Identity checks, employment verifications, and credit pulls were handled through separate systems. Manual coordination between these processes created delays and increased the risk of data mismatches.
Federal requirements for SSA‑89 consent and Social Security Number verification mandated precise consent tracking, secure data handling, and detailed audit trails.
Incomplete or inconsistent verification exposed the lender to identity fraud, especially during high‑volume lending periods.
Employment verification (The Work Number), credit bureau reports (Experian), and other checks were siloed, requiring repetitive data entry and creating potential for human error.
The end‑to‑end verification process could take several days, slowing loan approvals and frustrating customers.
Reduced total verification time from 2–3 business days to under 3 minutes.
Early mismatch detection reduced fraudulent application approvals by 70%.
Automated consent tracking and detailed API call logs ensured SSA‑89 and federal audit readiness.
Parallelized API calls and automated decisioning increased loan processing capacity without additional staffing.
Easily adaptable to integrate new data sources, such as alternative credit scoring APIs.
Potential to layer predictive analytics on aggregated verification data to further improve decision accuracy.
Could provide tamper‑proof consent records for regulatory and customer transparency.
By automating SSA‑89 Social Security verification and integrating it with multiple external verification services, the client transformed its loan applicant screening process. The result was faster decisions, stronger fraud prevention, and full regulatory compliance — without adding operational overhead. This case study illustrates how API orchestration within a BPMN framework can deliver measurable value in financial services.
Capital BPM is the leading provider of Camunda-based process management consulting, training and implementation services.
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