The impact

This is where compliance programs quietly break down. Not through deliberate shortcuts, but through variable human judgment compounding across thousands of cases: two reviewers screening the same applicant reach different conclusions depending on which transliteration variant they search, which watchlist they check first, and how much time pressure they face.

This agent enforces a single verification standard regardless of volume, origin, or workload. It extracts identity details, screens against AML, PEP, and sanctions databases, surfaces discrepancies, and records every check in an auditable trail before the application progresses.

How it works

• Extracts and cross-references identity and address details from passports, national IDs, driving licenses, utility bills, and bank statements, including transliterated names, non-Latin scripts, and non-standard address formats
• Screens against AML watchlists, PEP datasets, and sanctions regimes in real time vai API, with jurisdiction-aligned logic, and resolves near-match false positives from transliteration variants, common name overlaps, or outdated list entries using configurable disposition logic
• Records every verification check, screening result, and disposition in a complete audit trail that regulators can reconstruct independently

Why it matters

KYC deficiencies are among the most common triggers for enforcement actions in consumer lending. A single remediation program can consume tens of millions in direct costs and tie up senior management for years, while re-verifying previously approved borrowers is orders of magnitude more expensive than getting it right the first time. The gap between "we check everyone" and "we can prove we checked everyone consistently" is exactly where regulators focus. This agent closes that gap at scale: verification quality does not degrade under volume, screening does not vary by reviewer, and every decision is provably governed.

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The impact

Lending decisions rest on financial facts that are rarely presented cleanly. Income is buried in payslips that vary by employer and jurisdiction, employment details appear across multiple document types, and cash-flow signals are spread across bank records with inconsistent formats. 

Underwriters typically scan, extract, and interpret figures manually, introducing variability that becomes portfolio risk and often remains invisible until performance drifts months later.

This agent establishes a reliable financial record by extracting and validating personal and financial data from source documents, normalizing values into standard representations, and flagging missing, conflicting, or implausible data before credit evaluation proceeds.

How it works

• Extracts income, employment, and financial fields from payslips, tax documents, income statements, and bank records across country-specific formats, including non-Latin scripts and non-standard layouts where fields use local terminology with no direct English equivalent
• Handles multi-source income scenarios: a borrower with revenue from two businesses, a rental property, and part-time employment has all sources normalized into a single affordability picture aligned with your credit policy's income treatment rules
• Flags declared income that does not align with deposit patterns, overlapping employment dates, and expense-to-income ratios outside plausible ranges, blocking progression until discrepancies are resolved

Why it matters

Inconsistent extraction creates inconsistent risk inputs, which creates inconsistent credit decisions, which creates a portfolio whose actual risk profile diverges from what was modeled. That divergence surfaces as unexpected loss rates, repricing events, and regulatory capital adjustments. This agent removes uncertainty at the source: every document, regardless of format, language, or complexity, is processed through the same extraction and validation logic, creating a dependable foundation for faster decisions and consistent risk judgment.

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The impact

This agent executes credit scoring exactly as your policies define it, deterministically, every time, across every application. It takes verified applicant data, applies your connected scoring models and affordability rules, and produces a clear eligibility outcome with supporting risk signals, without reinterpretation or variation based on who reviews the case or when.

How it works

• Applies internal and external credit scoring systems using governed logic so the same applicant profile produces the same score regardless of timing, office location, or reviewer, including scenarios where bureau data originates from one country while the applicant applies in another 
• Calculates affordability ratios, debt-to-income metrics, and risk indicators consistently, flagging the specific drivers and their interactions rather than surfacing a single aggregate score
• Produces explainable recommendations with confidence indicators so reviewers focus on cases that warrant genuine judgment, not recalculation

Why it matters

Credit portfolios drift through small inconsistencies that accumulate: thresholds applied unevenly, borderline cases accepted under pressure, model updates rolled out inconsistently. When portfolio risk diverges from what was modeled, the institution faces repricing, increased regulatory capital requirements, and, in securitized portfolios, investor scrutiny that constrains future issuance. This agent prevents drift at the point of decision. Credit evaluation is locked to one standard across applications, offices, and jurisdictions, so margins are protected as volume grows and every approval is explainable.

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The impact

This agent governs whether a lending decision is permissible to stand. It applies compliance rules deterministically, detects breaches before approval, and produces regulator-ready records without retroactive reconstruction.

How it works

• Applies country-, product-, and policy-specific compliance rules to every decision, including requirements that vary by applicant segment, channel, and jurisdiction, such as a product compliant in one market but requiring additional disclosures in another
• Blocks progression on breaches, threshold violations, or documentation gaps until resolved, rather than relying on post-hoc review
• Captures complete decision context in real time and produces regulator-ready logs aligned with GDPR, DORA, and local consumer lending requirements, structured so supervisory reviewers can reconstruct any decision independently

Why it matters

Compliance failures are dangerous because they often surface months or years later, when teams must explain decisions under rules that may have changed, using evidence that may not have been captured.

Reconstruction is where institutions hemorrhage resources. A single request can trigger manual evidence gathering across logs, threads, and recollections, and scaled across examinations, that becomes a multi-million-dollar remediation drain.

This agent makes reconstruction unnecessary. Compliance evidence is produced as an inherent output of every decision, enabling growth without turning audits and supervisory reviews into existential events.

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The impact

This is where internal decisions become external commitments. The borrower who receives a conditional approval with terms that contradict the portal does not call to clarify. They close the tab and apply elsewhere.

This agent finalizes outcomes, generates decision communications, synchronizes every system, triggers the next binding steps, and records everything in a single controlled motion.

How it works

• Synchronizes updates across portals, case systems, CRM, and downstream workflows so every system reflects the same terms, status, and conditions at the same moment
• Generates decision documents aligned with terms, disclosure requirements, and jurisdiction-specific standards for approval, conditional approval, or rejection outcomes
• Triggers contract execution, direct debit setup, or payout workflows without manual handoffs or batch processing delays
• Records communications, system updates, and action steps from decision through execution, creating full traceability for every commitment

Why it matters

Every dropped borrower at the post-decision stage represents the full acquisition and processing cost with zero return. A 48-hour lag in the approval letter, a portal still showing "under review," or an omitted jurisdiction-specific disclosure can lose the borrower permanently. Across thousands of monthly decisions, even a small coordination failure rate translates into significant revenue leakage. This agent closes the loop: decisions are communicated clearly, executed correctly, and traceable long after the fact.

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