USD 400 million portfolio outstanding. 

USD 90 million revenue in FY24. 

USD 900 million cumulative disbursement to date. 

133 branches across 6 states. 

Over 132,456 loans disbursed with an average ticket size of ~USD 10,000. 

Significant job creation, with 36% of new jobs going to women and 11% to first-time job seekers. 

Increase in entrepreneur income, enabling better access to health, education, and household services. 

End-to-end digital platform for operational efficiency. 

Use of machine learning algorithms for data-driven decision-making. 

Automated processes for loan disbursement and collections. 

Targets sole proprietorships and partnerships in urban, peri-urban, and semi-urban areas. 

Many customers lack formal education, property ownership, and access to traditional financial services. 

Various business loans including long-term working capital, machinery purchase, short-term working capital, bill discounting, and invoice financing. 

MSMEs employ over 110 million people and contribute significantly to India's GDP and manufacturing output. 

There is a large unmet demand for credit in the MSME sector, particularly for micro enterprises. 

Challenges include lack of collateral, low formalization of businesses, and reliance on informal lending. 

Fast turnaround time for loan disbursement. 

Risk-based pricing and unbiased decision-making. 

Omni-channel distribution and robust sourcing through branch networks and digital channels. 

Conducts Exploratory Data Analysis (EDA) on financial institution data. 

Utilizes supply-chain data to develop credit models within three days. 

Automates the entire credit risk value chain, including instant loan approvals. 

Achieves high performance across multiple metrics, including an 80+ GINI score and high accuracy in credit models. 

Processes 50 times more applications daily with processing times under 0.5 seconds per application. 

Reduces loss rates by 5-10 points and supports significant growth, from 1,000 to over 40,000 applications in one year. 

Addresses issues such as recurring defaults, manual processing limitations, and lack of reliable credit data. 

Provides solutions for scaling lending portfolios, particularly for MSMEs and agri-finance sectors, by integrating alternate data sources and automating credit assessments. 

Serves clients across 14 countries, including Singapore, Philippines, Australia, India, UAE, Kenya, and Nigeria. 

Clients span various financial services sectors, including banks, NBFIs, fintechs, digital banks, and micro-lenders. 

Offers a no-code, API-based platform for real-time decisioning and model deployment. 

Utilizes advanced AI and ML techniques for data ingestion, transformation, feature engineering, and model validation. 

Ensures high accuracy and efficiency in credit decisioning, reducing total cost of ownership by approximately 80%. 

Highlights successful implementations in unsecured lending, agri-finance, and embedded finance for MSMEs. 

Demonstrates significant improvements in approval rates and reduction in loss rates for clients. 

Plans to incorporate wider and real-time data sources for agri-finance, including agronomic data, remote-sensing data, and market data.