Automated Financial Risk Assessment & Mitigation via Multi-Modal Data Fusion & HyperScore Optimization

**1. Abstract:** This paper presents a novel approach to financial risk assessment utilizing a multi-modal data ingestion and analysis pipeline. By combining structured financial data, unstructured textual reports (news, SEC filings), technical indicators, and market sentiment data, our system, leveraging a novel hierarchical evaluation architecture dubbed the HyperScore System (HSS), generates a robust and dynamically updated risk profile for individual securities and portfolios. This method provides a 10x improvement in risk detection accuracy compared to traditional quantitative methods, with wider applicability across diverse asset classes. The system is immediately commercializable, capable of integration with existing trading platforms and risk management systems, and offers a clear path to enhanced portfolio performance and reduced financial losses.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-08-09
DOI
https://doi.org/10.5281/zenodo.16784865
Primary Topic
Stock Market Forecasting Methods
Type
article
Field-Weighted Citation Impact
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article

Automated Financial Risk Assessment & Mitigation via Multi-Modal Data Fusion & HyperScore Optimization

Zenodo (CERN European Organization for Nuclear Research)
Stock Market Forecasting Methods
article

Automated Financial Risk Assessment & Mitigation via Multi-Modal Data Fusion & HyperScore Optimization

article en

Abstract

**1. Abstract:** This paper presents a novel approach to financial risk assessment utilizing a multi-modal data ingestion and analysis pipeline. By combining structured financial data, unstructured textual reports (news, SEC filings), technical indicators, and market sentiment data, our system, leveraging a novel hierarchical evaluation architecture dubbed the HyperScore System (HSS), generates a robust and dynamically updated risk profile for individual securities and portfolios. This method provides a 10x improvement in risk detection accuracy compared to traditional quantitative methods, with wider applicability across diverse asset classes. The system is immediately commercializable, capable of integration with existing trading platforms and risk management systems, and offers a clear path to enhanced portfolio performance and reduced financial losses.

Zenodo (CERN European Organization for Nuclear Research)
Freed–Hardeman University (US)
Partnerships for the goals
Openalex Percentile: Top 43%
Stock Market Forecasting Methods
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