Engineering an autonomous risk orchestrator to ingest real-time cash-flow and ERP metadata—unlocking credit access for underbanked SMEs while maintaining strict Basel III compliance.
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High-volume digital lending requiring rapid decisions on thin-file applicants without traditional bureau depth.
Risk Architect + 2 Data Engineers + MLOps Lead embedded within Credit Operations and Risk Compliance.
Transitioning from manual, multi-day reviews to sub-minute autonomous triage and scoring.
Event-driven ERP/Bank connectors, Entity Resolution, and Gradient Boosted models with immutable logs.
The client’s underwriting stack relied on traditional bureau-heavy scoring. This created a structural bias against 'thin-file' SMEs—businesses with high cash flow but limited credit history. 50% of legitimate applications were rejected or pushed to 7-day manual reviews.
The friction was commercial: high-quality SMEs churned to faster alternative lenders before the manual review was complete. The enterprise required a system to ingest non-traditional signals (ERP, Tax, Utilities) to verify creditworthiness without increasing default risk.
Reliance on credit bureau scores and manual document uploads (tax returns).
Real-time cash flow, sequence, and peer-group anomalies ingested via API Mesh.
Fragmented review logs with inconsistent justification for credit decisions.
Immutable logs containing the exact feature state at the time of the decision.
Queue spikes caused significant borrower drop-off during peak cashflow windows.
Autonomous Straight-Through Processing (STP) for 62% of applicants.
Centralized ingestion of recurring SaaS revenue, supply chain reliability, and utility stability features updated per transaction.
Automated decision narratives satisfy banking regulators by explaining 'Why' thin-file applicants were approved.
The AI orchestrator routes only borderline cases to humans, auto-approving high-confidence prime and thin-file leads.
Pre-built logic for secure SME identity-linkage across disparate ERP and banking environments.
Production-ready templates for rapid cashflow velocity and repayment-propensity engineering.
Real-time monitoring for approval funnel health, p95 latency, and model drift dashboards.
Automated policy-limit adjustment to protect portfolio quality during volume spikes.
Underwriting orchestration removed manual bottlenecks, reducing time-to-decision from days to sub-minute windows.
Autonomous triage allowed the same underwriting team to process a 3x increase in application volume.
Architecture ensures sub-20ms decisioning, maintaining zero impact on applicant session persistence.
Client Testimonial
Coretus didn’t just automate a process — they built a governed decisioning engine that unlocked a market we previously couldn’t serve. Our approval velocity spiked by 4.2x without a single compromise on risk policy.
Head of Credit Risk & Underwriting