Market risk analytics with agility and scalability
Monitor, explore, and explain real-time VaR, sensitivities, and stress scenarios. Be ready for FRTB SA and IMA, with zero trade-offs between regulatory accuracy and 1LOD/2LOD explainability.
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Why global and regional banks choose Opensee for market risk analytics
Key capabilities of Opensee for market risk analytics
FRTB regulatory capital calculations with full transparency
Comprehensive support for FRTB SA and IMA. Multi-dimensional sensitivity aggregations, bucketing, risk charge attribution, and capital decomposition with unprecedented drill-down and explainability. Support for both regulatory and internal FRTB models with full audit trails for supervisory review.
Automated FRTB SA and FRTB IMA capital calculations
Full sensitivity decomposition by desk, risk factor, & bucket
Real-time "what-if" scenario modeling for capital (new positions, market conditions, books hierarchy, SA vs IMA)
Regulatory reporting templates and benchmark portfolios
Advanced VaR, Expected Shortfall, and regulatory stress testing
Historical, Monte Carlo, and parametric VaR with Marginal, Incremental, stand-alone contribution. Calculate Expected Shortfall (ES) and MaxLoss. Run unlimited custom stress scenarios in parallel - comparing external and internal stress scenarios side-by-side with instant drill-down to desk, book, and trade level.
Multiple VaR methodologies calculations
Parallel regulatory and internal stress scenario execution
Historical analysis including backtesting framework for model validation
Intraday VaR updates for front-office and risk teams
Empower traders and desk heads with real-time analytics
Front-office users and desk heads can monitor intraday risk, slice sensitivities by desk, trader, issuer, tenor, or any risk factor required. Run real-time P&L explain, simulate hedging strategies, and generate risk reports on demand. Create custom Python calculators for desk-specific metrics without IT dependencies.
Drag-and-drop analytics interface
Natural language queries with Agensee AI
Python SDK for quants and advanced risk modelers
Excel, Tableau, and other BI connectors for custom reporting
Single source of truth across all trading desks and asset classes
Consolidate fragmented market risk data from all trading systems, risk engines, and market data vendors into one unified repository. Horizontally scalable architecture stores billions of trades with efficient compression and unlimited history. Full audit trail, version control, and BCBS 239 compliance for regulatory risk data aggregation.
Eliminate data silos across all trading desks and asset classes
BCBS 239 compliant data quality and risk data aggregation
AI-driven anomaly detection and data quality KPIs
Zero downtime at enterprise scale
Explore more Opensee solutions
Counterparty Credit Risk
SA-CCR, IMM-CCR, SA-CVA, and xVA calculations with full explainability—at any granularity, with sub-second response times on billions of exposures.
Banking Credit Risk
Monitor credit risk across retail, SME, and corporate portfolios by exploiting PD, LGD, and EAD outputs, analyzing provisions and RWA, and identifying emerging risks early.
Liquidity Risk
Monitor, stress test, and explain intraday and structural liquidity across entities and desks—covering cash flow management, regulatory metrics and internal liquidity metrics.
Collateral & Margin Management
Monitor SIMM exposure, optimize collateral allocation, and automate margin workflows in real time, with AI-driven insights and full regulatory audit trails.