Agent 05 · Fintech
ComplianceBot Agent
Finds misclassified NPAs and missing KFS, then drafts the regulatory return.
ServiceLendFlowLangGraph + CrewAI
One offline run on demo data with planted problems (recorded platform test, November 2026).
- Client problem
- Asset classification errors and missing Key Fact Statements create regulatory risk at month end.
- What it does
- Checks the 90-days-past-due rule against each loan's asset class, confirms the Key Fact Statement was issued, and catches negative outstanding balances.
- How it heals
- Reclassifies assets with an audit note, drafts the return CSV, and a CrewAI analyst-fixer-reviewer team writes the summary.
- Human gate
- The return is a draft; compliance signs and files it.
- Typical buyer
- NBFC compliance and finance teams
- Built with
- LangGraph self-healing loop with a CrewAI crew (analyst, fixer, reviewer)
- Demo data
- Synthetic loan book.
- Tables
- loan_book ← synthetic
- Target outcome
- Target: month-end prep from days to hours.
- Path to production
- Service engagement; mapped to the client's loan system.
| Issue | Risk | Proposed fix | Count |
|---|---|---|---|
| out_of_range_outstanding outstanding=-11100.0 outside [0, None] | low | Quarantine and reconcile with the general ledger | 3 |
| asset_misclassified DPD 120 but classified 'Standard' | medium | Reclassify as NPA per 90-DPD rule | 6 |
| kfs_missing Key Fact Statement not recorded as issued | medium | Trigger KFS issue to borrower and record acknowledgement | 40 |
How we demo it
- Load a 3,000-loan book with planted misclassifications.
- Run ComplianceBot: corrected classes and a draft return.
- Show the reviewer agent's sign-off notes.
Built on AWS
Runs in the platform container on EC2 Graviton (or on demand in Lambda), writes healed tables to the S3 lakehouse, uses Amazon Bedrock only to write explanations, and reports six metrics to CloudWatch.
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