Company Overview

Skanalytix is a generative modeling platform for financial time series, built to support scenario-aware simulation, stress testing, forecasting, and risk analysis.

At its core is the UNCRi framework — a flexible, graph-based engine for learning from structured and time-varying data. This enables the Skanalytix platform to generate realistic, interpretable synthetic datasets that reflect key features of financial markets, including volatility clustering, regime shifts, tail behavior, and cross-asset dependencies.

Designed for quant professionals, risk managers, and researchers, the platform provides a scalable, data-efficient alternative to black-box generative models, enabling deeper insights under uncertainty and data sparsity.

Skanalytix was founded in 2023 to bring a more principled, transparent modeling approach to a field too often dominated by opaque or overly simplified tools.

Founder's Note

I’ve spent over two decades working in artificial intelligence, machine learning, and decision systems — first in academia, and now through independent research and development. With a PhD in AI and a background in physics and mathematics, I’ve always been drawn to complex, structured problems — especially those that challenge conventional modeling techniques.

In 2020, I left academia to focus full-time on building better tools for understanding dynamic systems. That work led to the development of UNCRi, a new modeling framework that powers the Skanalytix platform.

My goal with Skanalytix is to offer financial professionals a powerful, flexible, and interpretable alternative to black-box simulations — one that respects the structure, uncertainty, and dependencies of real-world financial data.

— Andrew Skabar, Founder

Let's Connect

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Contact us or connect with Andrew on LinkedIn.