01
Scattered data
Credit limits in ERP, payment behavior in AR, sentiment in CRM.
Know your customer before every decision.
Payment score, exposure, sentiment, and order history — unified in the context graph for every O2C decision.
Payment scoreExposure trackingSentiment signals
Traditional Flow
02
Static scores
Credit ratings updated quarterly — not at decision time.
03
No exposure view
Open orders, invoices, and pipeline not aggregated.
04
Reactive risk
Problems discovered after payment failure, not before.
Where it breaks
- Credit decisions use stale customer profiles.
- Exposure calculation misses open orders and pipeline.
- Sentiment signals from support and sales never reach credit.
- No unified customer graph for cross-functional decisions.
The solution
Customer Graph
Unified node linking orders, invoices, payments, and interactions.
Dynamic Payment Score
Updated continuously from payment behavior and patterns.
Exposure Aggregation
Open AR, pipeline, and credit limit in one view.
Sentiment Integration
Support tickets and sales notes inform risk assessment.
Tier Classification
Policy-driven customer tiers with automated rule application.
Trend Detection
Early warning on deteriorating payment patterns.
Live scenario — Exposure before the hold
A repeat customer places a $50K order. Vyasa aggregates open AR ($120K), pipeline ($80K), and credit limit ($200K) — exposure at 100%. The order routes to credit review with full customer graph: 18-month payment history, two prior overrides, and a recent support escalation. Context, not just a limit check.
CreditSalesFinance
“Every customer decision starts with the full picture.”
Rollout
Weeks 1–4
Build customer graph from ERP and AR data.
Weeks 5–10
Dynamic payment score and exposure aggregation.
Quarter 2+
Sentiment integration and trend detection across O2C.
See what 70% looks like on your numbers.
30 minutes. No pitch. No commitment. We'll model your specific situation.