Supplier Passport
Problem
Finance teams lack visibility into vendor identity, bank account ownership, and verification history.
Risk
Payments to fraudulent accounts, duplicate vendors, or sanctioned entities.
How TrustRelay prevents it
AI-powered document extraction validates W-9s and insurance certificates automatically. Intelligent duplicate detection catches entity variations. Enhanced sanctions matching with fuzzy name resolution finds hidden matches.
Target:Identity verified before first payout
Payout Policy Engine
Problem
Payment approvals happen in ERP without real-time context on vendor status, bank changes, or risk signals.
Risk
Paying compromised accounts, missing fraud signals, violating internal controls.
How TrustRelay prevents it
Real-time risk scoring combines vendor history, bank change patterns, and network signals. Transparent rules with explainable decisions. Every hold or denial includes human-readable reasoning for audit.
Target:Policy enforced on 100% of payouts
Reconciliation Studio + Evidence Vault
Problem
Reconciling bank outcomes to GL entries is manual, error-prone, and lacks audit-ready evidence.
Risk
Unreconciled exceptions, delayed close, failed audits, unclear liability.
How TrustRelay prevents it
ML-assisted matching pairs bank lines to payout intents with confidence scoring. Exceptions are ranked by likelihood for faster resolution. Immutable evidence captures every decision with full context.
Target:Auto-reconcile ≥ 90% of transactions
Risk Graph Intelligence
Problem
Each payout is evaluated in isolation. Network-level fraud patterns and risk signals are invisible.
Risk
Missing sophisticated fraud, slow detection, reactive rather than predictive controls.
How TrustRelay prevents it
Machine learning detects emerging fraud patterns across the TrustRelay network. Predictive risk models learn from real payment outcomes. Every insight is explainable and feeds back into transparent policy rules.
Target:Network effects compound over time