The Indispensable Role of Multimodal AI in Modern Financial Fraud Detection: A Position Paper Leveraging Transaction, Voice, and Visual Data for Financial Security
DOI:
https://doi.org/10.63282/3050-9246.IJETCSIT-V6I2P108Keywords:
Multimodal AI, Fraud Detection, Risk mitigation, Financial Security, Voice Biometrics, Behavioral Biometrics, Visual Authentication, Deep Learning, Explainable AI, Privacy-by-Design, Customer Safety, Deepfakes, CyberSecurity, Transaction data analysis, Privacy, Operational Efficiency, Generative Adversarial Networks, SHAP, LIME, XAI, Federated Learning, Causal Inference, Edge AI, LLM, SLMAbstract
Financial fraud is growing in scale and also in terms of sophistication, highlighting the limitations and challenges of traditional detection systems in the financial sector. This position paper contends that multimodal artificial intelligence (AI), which unifies transaction analysis, voice biometrics, and visual authentication, represents a paradigm shift in the prevention of financial fraud. By integrating diverse data streams (historical transactions, voice patterns, visual identification, and behavioral biometrics), multimodal AI addresses the limitations of single-modal systems and tackles sophisticated fraud tactics, including AI-generated deepfakes and synthetic identities. We argue that multimodal AI delivers superior accuracy in fraud detection, reduces false positives, and enables continuous security. We provide evidence that financial institutions that incorporate multimodal AI architectures can achieve better fraud detection, risk mitigation, customer satisfaction, customer safety, and overall operational efficiency. The position paper highlights and explains mitigation approaches to key challenges such as the integration of complex data from various financial data sources, privacy regulations, and system complexity of solutions, while proposing effective strategies such as federated learning, privacy-by- design, and explainable AI. We emphasize that the integration of multimodal AI systems is not merely a technological upgrade in the financial services sector, but a strategic imperative for financial institutions seeking resilience against evolving threats. We call on leaders in the financial services industry, regulators, and AI researchers to collaborate and adopt multimodal AI architectures to ensure privacy, robustness, resilience, security, and fraud prevention for the global financial ecosystem
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References
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