Fraud detection in wire transfers

Fraud detection in transactions though wire transfers

Fraud detection in wire transfer 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 more nimble and economical manner. This software app identifies patterns related to the originators (i.e. financial institution’s clients) and beneficiaries, particularly if these beneficiaries occur in other wire transfers or have a high anomaly score) .

Use Cases

  • Entity resolution across databases

  • Watch list screening, enhanced KYC & KYCC

  • Geo-spatial risk for wire transfer transactions

  • Identifying originating accounts that are more at risk

  • Using external and internal data to identify common and less frequent scams

Anomalia Serves

Anomalia®

AI-based fraud detection app in wire transfers clears all Hurdles

Anomaly detection in wire transfers 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.