AI-Powered Fraud Investigations in Multifamily Lending | Foxtrot

Uncovering Hidden Connections in Multifamily Fraud Investigations

Foxtrot Services helped a multifamily lending institution transform its fraud investigation capabilities by developing an AI-assisted investigation environment built on Palantir Foundry. The solution connected fragmented financial information, uncovered hidden relationships between borrowers and affiliated entities, and enabled investigators to validate findings through traceable source evidence.

The Challenge

Financial fraud investigations often require analyzing vast amounts of disconnected information across rent rolls, operating statements, property appraisals, internal loan records, and external market data. Inconsistent representations of borrowers, principals, sponsors, and related parties made it difficult to identify suspicious connections across multifamily loans.

Investigators needed a way to detect anomalies, examine relationships, and efficiently navigate complex financial records while ensuring that AI-generated findings remained accurate, transparent, and independently verifiable.

The Foxtrot Solution

Leveraging Palantir Foundry, its Ontology, and AIP Chatbot Studio, Foxtrot engineered an integrated investigation environment combining advanced data engineering, entity reconciliation, relationship detection, and AI-assisted analysis.

The solution transformed fragmented documents and financial records into structured, interconnected data, allowing investigators to explore relationships across loans and identify previously obscured affiliations. Specialized detection logic and heuristic entity reconciliation helped eliminate duplicate representations and expose meaningful connections.

To support defensible investigative decisions, Foxtrot incorporated deterministic validation controls, source-level provenance, and direct access to supporting documents. Investigators could move seamlessly from AI-assisted findings to the original PDFs and spreadsheets, verify conclusions, review loan summaries, and support Suspicious Activity Report investigations.

Measurable Results and Business Impact

The solution reconciled 1.13 million disparate entity records into approximately 373,000 unique entities, establishing a more reliable foundation for financial investigations.

By connecting previously isolated information, the platform enabled investigators to uncover hidden loan relationships, examine suspicious affiliations, and identify inconsistencies that might otherwise remain undetected.

Most importantly, every AI-assisted finding could be traced to its underlying evidence. This combination of connected data, automated discovery, deterministic verification, and transparent source documentation strengthened investigative workflows and supported more defensible decisions.

The Takeaway

This case study demonstrates how Foxtrot combines Palantir Foundry, enterprise AI, and rigorous data engineering to solve complex challenges in financial services. Rather than relying on AI-generated conclusions alone, Foxtrot delivered an evidence-grounded investigation environment designed to make fraud detection more transparent, verifiable, and actionable.

The result is a scalable foundation for AI-assisted financial investigations in which sophisticated discovery capabilities operate alongside the validation and accountability required for high-stakes decisions.