AI Agents

Context

Designed for insurance within the Underwriting assessment stack, this agent is used when life applications require verification of stated income and occupation before pricing and decisioning. Typical scenarios include new policies and endorsements where financial suitability and risk class depend on accurate earnings, employment type, and job-risk classification.

What it does

The agent reads the application and supporting evidence to validate income and occupation. It extracts earnings from payslips, employment contracts, and bank statements where provided; checks consistency of employer, role, tenure, and employment type; and aligns the declared occupation to the insurer’s job-risk taxonomy. Discrepancies—overstated income, mismatched employer details, or misclassified occupations—are flagged with a concise rationale and links to the exact pages used, so reviewers can confirm and correct quickly.

Core AI functions

Document detection and parsing for payslips, contracts, and bank statements; OCR and field extraction for income amounts, dates, employer identifiers, and role titles; normalization of pay frequency and annualization; occupation mapping to approved risk categories; cross-document consistency checks between application and evidence; and reason-code generation with page-level lineage for every pass/flag.

Problem solved

Overstated income and misclassified occupations lead to incorrect risk assessment and downstream corrections. Manual checks are slow and inconsistent, creating rework and avoidable delays.

Business impact

Underwriting becomes faster and more accurate: income and occupation are evidenced early, pricing reflects true risk, and complaint and rework rates fall thanks to traceable, document-linked conclusions.

Integration and adjacent use cases

Integration complexity: Low–Med. The agent ingests PDFs or scans from portal/agent capture, email, or DMS and writes structured findings and evidence links into the underwriting workbench or policy admin; no core changes are required.

Common combinations in this stack include:

• Medical questionnaire analyzer (to structure applicant responses),

• Health history & diagnostic validator (to verify medical disclosures),

• Risk tier assignment agent (to translate verified health and occupation into a tier recommendation),

• Asset & usage pattern extractor (for non-medical context when relevant), and

• Manual exception escalation wrapper (to route edge cases with a complete evidence pack).