What challenges did SymphonyAI face before AI implementation?

Rapidly rising transaction volumes and compliance requirements in financial services. Existing legacy detection generates excess false positives, increasing workloads. Manual investigation processes slow response to emerging fraud risks. Global and local regulations require robust, transparent controls.

What was the impact of the AI solution?

Reduced false positives by up to 70% for compliance teams. Increased investigator productivity by up to 70%. Accelerated investigations by 60-70% versus manual approaches. Enabled detection of 30% more confirmed risks.

Source

MicrosoftExpanded

SymphonyAI Speeds Financial Crime Detection with Predictive and Generative AI

Use case typeRisk assessmentUpdated Jun 13, 2026

SymphonyAI leverages Microsoft Azure AI, Azure OpenAI, and Azure API Management to transform financial crime detection for global financial institutions. Their Sensa Investigation Hub and Sensa Copilot combine predictive machine learning and generative AI to automate investigations, identify suspicious patterns, and help compliance teams draft suspicious activity reports. By integrating multiple data sources and supporting real-time analysis, the solution enables investigators to investigate cases more efficiently and reduce false positives by up to 70%. The architecture supports compliance across diverse regulatory environments and ensures data privacy via Azure’s security and hybrid capabilities. With Sensa Copilot acting as a natural language assistant, investigators complete investigations up to 60-70% faster and file 30% more risk reports, resulting in measurable productivity gains and strengthened fraud prevention.

Organization: SymphonyAI
Industry: Finance
Location: United States
Published: June 2024

Reported outcomes

−70%

quantified impactQuality & accuracy

+70%productivity+30%quantified impact

Strategic outcomes

Risk & complianceReduced false positives in compliance screeningSpeed & agilityAccelerated investigationsBetter decisions & insightDetected more confirmed risksNew product / capabilityAutomated investigation assistance

Catalog median for quality & accuracy deployments: −40% across 42 reported metrics. Compare benchmarks →

Primary read

Use case focus

Showing 3 of 4

1AI-Powered Financial Crime Detection
2Automated SAR Generation and Fraud Investigation
3False Positive Reduction for Compliance

Rapidly rising transaction volumes and compliance requirements in financial services.
Existing legacy detection generates excess false positives, increasing workloads.
Manual investigation processes slow response to emerging fraud risks.
Global and local regulations require robust, transparent controls.

SymphonyAI developed Sensa Investigation Hub and Sensa Copilot, powered by predictive and generative AI on Azure.
Integrated multiple internal and external data sources for holistic detection.
Automated investigation assistance with natural language summarization and report drafting.
Deployed within scalable, secure Azure infrastructure compliant with industry standards.

Technologies

Microsoft Azure AI Azure OpenAI Azure API Management

Reduced false positives by up to 70% for compliance teams.
Increased investigator productivity by up to 70%.
Accelerated investigations by 60-70% versus manual approaches.
Enabled detection of 30% more confirmed risks.

Architecture

SymphonyAI’s solution runs on Microsoft Azure AI and integrates Azure OpenAI and Azure API Management for connectivity and compliance. Sensa Investigation Hub pulls data from internal and external sources, applies supervised and unsupervised machine learning for anomaly detection, and leverages a generative Copilot assistant to summarize findings and automate investigator workflows. Cloud security, access controls, and hybrid deployment options ensure privacy and regulatory alignment.

Sources & evidence1

ExpandedExpanded

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