MUMBAI, India, June 22 -- Intellectual Property India has published a patent application (202641070746 A) filed by Dhanavelu Anandan; Ms. Muthulakshmi. S; Mrs. D. Maalini; Mrs. V. Kavitha; Ms. Jeeva Shoruba; Ms. Kanaga A; Ms. Ilakaiya. G; and Ms. Madhumitha C on June 06, 2026, for Explainable Multimodal Framework For Financial Risk Assessment Using Llm-Driven Insights.
Inventors include Dhanavelu Anandan; Ms. Muthulakshmi. S; Mrs. D. Maalini; Mrs. V. Kavitha; Ms. Jeeva Shoruba; Ms. Kanaga A; Ms. Ilakaiya. G; and Ms. Madhumitha C.
The application for the patent was published on June 12, 2026, under issue no. 24/2026.
Abstract: The evaluation of financial risk is an important operation to any institution that wants to retain its stability and be able to make prudent decisions in relation to making investments. Conventional methods strongly depend on the formatted numerical data, which can be very unresponsive to the information that is available as unstructured text and other market indicators. This paper offers a Holistic Explainable Multimodal Financial Risk Assessment Framework, which combines structured financial measures, textual data on news, reports, and analyst commentary, other indicators, including social sentiment and macroeconomic measures. The use of a Large Language Model (LLM) is aimed at extracting a semantic feature, sentiment detection, and emergent trends to textual sources. These properties are combined with structured financial information in a multimodal learning system that makes better risk forecasting. In a bid to be transparent, the framework uses Explainable AI methods such as SHAP (SHapley Additive explanations) and attention-based visualization that gives valuable understanding of the role of every feature and modality. The real-world experimentation proves to have better predictive accuracy compared to traditional risk models and provide understandable actionable information. The proposed framework will provide the optimal balance between predictive accuracy, and explainability that will enable the financial institutions to produce transparent risk scores and implement adaptive strategies in uncertain markets.
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