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Evidence record 13871 · automatically gathered

TRuE-XAI: causal and explainable ai framework for trustworthy corporate earnings growth forecasting

Forecasting corporate earnings growth is fundamental to investment, credit, and regulatory decision-making. Existing forecasting approaches either rely on restrictive linear assumptions or provide limited interpretability, making them less suitable for high-stakes financial applications. This study proposes a transparent and causally informed framework for predicting future corporate earnings growth from financial statement data. We present TRuE-XAI (Transparent, Rule-based, and Explainable Arti

Record details

Published: 27 July 2026
Source: Frontiers in Artificial Intelligence
Category: Research
Topics: Regulation · Safety & alignment · Transparency · Finance, VC & PE
Retrieved: 28 July 2026

source-onlyevidence status

These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.

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How to cite this record

ethics.ai (27 July 2026), “TRuE-XAI: causal and explainable ai framework for trustworthy corporate earnings growth forecasting,” evidence record 13871, https://ethics.ai/record/13871 (originally published by Frontiers in Artificial Intelligence).

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