Victoria Leben

The AI Causal Graph delineates the true determinants of financial strength. At the top of the graph, data from public annual reports is inputted. These variables are synthesized to ultimately produce the Economic Capital Ratio. Green nodes signify the company's strengths relative to the market average, enhancing financial robustness, whereas red nodes indicate weaknesses.

The Causal Effects in each node indicate the individual impact of that variable on the final node, the Economic Capital Ratio. They reveal the extent to which the Economic Capital Ratio increases or decreases relative to the industry average. Cumulatively, these effects contribute to the overall Economic Capital Ratio.

The Input Variables consist of the absolute values from the public annual report data entered into the valuation model.

The output variables are the absolute values as calculated by the valuation model.

The Feature Distribution illustrates the distribution of the model variables' effect values across the industry. The specific effect of the company in question within this distribution is indicated by a black arrow. The top two charts highlight the company's greatest strengths, whereas the bottom two charts reveal its most significant weaknesses.

The strengths and weaknesses plot shows how the company's greatest strengths and weaknesses develop over time. The corresponding impact measures the percentage point increase or decrease in the Economic Capital Ratio.

The Regression compares the forecasted company valuation with the observed stock market values. A positive correlation suggests that the model effectively explains market prices. A company's valuation above the regression line indicates that the company is overvalued, otherwise it is undervalued.