The system works wonderfully if you’re salaried, with a steady pay cheque and a credit history. But the story is different for India’s informal sector. Despite running viable businesses and managing complex cash flows, street vendors, small farmers, and neighbourhood shopkeepers are often invisible to traditional credit scoring models.
The problem isn’t their creditworthiness. Banks and NBFCs lack the tools to assess risk in an economy where income is seasonal, documentation is sparse, and a moderate salary in Tamil Nadu differs significantly from that in Jharkhand.
Traditional credit bureaus can’t distinguish between a hawker needing working capital and a dairy farmer with a steady income who can repay loans. Faced with uncertainty, the system sends out a rejection.
That’s the gap is working to fix.
Founded in 2017 by Sucharita Mukherjee and Puneet Gupta, Kaleidofin builds credit assessment tools specifically designed for the informal sector. The Chennai-based fintech uses AI and machine learning to help banks and NBFCs assess customers who fall outside traditional credit scoring, expanding access while managing risk.
Mukherjee, who served as Vice President at Morgan Stanley and Deutsche Bank before founding IFMR Capital and serving as CEO of IFMR Holdings, is the co-founder and CEO of Kaleidofin.
Gupta, who served as Chief Manager at ICICI Bank, co-founded the IFMR Trust Group, where he held roles including CEO of IFMR Mezzanine Finance and CFO of IFMR Holdings, before joining as co-founder and director.
The two are joined by Natasha Jethanandani, co-founder and CTO, who brings experience from Microsoft and Google and holds a degree from Stanford University, and Vipul Sekhsaria, co-founder and COO, who previously headed new business initiatives at IFMR Holdings and brings years of experience in the insurance sector.
Initial solution and pivot
In 2017, Kaleidofin launched as a savings platform for informal sector workers, who had access to loans but nowhere to save. Customers put aside small amounts monthly toward goals, like their child’s education, which Kaleidofin invested in mutual funds with insurance coverage.
The model worked through microfinance partnerships, and agents would encourage savings during loan collection visits. But COVID-19 disrupted this.
When loan repayments stopped during lockdowns, these agents pressured customers to withdraw their Kaleidofin savings to repay overdue loans, disrupting the distribution channel.
Meanwhile, SEBI announced a ban on pooling accounts in October 2021, where platforms could collect money from multiple customers into one account before investing in mutual funds, with the rule coming into effect in April 2022.
But Kaleidofin had been building data models to understand household income and stability for its savings product, and these models turned out to have an unexpected application. When COVID hit, and lenders couldn’t figure out who could actually repay loans, Kaleidofin already had the tools to answer that question. They were turned into credit scores just when banks desperately needed better ways to assess risk.
A deeper dive into the solutions offered
Today, Kaleidofin’s core offering is the “ki score”, a credit assessment tool that pulls from a much wider data set than traditional credit bureaus: demographic information, geography, payment patterns, savings behaviour, and alternative data sources, including satellite imagery, rainfall patterns, crop types, and livestock counts for farmers.
“Credit assessments need to happen in fractions of a second for real-time lending decisions,” Gupta says. This required building a data warehousing system that retrieves information instantly from multiple sources.
The key difference is the multi-model approach, where the platform runs hundreds of localised versions, instead of one national model. For example, in Bihar, a rain-fed farmer in a distant village is scored differently from one with irrigation near Patna. “If you use the same model to appraise all farmers, a rain-fed farmer might always get eliminated,” Gupta explains.
When a bank or NBFC receives a loan application, Kaleidofin’s API delivers a credit decision in real-time, within seconds. Beyond credit scoring, the startup provides “ki view”, a risk management dashboard that helps lenders monitor portfolio health and track early warning signals. The platform also facilitates co-lending arrangements between banks, NBFCs, and microfinance institutions.
On compliance, Kaleidofin adheres to the DPDP Act and is SOC 2 Type 2 compliant, with ISO 27001 certification for its technology and information security practices. The startup has KPMG conduct audits four times a year.
The Chennai-based B2B startup has over 57 partners, including banks, NBFCs, and microfinance institutions. “We now work internationally as well; models have been taken to Bangladesh and Africa,” Gupta says.
After compliance checks, Kaleidofin integrates into lenders’ systems via API. Customer data flows in masked, and credit recommendations return in 0.03 seconds. Banks retain final approval authority, and the startup tracks loan performance to continuously refine models.
According to Precedence Research, the global credit risk assessment market size was $8.36 billion in 2024. It is predicted to increase to about $31.46 billion by 2034, expanding at a CAGR of 14.17%. In this space, the startup competes with Lendingkart, FinBox, and SMEcorner.
Reaching 10.6 million customers in seven years
The platform has enabled loans to over 10.6 million unique customers and disbursed a total of $9.12 billion. The ki credit platform evaluates over 350,000 customer loans each month, loans for women entrepreneurs, agricultural loans, dairy loans, loans against property, and small business loans.
“The ki credit platform currently processes around $215 million in monthly volumes,” Gupta says.
“The credit risk for loans given using Kaleidofin’s models has been under 3% during the huge risk spike that the industry has been witnessing. A lot of customers now can take credit not only as part of group loans, but as individual loans,” Gupta explains. Kaleidofin operates with 100 employees and is a few months from operational break-even.
What’s next?
Gupta says their vision has largely been about “how to get high-quality products available to low-income households, so they can build their livelihoods in a proper manner”.
In India, Kaleidofin is working to expand its partnerships with more banks and financial institutions, focusing on proving the creditworthiness of its models and incorporating the latest data sources.
“The challenges of the developing world are similar to the Indian context. In fact, compared to many other countries, India has a very well-developed financial services sector. Others lag significantly behind,” Gupta notes.
Kaleidofin has started operations in East Africa. Over the next few years, it plans to expand its operations in Africa, covering most of East Africa, gradually moving into Southeast Asia.
Edited by Suman Singh
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