AI Agents

Context

Built for banking in the Commercial lending stack, this agent is used when preparing SME and corporate credit files to confirm the borrower’s legal structure and ownership before analysis proceeds. Typical scenarios include new facilities, renewals with structural changes, and group lending where multiple related entities (parents, subsidiaries, SPVs) participate in the transaction.

What it does

The agent reads the corporate pack—register extracts, articles, share registers/certificates, organizational charts, and recent filings—and produces a structured view of the legal entity and its shareholding. It standardizes legal names, IDs, jurisdiction, and registered address; captures shareholders and their percentages; and reconciles ownership across documents. Where relationships involve intermediate entities, it compiles the chain so the effective ownership at the borrowing entity is clear. Findings are linked to the exact document page used, giving reviewers a single, auditable source of truth for structure and ownership.

Core AI functions

Document type detection and OCR tuned for corporate records; entity extraction for legal names, identifiers, jurisdictions, and addresses; shareholder/percentage capture with normalization of share classes; cross-document consistency checks (register vs. articles vs. filings); and graph assembly for direct/indirect holdings. Confidence scoring highlights low-certainty or conflicting elements and generates targeted exceptions (e.g., missing register page, unstated class, percentage mismatch) so clarifications are precise and fast.

Problem solved

Legal structure and ownership are often incomplete or inconsistent across submissions, forcing analysts to reassemble evidence by hand. Gaps in shareholding detail and unclear relationships delay covenant setting, KYC, and security documentation.

Business impact

Credit preparation moves faster with a clear, evidenced structure. Analysts and approvers rely on a consistent ownership view, downstream documentation (guarantees, security, covenant parties) is aligned on the first pass, and auditability improves because every field has document-level lineage.

Integration and adjacent use cases

Integration is light–moderate: ingest documents from portal/email/DMS; write the standardized entity profile and ownership table into the lending workflow or credit workbench; no core changes required.

Common combinations in this stack include:

• Financial statement analyzer (for standardized historicals and ratios),

• Business plan & use-of-funds validator (to verify purpose and KPIs),

• Contract & revenue stream verifier (to tie projected cash flows to agreements),

• Collateral & security package validator (to align parties and encumbrances),

• Cash-flow & repayment capacity (DSCR) (to assess servicing), and

• Commercial lending completeness agent (to confirm the pack is committee-ready).