mooScoreTM – Powering Credit Decisions for India’s Dairy Farmers

Introduction

India’s dairy sector is home to over 80 million smallholder farmers, many of whom remain excluded from formal financial systems due to lack of documented income or credit history. Traditional credit models often fail to evaluate such borrowers, restricting their access to credit. mooPay, the fintech arm of Stellapps, launched mooScore™, a groundbreaking credit scoring system designed specifically for dairy farmers. By leveraging data such as milk pouring patterns, milk quality, farmer consistency, and dairy engagement—combined with demographic and bureau data—mooScore empowers lenders with actionable insights while enabling farmers to access formal credit.

What is mooScore^TM

mooScore™ is a proprietary credit risk score tailored for India’s dairy farmers. Unlike conventional scores, mooScore evaluates:

• Milk pouring behaviour: Regularity, quantity, quality (FAT/SNF), and earnings.
• Demographic data: Pin code, state, and dairy affiliation.
• Credit history (if available): Bureau variables from Equifax.

Scores range from 300 to 900, where a higher score indicates lower risk of becoming 60+ days past due (DPD) within 9 months. mooScore helps lenders assess new-to-credit (NTC) borrowers and bridge the gap between rural dairy activity and formal credit access.

Why mooScore^TM matters

In a country where millions of smallholder dairy farmers remain underserved by traditional finance, mooScore™ brings a paradigm shift by enabling fair, data-driven credit access. Here’s why mooScore is a game-changer:

• Credit inclusion for farmers with limited or no financial history
• Alternative data insights from real-time milk pouring behaviour
• Automated underwriting: Up to 40% of cases can be auto approved
• Lower default rates: As low as 1.93% for approved farmers
• Custom design: Built for seasonal, behavioural, and regional nuances

By converting operational dairy data into credit intelligence, mooScore enables lenders to confidently extend credit to underserved rural borrowers.

The Journey: mooScore™ v1.0 to v2.0

Launched in 2019, mooScore v1.0 introduced alternative data lending to dairy farmers. It achieved 40% auto-approvals with a 1.93% default rate and successfully onboarded 60% of NTC borrowers. However, changing borrower behaviour and increased loan volumes reduced model accuracy.

In response, mooScore v2.0 (2024) was built in collaboration with Equifax, analysing over 740,000 farmers and introducing advanced ML techniques (xGBoost, logistic regression). It features four customized models:

• mooScore 2.0: Based on milk pouring and demographics (for NTC farmers)
• Hybrid Retail Score: Combines milk data with retail credit bureau insights
• Hybrid MFI Score: Tailored for microfinance borrowers
• mScore: Uses only geographic data (pin code and state) for non-Stellapps farmers

These models offer enhanced predictability, risk segmentation, and financial inclusion.

How mooScore™ Works

mooScore™ is a credit scoring system built for rural realities—turning a farmer’s dairy activity into a reliable predictor of their creditworthiness. Instead of relying solely on traditional banking data, mooScore uses a combination of milk pouring behaviour, demographic data, and where available, credit bureau records, to assess the likelihood of loan default. Here’s a step-by-step breakdown of how it works:

1. Data Collection:
   • Milk Pouring Data: Daily transactions from Stellapps’ dairy tech systems.
   • Credit Bureau Data: Repayment histories and account details from Equifax.
   • Demographics: Includes pin code, state, and dairy affiliation.
2. Variable Creation:
   • Milk Pouring Attributes: Regularity, Stellapps vintage, average and deviation in FAT/SNF content, milk rate, total income, max/min values, and derived ratios.
   • Credit Bureau Attributes: Delinquency, payment behaviour, balances, credit availability, number of accounts, credit utilization, and bureau tenure.
3. Model Development:
   • Uses logistic regression and xGBoost to predict the likelihood of default (60+ DPD in 9 months).
   • Models are tailored to different borrower segments.
4. Scoring and Risk Segmentation:
   • Converts predictions to a 300–900 score range:
     • 700+: Auto-approve
     • 550–700: Manual review
     • <550: Likely to be rejected
5. Lending Decisions:
   • Enables data-driven approvals
   • Supports credit access for underserved rural segments
   • Keeps defaults low and improves operational efficiency

Real Impact: Turning Data into Opportunity

mooScore™ is more than just an algorithm—it’s a financial enabler for India’s rural dairy ecosystem. By translating behavioural and operational dairy data into meaningful credit scores, mooScore is unlocking credit access for thousands of smallholder farmers who were previously invisible to formal financial systems.

Here’s how mooScore is making a tangible difference:

• 40% Auto-Approval: Faster turnaround with lower processing cost
• 60% NTC Farmers Approved: Default rates below 2.6%
• Low Risk Lending: Default rates as low as 1.48% with hybrid models
• Smarter Credit Expansion: Better targeting in rural and semi-urban areas
• Repeat Borrowing: Farmers show improved repayment and loyalty

Conclusion

As India continues its journey toward deeper financial inclusion, tools like mooScore™ are proving to be game-changers—bridging the gap between rural realities and formal finance. By using data that truly reflects a farmer’s daily livelihood, mooScore empowers lenders to make smarter, faster, and more equitable credit decisions, while giving dairy farmers a fair shot at economic growth. Looking ahead, mooScore will continue to evolve—incorporating richer datasets, refining predictive models, and expanding its reach across more geographies and farmer segments. As mooPay grows, mooScore will remain at the heart of its mission: to make credit accessible, reliable, and inclusive for every farmer in India’s dairy economy.