Underwrite Smarter, Disburse Faster Than Ever
Digital lending in India is projected to hit $515 billion by 2030. But most lenders still rely on manual credit assessment, paper-based verification, and collection teams that call from spreadsheets. Our platform automates the entire lending lifecycle — from lead capture to recovery.
Lending Bottlenecks That Kill Growth
Every manual step in your lending pipeline is a customer you might lose to a competitor who disburses in minutes.
Manual Underwriting
Credit analysts manually review bureau reports, bank statements, and ITRs — adding 2-3 days to every application.
Thin-File Borrowers
Traditional credit scores miss 300M+ Indians with no bureau history. Without alternative data models, you leave money on the table.
Inefficient Collections
Collection agents work from static call lists with no prioritization — burning time on borrowers who would have paid anyway.
Bureau Integration Woes
Connecting to CIBIL, Experian, CRIF, and Equifax requires separate integrations, each with different APIs and SLAs.
DLG & FLDG Complexity
Digital Lending Guidelines and First Loss Default Guarantee regulations add compliance layers that most lending stacks were not designed for.
Portfolio Monitoring Gaps
Monthly MIS reports catch deterioration too late. By the time you see rising DPD buckets, NPAs are already forming.
Full-Stack Lending Automation
From application to recovery — every stage of the lending lifecycle, automated and compliant.
Want to disburse loans in under 10 minutes?
See how our AI underwriting engine processes applications in real time — book a live demo today.
Lending Platform Results
Aggregated outcomes from 12 NBFC and digital-lending deployments over the last 18 months.
ROI Breakdown
Three areas where lending platforms see the fastest payback.
Lending Compliance Framework
Built for the regulatory reality of Indian digital lending.
Why Lenders Trust OpenMalo
We have built lending automation for NBFCs, fintechs, and co-lending platforms across India.
Get Your Lending Automation Blueprint
Tell us your loan products, volumes, and pain points — we will build a custom automation roadmap.
Case Study
How a Digital NBFC Cut Defaults by 45%
A mid-size NBFC disbursing ₹200 Cr/month in personal and SME loans was seeing a 6.2% default rate — well above the industry benchmark of 3.5%. Manual underwriting could not scale with application volume, and collections were reactive rather than predictive.
The Problem
The NBFC was growing fast but losing control of credit quality:
Our Approach: We deployed an AI underwriting engine that blends bureau scores with bank-statement analytics and GST data for richer risk assessment. Auto-decisioning handles 78% of applications without human review. A predictive collections engine starts engagement at 1 DPD with WhatsApp reminders and escalates to agent calls only for high-risk accounts. Co-lending data flows were automated with partner-specific reporting. Full deployment took 9 weeks.
Read Full Case StudyWhat Our Clients Say
“Our default rate dropped from 6.2% to 3.4% within two quarters. The AI catches circular transactions and cash-flow anomalies our analysts were missing.
“We went from 400 to 3,000 applications per day with the same team. Disbursement in under 8 minutes is our new normal.
“The WhatsApp collection bot recovered ₹2.3 Cr in its first month — borrowers actually prefer paying through chat over calls.
Frequently Asked Questions
Personal loans, business loans, SME lending, LAP, gold loans, microfinance, BNPL, and invoice discounting. Each product type has configurable underwriting rules, approval matrices, and documentation requirements.
Explore Related Industries
Discover how we serve similar verticals with tailored technology solutions and deep domain expertise.
