PII-Safe Fraud Analysis
Intercept internal transaction logs, scrub Personally Identifiable Information (PII) locally, and route the anonymized payload to OpenAI or Claude for complex fraud detection without violating data privacy laws.
The Baseline
Financial institutions cannot use industry-leading LLMs (like OpenAI or Claude) for fraud analysis because sending raw transaction logs with customer names and account numbers violates internal compliance and federal privacy regulations.
AVELIN AI intercepts the data stream locally via Privacy Shield. It automatically strips all PII and replaces it with secure tokens before routing only the anonymized transaction patterns to external LLM providers.
Banks achieve state-of-the-art AI fraud detection with zero regulatory risk. Data leakage drops to zero, and the institution maintains full compliance while safely leveraging the most powerful third-party models available.
Architecture Flow
Data Ingestion (Internal)
The bank's internal transaction database flags a suspicious pattern and sends the raw log to the AVELIN API interface.
Local Scrubbing (Privacy Shield)
Before the data leaves the corporate firewall, AVELIN's Privacy Shield intercepts the payload. It identifies and replaces all PII (names, SSNs, account numbers) with secure, mapped tokens (e.g., [USER_001]).
External Inference (Model Engine)
The anonymized payload is routed to the chosen external LLM (e.g., OpenAI). The external model analyzes the behavioral pattern and returns a fraud probability score and reasoning.
Local Re-Assembly
The AVELIN platform receives the response, maps the secure tokens back to the original customer data locally, and pushes the final alert to the bank's internal dashboard.
Core Infrastructure
| Component | Role |
|---|---|
| Privacy Shield | Executes local PII scrubbing and token mapping via edge models before any data reaches the public internet. |
| Model Engine | Manages the API routing to external LLMs. Allows the engineering team to swap OpenAI for Anthropic instantly if compliance rules change. |
| y-ray Deep-Trace | Logs the exact sequence of the payload transfer. Provides auditors with a verifiable log proving no PII left the internal servers. |
Technical Specifications
AES-256 for data at rest; TLS 1.3 for data in transit
GDPR, CCPA, and GLBA compliant architecture
Deploys natively on your existing Kubernetes clusters (AWS, Azure, or bare metal)
Build this architecture
Map this workflow to your internal data models. Deploy AVELIN AI to gain sovereign control over your enterprise intelligence.
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