Skanalytix Pty Ltd

High-Fidelity Synthetic Financial Data Skanalytix generates realistic synthetic time series for financial assets — including equities, yield curves, and macro-conditioned scenarios — powered by our proprietary UNCRi modeling framework. Our platform helps financial institutions, fintechs, and researchers: • Backtest and compare strategies across different market conditions • Generate forward-looking VaR and CVaR estimates under stress • Simulate correlated asset paths for robust scenario testing • Fill gaps in incomplete or sparse datasets • Train ML models on realistic, high-variance time series data Unlike GANs, VAEs, and other deep learning approaches, our framework is nonparametric, data-efficient, and interpretable — capable of generating synthetic data that preserves volatility clustering, tail risk, and cross-asset correlations, even with limited historical input. The result: synthetic financial data that behaves like real markets — without the limitations of rigid assumptions or black-box models. After several years of independent development, we’re now opening the door to strategic partnerships as we bring our technology to market. Visit skanalytix.com to learn more or get in touch.