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Decision Maker Profiling Using Their Mental Behavior Pattern.

Flávio Luis de Mello¹, Sebastião Alves de Souza²

¹Electronic and Computer Engineering Department, Polytechnic School, Centro de Tecnologia, Ilha do Fundão, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil.

Frontiers in Psychology

|September 7, 2021

Summary

This study uses artificial intelligence (AI) to predict individual decisions by analyzing psychological and emotional indicators. The AI model accurately forecasts behavior, significantly improving prediction accuracy in debt negotiation scenarios.

Keywords:

artificial intelligence cognitive interactive pattern decision making degree of differentiation of self systemic-linking method

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Area of Science:

Psychology
Artificial Intelligence
Behavioral Economics

Background:

Predicting individual decision-making is complex, influenced by psychological and emotional factors.
Existing methods often lack the precision to account for nuanced human behavior.
Artificial intelligence offers potential for more accurate predictive modeling.

Purpose of the Study:

To develop and validate an AI-driven method for predicting individual decisions.
To identify and categorize psychological and emotional indicators relevant to decision-making.
To assess the efficacy of the method in a real-world financial context.

Main Methods:

Creation of primary and circumstantial indicators for psychological and emotional profiling.
Integration of these indicators to identify expected behavioral patterns.
Application of artificial intelligence techniques for predictive analysis.
Validation through assessment of four debtor decision variables in debt negotiation.

Main Results:

The developed method successfully predicted individual behavior patterns.
The mental functioning pattern indicator effectively signaled most likely decisions.
Prediction accuracy for debtor decisions was significantly improved, outperforming random prediction by sevenfold in the best case.
Even the least effective variable showed a 20% improvement over random prediction.

Conclusions:

The AI-based method provides a robust framework for predicting individual decisions.
Psychological and emotional indicators, when analyzed through AI, can reliably forecast behavior.
The approach demonstrates broad applicability across various decision-making domains beyond financial negotiations.