Infinity Data AI: AI-Enabled Collateral Management System
Transform fragmented collateral data into trusted, explainable, audit-ready decisions—at underwriting speed.
The Problem We Solve
Collateral data in modern financial organizations is fragmented across loan origination systems, core banking, custodians, third-party appraisers, market data feeds, and legal sources. In legacy, manual environments, key asset information is inconsistent, duplicated, often incomplete, and difficult to validate. Manual checks, static valuations, and inconsistent haircuts slow approval cycles, increase operational and regulatory risk, and expose the institution to audit gaps and model errors. In South Africa, these challenges are compounded by evolving South African Reserve Bank (SARB) and Basel III/IV requirements—forcing banks into an overly conservative stance or risking non-compliance.
Misclassified industries (SIC/NAICS) and stale appraisals quietly distort limits, haircuts, and concentration metrics—slowing approvals or creating avoidable compliance risk.
Our Solution
Infinity Data AI delivers a production-grade Collateral Management System that leverages an ontology-driven data model, embedding business logic into every data flow and decision. The platform orchestrates, enriches, and unifies collateral data from all sources, automating validation and compliance with embedded rule logic and AI Data Agents. With AI Data Agents (for autonomous quality checks, enrichment, and monitoring) and the Data Whisperer (plain-English, lineage-linked answers), business users finally work with decision-grade collateral data in their day-to-day activities. The result: real-time analytics for underwriting, monitoring, and governance—backed by a full audit trail and flexible enough to adapt to local regulation and business evolution.
What It Does
Unified Collateral Graph
Resolves entity, asset, lien, and exposure relationships into a single, governed layer—eliminating double-counting and aligning obligor ↔ facility ↔ asset ↔ lien coverage for committee-ready views.
Automated Data Orchestration & Enrichment
System-agnostic pipelines ingest structured and semi-structured data; enrich records with appraisal, market, and regulatory context; and preserve full lineage for every transformation (LOS/core, appraisers, public records/UCC, market/pricing, geospatial/catastrophe; optional sanctions/PEP for EDD alignment).
Decision Intelligence for Approvals
Loan-to-Value (LTV) calculators with stress overlays; jurisdiction-aware eligibility, haircuts, and advance-rate policy; concentration and wrong-way risk checks; exceptions routing with maker–checker. Results surface in interactive dashboards for underwriters, credit, and risk teams.
Industry Classification Governance (SIC/NAICS)
Normalizes and versions customer industry codes with confidence scoring; automatically propagates downstream policy/limit effects.
Dynamic Monitoring & Early Warning
Market volatility, reappraisal triggers, and stress overlays drive ongoing collateral eligibility assessments, producing real-time alerts on exceptions or deviations from required coverage.
Explainability & Auditability
Every input, transformation, rule, and outcome is versioned, timestamped, and fully traceable—ready for internal and regulatory scrutiny.
Human-in-the-Loop Controls
Supports industry-grade maker–checker workflows and attestation chains, with override and rationale tracking to meet model-governance standards.
Why It’s Better
Accuracy: Ontology-based mapping eliminates duplicates, reconciles mismatches, and maintains lineage integrity.
Reliability: SLA-backed pipelines, dynamic data-quality enforcement, and automated lineage keep data current, complete, and consistent.
Trustworthiness: Transparent rules and end-to-end evidence chains build confidence with credit committees, leadership, and regulators.
Compliance: Embedded controls align to global frameworks and South Africa’s evolving requirements, with robust policy, retention, privacy, and access mechanisms.
Platform Highlights
Ontology-Driven Knowledge Core: Harmonizes meaning and context for assets, liens, and risk exposures.
AI Data Agents: Active quality checking, continuous enrichment, exception flagging, and audit-workflow automation.
Configuration-Driven Pipelines: Adapt as rules, products, or regulations change—no redevelopment required.
Open API Ecosystem: Secure, extensible connections to core banking, LOS, vendors, BI, and risk platforms.
Enterprise-Ready Security & Governance: RBAC/ABAC, field-level encryption, PII minimization, immutable audit logs; controls aligned to SR 11-7 / OCC 2011-12 (model risk) and BCBS 239 (risk data aggregation), plus GDPR/POPIA.
Implementation Approach
We deploy as an overlay, not a swap. In ~90 days:
Days 0–30: Connect priority sources (LOS/core, appraisers, public records, market/pricing). Stand up the unified collateral graph. Turn on data-quality scorecards and end-to-end lineage.
Days 31–60: Codify eligibility, haircuts, and advance-rate policy (jurisdiction-aware). Enable decision dashboards. Activate AI Data Agents for monitoring, reappraisal triggers, and exceptions.
Days 61–90: Move target portfolios into governed decisioning. Integrate with credit-memo workflow and committee packs. Configure revaluation schedules and attestations.
No rip-and-replace— start with the highest-risk portfolios; existing workflows and controls stay intact.
Business Outcomes & Value
Faster, more consistent loan and collateral decisions
A single, trusted source of truth for underwriting, risk, and finance
Automated early warning and exception management to prevent collateral gaps
Lower audit and model-risk exposure via transparent, end-to-end traceability
Greater operational agility—teams shift from reactive fixes to proactive, data-driven action
Summary: Reduce time-to-decision, manual exceptions, data defects reaching the credit file, and rework from audit findings. Detect more coverage breaches pre-close. Reclaim underwriter time.
Infinity Data AI: Precision Classification. Trusted Governance. Explainable Decisions.