An AI-powered system for personalized financial advisory chatbots using LLMs and real-time data integration

Abstract

An AI-driven system (100) for a personalized chatbot for financial advice using LLMS and real-time data integration, comprising the following: a chatbot module based on a large language model (LLM) that is configured to process user requests and generate personalized financial recommendations by using natural language understanding and historical data patterns; a real-time data processing module configured to retrieve and process financial data from stock exchanges, banking systems, government economic reports and financial news sources, continuously updating relevant financial information such as stock prices, interest rates and economic indicators; a risk assessment module configured to analyze a user's financial profile, including their risk tolerance, investment history and financial objectives, to ensure regulatory compliance and the suitability of investment recommendations in accordance with relevant financial regulations; an adaptive module based on machine learning that is configured to refine and optimize financial recommendations based on user interactions, financial trends, historical data and evolving market conditions, learning from past user behavior and adapting to changing market dynamics; a natural language processing module that facilitates interactive interaction with the user through text, speech, and graphical financial reports, thus enabling multimodal interaction to improve user experience and understanding of complex financial information; a proactive warning module configured to inform users about investment opportunities, market risks, and necessary portfolio adjustments based on real-time market data, trend analyses, and predictive models; a security and compliance module that ensures encrypted data transmission, user authentication and compliance with financial data protection regulations, including the secure storage of sensitive financial data and adherence to industry standards such as GDPR and PCI-DSS.

