Anomaly detection in ACH

Anomaly detection in ACH debit transactions

Anomaly detection in ACH debit transaction harness the true power of artificial intelligence by using proprietary algorithms and connectors that help in automating several steps such as pre-processing, cleansing and harmonizing originator & beneficiary names, addresses. ACH/ABA codes, and enabling fraud identification process to be nimbler and more economical. This software app identifies patterns related to the debited & originating accounts, corresponding banks, customer behavior, and geo-spatial locations.

Use Cases

  • Entity resolution across databases

  • Watch list screening, enhanced KYC & KYCC

  • Geo-spatial risk for SCH debit transactions

  • Identifying accounts that are more at risk due to fraud in ACH debit transactions

Anomalia Serves


AI-based Anomaly in ACH transactions clears all Hurdle

Anomaly detection in ACH transactions by Scry Analytics ingests data from different sources and detects fraud and is able to process tremendous amount of records of 4 million/hour.

More Detail

Anomalia has been built using

  • Bayesian networks

  • Reinforcement learning

  • Generic rule-based machine learning

  • Heuristic algorithms

  • Data mining

  • Big data integration

  • Big data analytics

  • Reverse engineering

Key Differentiators &
Business Benefits

  • User Interface and APIs

    Pre-built graphical user interface (GUI) & APIs for quick deployment & integration with clients’ existing workflow.

  • Domain Ontologies

    Pre-built financial ontologies & business rules that are dynamically updated to improve the product accuracy over time.

  • Knowledge Graphs

    30+ probabilistic spatial and temporal graph algorithms to determine links and connected entities.