Malem

A borrower’s repayment capacity cannot be looked at in isolation.

Under RBI’s Regulatory Framework for Microfinance Loans, regulated entities must have a board-approved policy limiting a household’s monthly loan repayment obligations to **a maximum of 50% of monthly household income**. The calculation takes into account the household’s outstanding loans and the loan under consideration.

This is important because credit risk is not simply about whether a borrower has income.

It is about whether the **household’s total repayment burden remains sustainable**.

For MFI operations, that also makes disciplined post-disbursement monitoring important.

When repayment commitments are made, someone needs to know:

**What was promised?
On what date?
Was the commitment fulfilled?
What happens when it wasn't?**

Recova AI focuses on that follow-up layer—turning logged Promise-to-Pay commitments into scheduled borrower reminders through WhatsApp, SMS and reminder calls.

**RBI sets the repayment-capacity framework.
Strong operations determine how consistently repayment commitments are followed up.**

A field officer may have dozens—or hundreds—of borrower commitments to remember.

“Pay on the 10th.”

“Pay on the 12th.”

“Pay after the market day.”

“Pay this Friday.”

The operational risk is simple:

**A commitment that is not tracked can become a missed commitment.**

Recova AI is built around this exact workflow.

When a field officer logs a Promise-to-Pay, Recova AI schedules the follow-up for the committed date and can reach the borrower through **WhatsApp, SMS and reminder calls**, with a payment QR available in the reminder flow.

The goal isn't to replace the collections officer.

It is to remove repetitive date-tracking from the officer's workload so the team can spend more time on cases that actually require human judgment.

For an MFI, the question is worth asking:

**How many repayment commitments are currently being tracked by memory, notebooks, spreadsheets or scattered messages?**

That is an operational problem worth measuring.

Trending🔥

📚 3 Reasons Why Manual Loan Recovery Is Still Failing MFIs in 2026

Running an MFI or NBFC? Here's what the latest numbers are telling us:

1️⃣ Scale is impossible manually
India has 627 lakh active microfinance borrowers (FY2025, Economic Survey 2025–26). The total MFI loan portfolio stands at ₹3.38 lakh crore as of March 2026. No team of agents can follow up with crores of borrowers on time, every time.

2️⃣ The NPA crisis is real and growing
The GNPA ratio of India's microfinance sector jumped from 8.8% in FY2024 to 16% in FY2025 — nearly doubling in just one year. Overall stress (SMA + GNPA + write-offs) surged to 15.3% in FY2025 from 5.9% in March 2024. Delayed and unstructured follow-up is a core reason.

3️⃣ Delayed follow-ups are costing crores
Early, consistent, and respectful borrower communication is the single biggest lever to prevent a loan from going NPA. Yet most MFIs still rely on field agents, phone calls, and WhatsApp — with zero personalization at scale.

🔑 What AI debt recovery does differently:
✅ Contacts borrowers at the right time using predictive scheduling
✅ Sends personalized voice/text reminders in local languages
✅ Flags high-risk accounts before they default
✅ Reduces operational costs by 30–50% and increases collector productivity by 2–4x
✅ Frees your field agents to focus on complex cases only

This is exactly what Recova AI is built to solve — for MFIs and NBFCs across India.

📩 DM us if you want to see how it works.

In many MFIs and NBFCs, paying an overdue instalment still means calling a loan officer, visiting a branch, or waiting for a field staff visit. Every extra step adds friction and delays — and friction kills repayments.

Modern lenders see the opposite effect when they offer self‑serve, digital payment options (online, mobile, text-to-pay, etc.): borrowers can pay anytime, from anywhere, without waiting for staff. Institutions that integrate multiple digital payment methods and channels report higher collection rates because payments become more convenient and accessible for different borrower profiles.

On top of that, self‑service tools and digital payments reduce operational costs: fewer manual transactions, fewer cash-handling risks, and less time spent chasing small overdue amounts in person.

At Recova AI, we’re building an AI‑driven follow‑up layer that nudges borrowers on their preferred channels and can plug into digital payment flows, so your team spends less time on reminders and more time on high‑value cases.

If you’d like a simple checklist of “What to digitise first in your collections process”, comment “DIGITAL” or DM us, and we’ll share it with you.

We are inviting 2 retired bank managers to join Recova AI as advisors
Apply here: www.malemlabs.com/advisor
Learn more: www.malemlabs.com/advisor
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Call: 8974898579
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