Overview
Forensica is a trade surveillance and market abuse detection platform for brokers, exchanges, wealth managers and asset managers. It watches order, trade and market-data flow as it happens and flags layering, spoofing, wash trading, marking the close, front running, pump and dump, cross-venue layering and insider-correlated activity as soon as the pattern forms. It covers five asset classes (equity, F&O, FX, commodity and debt) on one architecture.
Detection pairs a pre-built rule library with ML-assisted anomaly detection. The rules cover the manipulation patterns regulators name, using multi-condition triggers and correlation-based alerts in place of single-threshold alerts. The ML models score behaviour that fixed rules miss and learn from every disposition your analysts make, which cuts false positives over time. Surveillance teams can write and tune their own rules for a new product or venue without raising a vendor ticket. Every alert comes risk-scored with a severity, a full evidence chain and a recommended next step. Confirmed alerts become cases with ownership, SLAs, an audit trail, a reconstructed timeline and SAR/STR drafting in the regulator's format. An AI Investigator's Copilot answers plain-language questions such as "what did this account do across venues last week?" in seconds.
Forensica is lakehouse-native. It runs on open table formats (Delta Lake, Apache Iceberg, Apache Hudi) and deploys on AWS, Databricks, Cloudera CDP, Azure or on-premises, so it sits on the data you already have instead of adding another data store. Optional modules extend the core platform: NexusLakehouse (surveillance data models and governance), Stream Markets (low-latency streaming at exchange scale), SentinelAI (AI/ML detection engine) and Investigator's Copilot. Reporting formats and attestation for SEBI, SEC and FINRA are built in. Teams deploy in 14 days and tune over the following four weeks, and many run Forensica beside their current surveillance vendor on one venue before moving more over.
Highlights
- Real-time market abuse detection: a pre-built rule library for spoofing, layering, wash trading, marking the close and insider trading, plus ML anomaly detection for patterns no rule describes yet.
- Regulator-ready trade surveillance: every alert carries a risk score, a full evidence chain and a recommended next step. Built-in case management, timeline reconstruction, SAR/STR drafting and an AI Investigator's Copilot, with SEBI, SEC and FINRA reporting formats included.
- Lakehouse-native and multi-asset: one architecture for equity, F&O, FX, commodity and debt on Delta, Iceberg or Hudi. Runs on AWS, Databricks, Cloudera CDP or on-premises, and goes from deployment to the first production pattern in 14 days.
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Email: info@smart-analytica.com Phone: +91 79723 98190 Support URL: https://smart-analytica.com/contact/
Support description: Smart Analytica provides support for every Forensica subscription. Onboarding includes deployment help, data-source and lakehouse integration, and configuration of the standard rule library, with a target of the first production pattern within 14 days. After go-live, customers get support by email and phone during business hours (IST, with overlap for US hours), help tuning rules and models, product updates, and a named customer success contact. Managed Services for day-to-day surveillance operations and Solution Implementation for custom rule authoring, ML model development and surveillance-team integration are available under separate agreements. Contact info@smart-analytica.com with your AWS account ID and a description of the issue.