Commercial Debt Registry Software
Minimize trade risk with Garxly's centralized debt registry. Zero-trust credit tracking for Global agricultural trade.
Secure Your TradeAdvanced Risk Engines
Protect your capital with data-backed credit decisions.
Cross-Firm Alerts
Get notified if a buyer has defaulted with other firms in the network. Stop supplying to defaulters before they crash.
Risk Scoring
Dynamic risk scores (0-100) based on payment history, bounce rates, and trade volume. Updated daily.
Behavioral Scoring
Analyze buying patterns to predict potential defaults. Sudden spikes in credit utilization are flagged as warning signs.
Zero-Trust Credit
Control credit limits dynamically based on real-time registry data. Set system-wide caps for risky categories.
KYC Verification
Store and verify digital copies of PAN, Aadhar, and GST certificates for all your counterparties.
Legal Evidence
Maintain digital ledgers that can be used as evidence in arbitration or legal disputes under Sec 138.
What is a Commercial Debt Registry?
A Commercial Debt Registry is a shared database where trading firms record outstanding dues and payment behaviors of their buyers. Unlike traditional bank CIBIL scores, this registry focuses on B2B trade credit, which is often informal and undocumented.
Why It Matters
In Global agricultural trade, credit is the lifeblood of business. However, "rolling bad debt" (taking goods from one trader to pay off another) is common. Garxly's registry identifies these patterns instantly.
Risk Scoring Model
Our proprietary algorithm takes into account:
- Payment Delays: Average days overdue (DPD - Days Past Due).
- Bounce Rate: Frequency of cheque bounces or NACH failures.
- Utilization: Percentage of credit limit used across the network.
- Vintage: How long the buyer has been in the market.
Who uses our Debt Registry?
Commission Agents
To vet new buyers coming to the mandi. Avoid 'fly-by-night' operators.
Wholesalers
To manage credit limits for hundreds of retail shopkeepers.
NBFCs & Lenders
To assess alternative data for lending to the informal sector.