Digital Mission

Accelerated Banking

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Digital Trust and Stewardship Regulatory Compliance

Advanced AML Transaction Monitoring

Current Situation

High false positives continue to be a primary area of concern for financial firms, which are a substantial drain on resources that could be used more productively. Rules-based systems without advanced analytical capabilities are not adequate to identify suspicious activity and meet regulatory requirement and expectations.

Goals and Objectives

Improve efficiency and effectiveness of AML processes to reduce operational costs while more accurately identifying suspicious activity. As a result, compliance and reputational risks are reduced.

Technology Deployed

Hardware: Enterprise hardware

Services: Business consulting and managed services (BPO and SaaS)

Software: Analytics, AI, application platforms, and content workflow and management applications

Innovation accelerators: Cognitive machine learning

3rd Platform technologies: Big Data and analytics

Use Case Summary

Firms leverage AI to drive down false positives and automate elements of the investigative process. Explainable machine learning models are continually tuned by feeding investigative results and external data. Predictive analytics prioritizes case work. Regulatory reporting of suspicious activity is highly automated through natural language processing and generation.

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