Abstract: A system and method for modifying existing rules of an existing anti-money laundering software system to reduce false alerts is disclosed. The system and method can find relationships amongst transactions and actors involved in transactions by using knowledge graphs and techniques that can help determine actors' likelihood of money laundering. Artificial intelligence may be used to: augment missing data at various stages throughout the disclosed method, help find new thresholds for existing rules of an anti-money laundering system, and test the new thresholds before making recommendations for thresholds. The system and method can gather more context about transactions and actors (e.g., account holders) by providing a way for entities, such as financial institutions, to share transaction data, non-transaction data, analyses based on transaction data, and historical alerts through private blockchain.