etio: Automating Financial Reporting with Causal Intelligence at Zurich Insurance Group
The winner of Zurich's agentic hyperchallenge in the finance category, etio transforms complex financial reporting from a labor-intensive manual process into an intelligent, agent-driven workflow that seamlessly integrates with their existing enterprise systems. What traditionally required days of analyst time can now be completed in hours, freeing Zurich's actuaries to focus on strategic decision-making rather than data compilation.
But etio goes far beyond simple automation. Our platform surfaces hidden causal relationships across metrics, offering insights that extend beyond human pattern recognition and surpass current actuarial analytics tools. By identifying the true drivers of financial performance, etio enables Zurich to understand not just what happened, but why it happened — and what's likely to happen next.
Speed
Complete reports in hours, not days
Integration
Seamless enterprise system connectivity
Intelligence
Causal insights beyond correlation
Designed for speed. Built for understanding. Ready to transform how your organization approaches financial reporting.
Proven with Leading Institutions
01
Zurich Insurance Pilot
Our current collaboration with Zurich Insurance demonstrates how agentic automation and causal AI can fundamentally reshape financial reporting from the ground up, delivering measurable improvements in efficiency and insight quality.
02
European Banking Research
Earlier work uncovered critical causal links between sustainability metrics and financial performance for a major European banking institution (under NDA), revealing relationships that traditional analysis methods had missed.
03
Scientific Foundation
Wangari's scientific roots trace through prestigious institutions including AXA Climate, Sorbonne Université, and CERN, blending rigorous research precision with deep financial sector insight.
The Wangari Digest
Exploring the Frontier Between Finance, Data, and Sustainability
Every week, we share what we're learning on the cutting edge of financial intelligence. From advanced causal inference methodologies to real-world ESG signal analysis, our digest offers a transparent view into our research and discoveries.
This isn't corporate marketing. It's an open lab notebook from our journey of making the invisible visible — exploring the questions that don't have easy answers and sharing both our breakthroughs and our challenges along the way.
Causal Inference in Finance
Deep dives into methodologies that separate true drivers from spurious correlations in financial datasets
ESG Signal Analysis
Practical insights on extracting meaningful sustainability signals from unstructured data sources
AI in Financial Systems
Exploration of how intelligent agents are transforming analysis, reporting, and decision-making
Led by Science. Built on Collaboration.
Wangari Global was founded by Dr. Ari Joury, a particle physicist turned sustainability-driven entrepreneur. With deep experience spanning fundamental research at CERN, climate intelligence at AXA Climate, and academic rigor at Sorbonne Université, Ari brings a unique perspective that bridges scientific methodology with practical financial application.
Under Ari's leadership, Wangari has assembled a growing ecosystem of data scientists, engineers, and sustainability experts who share a commitment to rigorous analysis and meaningful impact. Our extended network includes accomplished alumni from Entrepreneurs First, the Collège des Ingénieurs, and leading European innovation programs.
Scientific Rigor
Research methodologies from world-class institutions applied to financial challenges
Collaborative Network
Diverse expertise across physics, data science, finance, and sustainability
Innovation Focus
Backed by leading entrepreneurship programs and venture builders
Why Causal Intelligence Matters for Your Organization
For Insurers
- Identify true risk drivers beyond traditional actuarial models
- Understand how sustainability factors causally impact loss ratios
- Automate complex reporting while improving accuracy
- Support evidence-based underwriting decisions
For Investors
- Move beyond ESG ratings to understand actual impact on returns
- Identify material factors that drive valuation
- Make allocation decisions based on causal evidence
- Demonstrate fiduciary responsibility with scientific rigor
10x
Analysis Speed
Complete comprehensive causal analyses in a fraction of traditional timelines
50+
Data Sources
Integrate structured and unstructured data from diverse origins
24/7
Continuous Monitoring
AI agents work around the clock to identify emerging patterns
The Science Behind Our Approach
Wangari's technology foundation rests on cutting-edge research in causal inference, machine learning, and agentic systems. Our approach combines established statistical methodologies with modern AI capabilities to deliver unprecedented insight into financial dynamics.
1
Causal Graphs
Build graphs representing hypothesized causal relationships
2
Counterfactual Analysis
Estimate what would have happened under different conditions
3
Agent-Based Processing
Deploy specialized AI agents for data gathering, analysis, and reporting
4
Continuous Learning
Systems improve over time as they process more data and receive feedback
Rigorous Validation
Every causal claim generated by our platform undergoes multiple validation steps. We employ techniques like instrumental variables, regression discontinuity, and difference-in-differences to ensure robustness. Our models are tested against out-of-sample data and subjected to sensitivity analysis to quantify uncertainty.
This commitment to scientific rigor means you can trust the insights we deliver — they're not just statistically significant, but causally meaningful.
