines the loan application process: when a small business submits documents like financial statements and tax returns, Kaaj’s AI technology classifies, verifies, and organizes this data into the lender's Loan Origination System (LOS). Additionally, it conducts assessments to detect potential document tampering for fraud detection. By integrating with popular Customer Relationship Management (CRM) systems such as Salesforce and HubSpot, Kaaj ensures that lenders can quickly ascertain whether a business meets their lending criteria. "This innovation allows a team that typically processes 500 applications per month to handle up to 20,000 with the same resources, making smaller loans more economically feasible," Shah noted. The goal is to enhance accessibility to loans for small businesses by making the evaluation process more cost-effective for banks. Competitors like Middesk, Ocrolus, and MoneyThumb are also in this space, but Sharma believes Kaaj differentiates itself by automating the entire credit analysis process rather than just segments of it. “We utilize advanced AI workflows that replicate the actions of lending teams to facilitate comprehensive loan package assessments,” she stated. The new funding will accelerate product development and drive expansion among independent and small business lenders. Shah and Sharma aspire to revolutionize small business lending by infusing automation into a traditionally cumbersome, paper-heavy process. "By automating credit analysis, we enable human underwriters to concentrate on the nuances of deal-making and subjective assessments, which represent their true competitive edge," Shah concluded.