Risk and Compliance

Mitigate risk and ensure compliance with robust data and machine learning solutions

Secure your business with real-time data and alerts

Financial institutions need to process large volumes of data from multiple sources, undertake deep analysis of big data, and provide non-compliance detection and risk oversight to act in near-real-time. Sigmoid’s data engineering and AI services empower banking and financial services organizations to stay compliant and mitigate risks faster. With the help of our risk and compliance analytics, financial institutions can predict the likelihood of a customer to take a specific action using propensity modeling as well as assess an individual's credit worthiness based on credit score modeling. Our scalable data models help flag malpractices, improve the quality of decisions, and implement stronger governance policies.

Navigate the evolving risk and compliance landscape with real-time analytics

Risk Management

Risk classification modeling

Predict risk levels through AI-driven risk classification models that can categorize entities into standardized risk classes.

Customer profiling and segmentation

Create targeted risk profiles of customers via segmentation models that identify behaviors, characteristics, and past activities.

Fraud detection with ML

Enable accurate fraud detection with machine learning algorithms that recognize suspicious anomalies in large, high-velocity transaction data.

Regulatory Reporting

Data lake for SSOT

Centralize enterprise data from all sources into a readily available data lake with standardized schemas for integrated analytics.

Automated data consolidation

Combine, cleanse, and process data automatically across platforms for consolidated, unified analytics and reporting.

Real-time insights and visualizations

Gain on-demand visibility on risk indicators for continuous threat management through interactive analytics dashboards.

Data Security

Data governance and cataloging

Establish rigorous governance standards and catalog data to improve compliance and risk data accountability.

Data lifecycle management

Manage the end-to-end lifecycle of risk data sets with tools for discovery, integration, security, and model-based data processing.

Data provenance and lineage

Ensure data governance by deploying models that can trace data’s origin and transformation journey to maintain accountability in compliance.

Case study

Enhanced trade surveillance and regulatory compliance for top-3 investment bank

Find out how Sigmoid helped set up a robust trade surveillance for a top-tier investment bank, making it regulatory compliant and creating faster system response times.

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