Intelligent Pricing Mechanism of Consumer Finance Behavior Based on Multimodal Data Integration

Xirui Chen

doi:10.54254/2753-8818/2025.25324

Theoretical and Natural ScienceOpen access

Intelligent Pricing Mechanism of Consumer Finance Behavior Based on Multimodal Data Integration

Research Article

Open Access

Intelligent Pricing Mechanism of Consumer Finance Behavior Based on Multimodal Data Integration

Xirui Chen ^1*

¹ University College London, London, UK

^*Corresponding author: melodyroi99@gmail.com

Published on 20 July 2025

TNS Vol.130

ISSN (Print): 2753-8826

ISSN (Online): 2753-8818

ISBN (Print): 978-1-80590-289-8

ISBN (Online): 978-1-80590-290-4

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Abstract

In response to the limitations of traditional consumer-credit pricing models that rely on single-modal demographic and financial tables, this study develops and empirically validates a multimodal intelligent pricing framework that jointly exploits textual declarations, profile images and granular in-app behavioral logs. Each modality is encoded into a 128-dimensional embedding and fused through gated multimodal units and cross-modal attention to capture latent signals of repayment risk. The fused representation feeds a two-stage pipeline in which a deep classifier estimates individualized default probability and a reinforcement-learning policy converts this risk score into compliant, profit-maximising price adjustments. Using 120,000 real loan applications from an international fintech platform, the proposed model reduces mispricing loss by 17 % and lifts AUC to 0.879 compared with the best unimodal and gradient-boosted baselines, while meeting interest-rate caps in five regulatory regimes and sustaining 94 ms online latency. Attention heat-maps and SHAP analyses confirm that pricing decisions remain interpretable and free of single-feature dominance, satisfying emerging AI-governance requirements. The results demonstrate that rich multimodal cues substantially enhance pricing accuracy, fairness and operational robustness, offering a scalable blueprint for next-generation responsible consumer-finance systems.

Keywords:

consumer finance, multimodal data fusion, intelligent pricing, representation learning, fintech

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References

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References

[2]. Farimani, Saeede Anbaee, Majid Vafaei Jahan, and Amin Milani Fard. "An Adaptive Multimodal Learning Model for Financial Market Price Prediction." IEEE Access (2024).

[4]. Shrestha, Yash Raj, and Vivianna Fang He. "Integrating multimodal data and machine learning for entrepreneurship research." Strategic Entrepreneurship Journal (2023).

Cite this article

Chen,X. (2025). Intelligent Pricing Mechanism of Consumer Finance Behavior Based on Multimodal Data Integration. Theoretical and Natural Science,130,1-6.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

About volume

Volume title: The 3rd International Conference on Applied Physics and Mathematical Modeling

ISBN: 978-1-80590-289-8(Print) / 978-1-80590-290-4(Online)

Editor: Marwan Omar

Conference website: https://2025.confapmm.org/

Conference date: 31 October 2025

Series: Theoretical and Natural Science

Volume number: Vol.130

ISSN: 2753-8818(Print) / 2753-8826(Online)

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