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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