# Fraud detection with Neo4j
URL: https://docs.datarobot.com/en/docs/api/dev-learning/accelerators/time-series/fraud-detection.html

> Build a fraud detection pipeline using Neo4j for storing and querying a knowledge graph.

# Fraud detection with Neo4j

[Access this AI accelerator on GitHub](https://github.com/datarobot-community/ai-accelerators/tree/main/use_cases_and_horizontal_approaches/datarobot-neo4j-knowledge-graph-for-fraud-detection)

This accelerator demonstrates how to build a fraud detection pipeline using Neo4j and DataRobot. Use Neo4j to store and query a knowledge graph of clients, loans, addresses, and more. Then, use DataRobot to build a predictive model with graph-based features. The accelerator contains multiple notebooks. The first notebook walks through installing a Neo4j 4.4.11 instance, loading a Neo4j database, and uploading a dump file with the CLI. The second notebook outlines how to extract graph data into training and holdout CSVs, upload training data to DataRobot, and build a classification model for scoring.

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