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Synthetic Data via Maxwellian GenAI for Financial Services

Overview

Unlock the transformative potential of synthetic data in the financial sector with GenAI. Generate high-quality, secure synthetic data on-demand to accelerate AI model training, ensure compliance, and drive immediate value.


Key Features


1. Quality: Relatively Indistinguishable

  • Generative AI: Create data that mirrors the source for immediate value in model training or forecasting.

  • Integrated Validator: Compare synthetic data to the original source and measure the difference.

2. Model Training: Faster & Robust

  • Realistic Datasets: Develop and test AI models without compromising privacy.

  • Effective ML Models: Employ neural networks to mirror complex relationships in your data.

3. Compliance: PII Masking

  • Sensitive Data Detection: Automate alerts to protect against leaks and breaches.

  • Compliance Assurance: Remove all PII data while leveraging synthetic data.

Target Customers & Value Proposition

  • Hedge Funds: More robust backtesting.

  • Banks: Expanded scenario modeling for risk management.

  • Asset Managers: Low-cost alternative data.

  • All Financial Firms: Customizable data and compliance.

Initial Focus: Expanded Scenario Modeling for Risk Management

  • Clear Value: Simulate more potential risk scenarios.

  • Urgent Need: Regulatory focus post-financial crisis.

  • Data Accessibility: Existing data for initial training.

  • Light Customization: Less effort compared to trading strategy backtesting.

Customer Personas


Risk Analytics Manager at a Retail Bank

  • Needs: Faster model development, more risk scenarios.

Head of CCP Risk at an Investment Bank

  • Needs: Better coverage of exotic products, stress testing.

Operational Risk Manager at an Insurance Company

  • Needs: Expanded dataset for statistical modeling.

Head of CCAR Modeling at a Regional Bank

  • Needs: Quickly generate high-quality scenarios.


Market Opportunity

  • TAM: $28 billion globally for risk management software.

  • Scenario Modeling TAM: Approximately $4 billion.

  • Growth Drivers: Regulations, AI/ML adoption, market volatility.

  • Capital Savings: 1% reduction in capital needs equals billions in savings.




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