Structured PREreview of Explainable and Hybrid AI Approaches for Corporate Financial Performance Forecasting: A Structured Literature Review

Does the introduction explain the objective of the research presented in the preprint?

Yes

Are the methods well-suited for this research?

Highly appropriate

Are the conclusions supported by the data?

Somewhat supported

“Consistent pattern” and “substantial improvements” are reasonable summaries, but the paper is still a structured literature review, so the strength of the evidence depends on the underlying studies’ heterogeneity and metrics. The claim that explainability “strengthens AI model risk governance” and “provides a substantiated basis for managerial decision-making” is directionally supported, but it is more interpretive than directly demonstrated empirically in the review. “Comprehensive integration into organisational processes has yet to be achieved” is supported as a literature-gap statement, but it is not the same as direct evidence from organizational deployment data.

Are the data presentations, including visualizations, well-suited to represent the data?

Somewhat appropriate and clear

Tables are visible with data. Not seeing any Graphs in throughout the document.

How clearly do the authors discuss, explain, and interpret their findings and potential next steps for the research?

Somewhat clearly

Is the preprint likely to advance academic knowledge?

Highly likely

Would it benefit from language editing?

No

Would you recommend this preprint to others?

Yes, it’s of high quality

Is it ready for attention from an editor, publisher or broader audience?

Yes, as it is

Competing interests

The author declares that they have no competing interests.

Use of Artificial Intelligence (AI)

The author declares that they used generative AI to come up with new ideas for their review.