The Sunday Draft

Origin: Domestic Trade Finance Exchange | TReDS Platform | Credit & Risk Workflow

Context

As part of building the regulated Trade Receivables Discounting System (TReDS) platform, we needed to streamline how credit was managed across multiple participants—sellers, buyers (anchors), and financiers—within an invoice factoring marketplace ecosystem.

TReDS facilitates financing of receivables through bidding by financiers on invoices uploaded by MSME sellers. These invoices are backed by purchase confirmations from large enterprises (anchors), and all funds flow through NACH debit mandates. Ensuring proper credit management was essential for trust, compliance, and smooth operations.

Problem / Opportunity

We needed a system that could:

• Track and control real-time credit exposure across the platform
  
• Distinguish credit limits across different buyer entities under one anchor
  
• Link limits effectively with sellers and financing products (factoring or reverse factoring)
  
• Allow financiers to manage risk without manual intervention
  
• Prevent bid failures due to outdated or misaligned credit limits
  

Building this layer correctly was essential for operational stability, financier trust, and regulatory scrutiny.

How We Envisioned the Solution

As the product lead for this initiative, I was responsible for end-to-end conceptualization and execution—translating complex risk practices into digital workflows and scalable system architecture.

This involved:

• Deep engagement with financiers to understand credit allocation logic
  
• Working with engineering and compliance to design an auditable backend
  
• Driving product decisions across configurability, transparency, and automation
  
• Simplifying complex rules into usable platform features
  
• Leading go-to-market and rollout readiness
  

Approach & Decisions

We solved the problem by asking five key product questions:

a. Where should credit exposure be tracked?

We defined four key tracking dimensions:

• Platform-level: Total exposure financier is willing to commit on TReDS
  
• Buyer-level: Entity-specific cap under each anchor (based on creditworthiness)
  
• Seller-level: Seller-specific limits to prevent over-concentration
  
• Product-level: Split between factoring and reverse factoring limits
  

This hierarchy ensured fine-grained risk control and enabled easy adjustments when policies changed.

b. How should limits adjust as transactions progress?

We built a real-time recalculation engine that responded to:

• Bid placement
  
• Bid acceptance
  
• Disbursement confirmation
  
• Repayment via NACH
  

This meant financiers always saw updated exposures and could act without fear of breach.

c. What happens if credit is insufficient?

We designed smart failure flows—alerts guided users to resolve issues, and maker-checker override flows allowed approvals under policy exceptions.

d. How configurable should it be?

We created configurable templates so financiers could define rules by buyer profile, risk flags, invoice tenor, and historical repayment. This empowered scale and repeatability.

e. How will users gain visibility?

Each stakeholder had access to tailored dashboards:

• Financiers: real-time credit utilization and alerts
  
• Buyers / Anchors: visibility into usage by their entities and sellers
  
• Sellers: limit status and invoice eligibility
  

This reduced support dependencies and drove user confidence.

Platform Outcomes and Product Impact

The credit limit logic became a foundation layer that enabled multiple benefits:

• 95%+ bid success rate, minimizing operational friction
  
• Zero limit breaches post-launch, supporting risk compliance
  
• 30% faster credit evaluation time through automated rules
  
• Supported scaling to 500+ sellers and 100+ buyers within 3 months
  
• Enabled downstream features like auto-bidding and ERP-integrated validations
  

Risks & Challenges Addressed

• Overexposure: Real-time recalculations with platform-level limits protected against breaches
  
• Complex Anchor Org Structures: Proper mapping of buyer subsidiary entities to Parent Anchor.
  
• Rule Fatigue: Configurability was counterbalanced by defaults, templates, and validations
  
• Audit Readiness: We built in traceable logs, checker approvals, and export-ready reports to meet RBI and audit standards
  

Product Learnings with Broad Applicability

This module revealed product patterns that apply well across complex fintech and B2B platforms:

Use layered exposure models

Mapping limits at multiple levels (platform, buyer, seller, product) balances flexibility and control—vital in lending, payments, and insurance ecosystems.

Automate recalculations at trigger points

Real-time recalculation on event triggers (e.g., bid, disbursement) eliminates reliance on batch jobs or manual tracking.

Separate rule configuration from execution

Allowing stakeholders to set rules but automating execution builds trust, especially in regulated domains.

Align visibility with stakeholder roles

Dashboards tailored by role reduce operational load and help users self-serve, especially in multi-party platforms.

These principles shape how I continue to lead and scale financial products built on trust, automation, and platform discipline.

Conclusion

Designing the credit limit workflow was an exercise in translating nuanced financial logic into clear, actionable system behavior. By mapping exposure across relevant dimensions and automating updates at key transaction points, we built a system that supported informed decisions and operational flow. In ecosystems with multiple stakeholders, aligning product behavior with each participant’s perspective creates consistency that benefits everyone.