Quickstart
Build a Real-Time Fraud Detection Model with Natural Language in Snowflake ML
Public SectorAIState & Local GovernmentFederal Government
Program Integrityand Payment Accuracy
Detect improper payments, reduce fraud, waste and abuse, and improve payment accuracy across government programs with unified data analytics and AI.
Overview
Protect public funds with data-driven oversight
Unify claims, payments and provider data to detect anomalies, prevent improper disbursements and recover overpayments.
Improper payment detection
Consolidate payment data across programs and apply anomaly detection to flag duplicate, erroneous or fraudulent disbursements before payment.
Provider and beneficiary risk scoring
Build ML-driven risk scores for providers and beneficiaries by joining claims data, behavioral patterns and watch list databases on a single platform.
Audit-ready data lineage
Maintain end-to-end lineage and access logs for payment decisions, giving auditors a clear trail from raw data through model output to final action.
CUSTOMER OUTCOMES
Leading public agencies protect program integrity with Snowflake
400k
Providers supported with improved performance and cost
Centers for Medicare & Medicaid Services (CMS)
257k
Employers served at one of the largest state-run insurance systems
Ohio Bureau of Workers’ Compensation
HOW IT WORKS
Stop improper payments with modern data analytics and machine learning
Unify siloed payment streams, run automated anomaly detection at scale and accelerate overpayment recovery workflows on a single secure platform.
Consolidate claims and payment data
Ingest payment, provider and beneficiary data from disparate program systems into a single source of truth without complex ETL.
Deploy fraud and anomaly detection models
Train and deploy ML models with Snowpark and Snowflake Cortex AI. Score transactions against behavioral baselines, peer groups and known fraud patterns.
Automate recovery workflows and compliance reports
Create recovery cases, produce OMB-mandated metrics and feed case management systems with near real-time visibility into improper payment rates.
DEMO
Public sector fraud detection with Snowflake AI
Ravi Kumar from Snowflake builds a fraud, waste and abuse (FWA) detection platform for a fictitious state Medicaid agency. It unifies claims, provider, beneficiary and clinical data, then uses AI and ML to flag suspicious claims before payment.
Why Snowflake
The Snowflake difference
Comprehensive fraud prevention
Break down data silos across programs to uncover complex, cross-agency payment fraud schemes in near real time.
Embedded AI and ML capabilities
Run anomaly detection models where your data lives using Snowpark and Cortex AI, without the need for external tools.
Governed and audit-ready
Maintain end-to-end lineage and automated compliance reporting with FedRAMP High-level data security on select deployments.
Our solution partners
RESOURCES
Explore Developer Guides
Discover technical quickstarts and guides to build scalable fraud, waste and abuse detection architectures on Snowflake.
GET STARTED
Protect program integritywith Snowflake
Snowflake for Program Integrity and Payment Accuracy
Frequently asked questions
How does Snowflake help government agencies detect improper payments and fraud?
Snowflake unifies claims, payment, provider and beneficiary data on a single platform. Using built-in ML and AI models via Snowpark and Cortex AI, agencies can run near real-time anomaly detection and risk scoring across massive data sets without moving sensitive data.
Is Snowflake FedRAMP compliant for public sector data workloads?
Yes, Snowflake supports FedRAMP High on AWS GovCloud and Azure Government, as well as DoD Impact Level 4 (IL4) and Level 5 (IL5) requirements on AWS GovCloud, helping government agencies meet data protection and governance standards.
Can Snowflake integrate with existing case management and claims systems?
Yes, Snowflake integrates with legacy databases, modern case management platforms and downstream analytics tools using native connectors, REST APIs and zero-copy data sharing.
How does Snowflake handle unstructured data like clinical notes or appeal documentation?
Snowflake Cortex AI allows agencies to process and analyze unstructured text, scanned PDFs and audio recordings natively using LLMs and natural language processing to surface hidden FWA patterns.
How does Snowflake maintain auditability for payment recovery actions?
Snowflake provides end-to-end data lineage and access logging, so model inputs, decisions and record changes are traceable and audit-ready for OMB compliance.
What is the cost structure for running fraud detection models on Snowflake?
Snowflake operates on a consumption-based pricing model, allowing agencies to scale compute up or down as needed so they pay only for the exact query and training processing power used.
