Anomaly detection in Remote Deposit

Anomaly detection in remote deposit through mobile

Anomaly detection in Remote Deposit harnesses 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 & enabling fraud identification process more agile & cost effective ACH/ABA codes, and enabling fraud identification process to be more nimble and economical manner. This software app identifies patterns related to customer behavior, authenticity of mobile checks, accounts in which they are deposited, & their geo-spatial mobile deposit locations.

Use Cases

  • Entity resolution across databases

  • Determining authenticity of checks

  • Geo-spatial risks related to mobile checks

  • Identifying accounts that are more at risk due to fraud in Remote Deposit Capture (RDC )

Anomalia Serves


AI-based anomaly detection app in remote deposit clears all Hurdles

Anomaly detection in remote deposit by Scry Analytics ingests data from different sources and detects fraud and is able to process tremendous amount of records of more than 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.