Risk Intelligence for Investment Teams
Next-generation portfolio analytics and risk management, built for firms of every size
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Our Solutions
Investment Portfolio Analytics
Strategic modelling and optimisation of multi-asset portfolios prior to execution
- Factor analytics & risk decomposition
- Portfolio optimisation & rebalancing
- Performance attribution analysis
- Stress testing
Risk Intelligence API
Embed risk analytics to power institutional-scale workflows
- RESTful API with full coverage
- Integrate into existing systems
- Flexible per-instrument pricing
MCP Interface for LLMs
Connect portfolio intelligence directly to AI agents and LLM workflows
- Model Context Protocol support
- AI-native risk queries
- Seamless LLM integration
Trade Risk Management
Real-time pre-trade validation and AI-driven risk analysis for active trading
- Pre-execution order validation
- AI-powered trade analysis
- Personalized risk frameworks
Built for the AI Age
Mantarisk is designed to work naturally inside modern AI systems. Institutional-grade risk intelligence can now be accessed through chat assistants, embedded into agent workflows, and integrated programmatically into investment tools.
Institutional-grade risk intelligence
Run portfolio risk analysis with capabilities traditionally reserved for large financial institutions.
Engineered for AI
Designed to integrate directly with chat assistants, AI agents, and automated investment workflows.
API-first design
Access risk intelligence programmatically through a modern developer interface.
Inside ChatGPT and Claude
Use Mantarisk directly inside chat assistants through the Mantarisk MCP server.
Built for AI agents
Automate monitoring, due diligence, and portfolio risk workflows using autonomous agents.
Portfolio exposure insights
Retrieve portfolio exposure, concentration risk, and key portfolio risk signals quickly.
Capabilities
| Factor Based Analysis | 134 factors covering sectors, geographies, currencies, commodities, government & corporate (IG, HY), money market, style |
| Contribution Analysis | Decomposes returns into Allocation and Selection (and Interaction effects for Brinson-Fachler) to identify performance drivers. |
| Base Analytics | Standard metrics including Volatility, VAR (Value at Risk), CVAR, and Exposure analysis. |
| Bespoke Factors | Custom factor modeling (e.g., user-defined macro factors) for tailored risk exposure analysis. |
| Expected Returns | Forward-looking return estimates based on factor exposure and historical risk premia. |
| Portfolio Optimisation | Constraint-driven optimization (Min Risk, Max Diversity, Max Sharpe, Tracking Error). |
| Portfolio Tracking | Optimization specifically to minimize tracking error against a chosen benchmark. |
| Mass Rebalancing | Automated rebalancing of multiple portfolios simultaneously to align with target models. |
| Efficient Frontier | Visualizes the risk/return trade-off curve to select optimal portfolios. |
| Black Litterman | Bayesian optimization framework combining market equilibrium with investor views. |
| Brinson-Fachler Model | Standard attribution breaking excess return into Allocation, Selection and Interaction effects. |
| Hierarchical Model | Multi-level attribution (e.g., Asset Class -> Sector -> Security) for granular insight. |
| Blended Benchmarks | Attribution against custom composite benchmarks (e.g., 60% SPY / 40% AGG). |
| Historical Stress Testing | Simulate portfolio performance during past crises (e.g., Covid-19). |
| Hypothetical Stress Testing | User-defined "What-if" scenarios (e.g., "Tech Sector -10%") using factor sensitivities. |
| Cashflow Forecasting | Projections of portfolio liquidity needs and income generation (coupons/dividends). |
| Pre-Execution Order Validation | Assess trades in real time against your custom risk profile. Receive actionable analytics to confirm or challenge setups, improving consistency and reducing behavioral risk. |
| AI-Powered Trade Analysis | Our genetic algorithm examines your trading history to build a personalized, evidence-based risk framework. Tactical rules are derived from your own data and quantified to reflect your actual behavior. |
| Commodities | Support for commodity ETFs/Indices (e.g., DBC, Gold) and futures proxies. |
| Crypto | Native support for major cryptocurrencies and digital asset indices. |
| Equity | Full support for global equities, including sector and geography mapping. |
| ETFs | Full look-through or regression-based analysis for ETFs. |
| Fixed Income | Support for Government and Corporate bonds (e.g., TLT, IEF) with yield curve sensitivity. |
| Funds (inc. Mutual Funds) | Analysis via fund breakdowns and NAV time-series regression against risk factors. |
| Money Market, FX, Cash | Native support |
| Options / Warrants | Repricing of options to correctly model the nonlinear payoffs |
| Private Assets Modelling | Proxy-based modeling for illiquid assets (PE/VC) using listed factor equivalents. |
| Structured Products | See our product roadmap for details. |
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Every portfolio deserves
institutional precision
The wealth management industry is undergoing a fundamental shift. Personalized, data-driven risk intelligence — once reserved for the largest institutions — is becoming the standard clients expect, regardless of firm size.
MantaRisk was built for this moment. Our platform delivers real-time portfolio analytics, AI-powered risk overlays, and institutional-grade optimization to firms of every size — with pricing based on what you use, not what you manage.