Description

The present invention relates to artificial intelligence (AI)-based financial consulting systems. In particular, it is a chatbot that uses large language models (LLMs) and integration of financial data in real time to give personalized financial recommendations.One of the major limitations of conventional financial consulting services is their limited personalization. Conventional robotics advisors rely primarily on static rule-based models that do not take into account dynamic changes in a user's financial status or market conditions. As a result, the recommendations provided are often generic and fail to provide a contextual understanding of a person's specific financial history, output behavior, or future desires.Another critical disadvantage is the lack of data integration in real time. Many existing consulting systems depend on static data sets or periodic updates, which can lead to legacy or suboptimal plant recommendations. The inability to integrate stock prices, interest rates, market news and business indicators in real time limits the effectiveness of these systems, particularly under volatile market conditions.In addition, conventional systems often lack flexibility and continuous learning. Many Robo advisors operate with rigid frameworks that do not develop based on user feedback or changing financial goals. This results in suboptimal financial planning, since the system cannot adapt its recommendations to life events such as workplace changes, conjunctival waste or changes in plant goals.Moreover, compliance with financial regulations and risk assessment remains a challenge for traditional systems. Many rule-based consulting tools do not include AI-driven risk assessment techniques, which may result in plant suggestions that do not conform to an attendant's risk tolerance or regulatory guidelines. This increases the risk of financial mishandling and non-compliance with financial laws.Finally, user-friendliness and interpretability continue to provide a source. Many financial consulting platforms provide numerical results and complex analyses that are difficult to understand for small-scale employees. The lack of a natural language interactive interface makes it difficult for users to interpret recommendations and make informed plant decisions.In view of these disadvantages, there is a need for an AI-controlled chatbot for financial consulting that uses Large Language Models (LLMs) and integration of financial data in real time to provide highly personalized, adaptive, and compliant financial consulting. The present invention addresses these challenges by introducing an intelligent chatbot that dynamically processes user financial data, integrates real-time market insights, and continuously refines recommendations based on user feedback and evolving financial conditions.To solve this problem, the present invention provides an AI-controlled system for personalized financial consulting chatbotes using LLMS and real-time data integration.The AI-driven system for personalized financial consulting chatbotes that utilizes LLMS and real-time data integration can provide personalized financial recommendations by employing LLMs that are capable of understanding the preferences, financial goals, risk tolerance, and output behavior of the users through natural language interactions.The personalized financial consulting chatbots AI-controlled system that utilizes LLMS and real-time data integration may integrate real-time financial data from various sources, including stock markets, bank APIs, state business indicators, and financial messages to provide current plant recommendations.The AI-controlled system for personalized financial consulting chatbotes that utilizes LLMS and real-time data integration may enable continuous learning and adaptation by refining financial strategies based on user feedback, past interactions, and changing financial circumstances, thus ensuring dynamic and relevant consulting assistance.The AI-directed system for personalized financial consulting chatbotes that utilizes LLMS and real-time data integration may improve risk assessment and compliance with legal requirements by employing AI-directed risk assessment techniques that conform plant recommendations to legal constraints and risk profiles of the users.The AI-driven personalized financial consulting chatbote system that utilizes LLMS and real-time data integration can improve the engagement and interpretability of the users by offering a conversational AI chatbote with an intuitive, user-friendly surface that explains financial insight in simple, comprehensible language.The AI-driven personalized financial consulting chatbote system that uses LLMS and real-time data integration can provide security and privacy by implementing robust encryption and authentication mechanisms as well as secure API integrations to protect sensitive financial data.The AI-driven personalized financial consulting chatbote system that uses LLMS and real-time data integration can provide multi-modal interaction capabilities by supporting text, voice, and graphical financial reports and making the chatbote accessible across various devices and user preferences.The AI-driven personalized financial consulting chatbote system, utilizing LLMS and real-time data integration, can provide proactive financial alerts and insights by monitoring market trends and informing users of potential equipment capabilities, risks, or necessary portfolio adaptations.The AI-controlled system for personalized financial consulting chatbotes that utilizes LLMS and real-time data integration can facilitate seamless integration with financial services from third-party providers such as online trading platforms, banking applications, and control management tools, thus improving the overall financial consulting experience.In one embodiment, an AI-controlled system is provided for a personalized financial consulting chatbot with LLMS and real-time data integration. The AI-driven financial consulting chatbot uses large language models (LLMs) and real-time data integration to provide personalized, adaptive, and regulatory-compliant financial recommendations. The system has been developed to overcome the limitations of conventional financial consulting techniques by incorporating advanced AI techniques, real-time market data processing, and continuous learning mechanisms to provide dynamic and context aware financial consulting. The chatbot interacts with users through natural language processing (NLP) and allows them to obtain customized plant strategies, insight into portfolio management, risk scores, and financial planning recommendations based on their specific financial goals, their risk readiness, and their output behavior. By utilizing real-time stock market data, banking APIs, business indicators, and financial messages, the system ensures that plant decisions remain relevant and up-to-date. The system has continuous learning and flexibility that allows the chatbot to refine its recommendations based on user feedback, historical investment trends, and changing financial conditions. In addition, the system includes an AI-controlled risk assessment to conform financial strategies to regulatory compliance standards, thus minimizing financial misexpansion risks. The system also focuses on improving the user's engagement and interpretability by providing a conversational intuitive interface that explains complex financial insights in a simplified manner. The chatbot supports multimodal interactions including text, speech and financial graphics reports and is thus accessible to various user settings and devices. In addition, the system integrates proactive financial alerts and insights that inform users of potential facilities, market risks, or necessary portfolio adaptations. The system is also designed to be seamless with financial services from third party providers such as trading platforms, banking applications, and control management tools, thus offering a comprehensive financial consulting experience. By combining AI-controlled decision making, real-time financial data processing, and secure user interactions, the system provides a smart, scalable, and cost effective solution for personalized financial consulting services and makes professional financial consulting accessible to a wider audience.The invention is explained again below with reference to the figure. The following shows: FIG. 1 : shows an AI-controlled system for a personalized financial consulting chatbot with LLMS and real-time data integration.FIG. 1 shows an AI-controlled system (100) for a personalized financial consulting chatbot using LLMS and real-time data integration. The system (100) is designed to provide personalized financial recommendations and to provide continuous adaptation to changing market conditions. The system (100) includes a chatbot module based on a large speech model (LLM), a real-time data processing module, a risk assessment module, a machine learning based adaptive module, a natural speech processing module, a proactive alert module, and a security and compliance module. Each of these modules cooperate to provide dynamic, real-time, and secure financial consultants to users. The LLM-based chatbot module serves the users as a primary interface for interaction with the system ( 100). This module utilizes advanced natural language processing techniques to understand user requests and generate personalized financial recommendations based on historical data patterns, user inputs, and financial goals. The chatbot module is able to interact with the users, making the system (100) very accessible and user-friendly. By processing the user requests, the chatbot provides customized advice and guides the user through various financial strategies. The real-time data processing module retrieves and processes financial data from a variety of sources, including exchanges, banking systems (100), government inventory reports, and financial messaging sources. This module continuously monitors and updates financial data such as stock prices, interest rates, business indicators and other relevant market trends. By providing current financial information, the real-time data processing module allows the system (100) to have a timely and accurate financial advice that ensures that users will receive an advice based on the latest market conditions. The risk assessment module is responsible for analysing a user's financial profile to ensure that the recommendations provided by the system (100) conform to its risk tolerance, financial goals, and regulatory requirements. This module evaluates various factors including the investment history, risk preferences, and financial goals of the user to create a personalized risk profile. By integrating legal compliance checks, the risk assessment module ensures that all plant recommendations conform to the relevant financial regulations and suitability standards. The machine learning based adaptive module plays a key role in refining the recommendations of the system (100) over time. It utilizes machine learning techniques, including reinforcement learning, to continuously optimize financial consulting for users. By analyzing past user interactions, financial results, and evolving market trends, this module adjusts the recommendations to account for changes in user behavior and market conditions. The ability of the adaptive module to learn from historical data ensures that the system (100) will give more and more relevant and accurate beats. The natural language processing module (NLP) enhances user interaction by enabling communication via text, speech, and financial graphical reports. This module uses mood analysis and contextual voice processing to ensure that the system (100) understands emotional sound and intent behind the user requests. By including NLP, the system (100) can provide more nuanced contextual advice to improve user satisfaction and engagement. The proactive alert module is designed to inform users of equipment capabilities, market risks, and necessary portfolio adjustments. Through the use of real-time data and prediction models, this module proactively informs users of significant market changes or events that may affect their financial position. The warning messages can be customized by the user so that they can be notified via the communication channels preferred by them, such as push notifications, e-mails or text messages. Finally, the security and compliance module provides that the system (100) complies with industry standards for data protection and security. It encrypts the entire transmission of financial data and provides secure authentication methods, including two-factor authentication, to protect the user data. The module also ensures compliance with privacy regulations such as GDPR and PCI-DSS and protects the sensitive financial data from during the entire interaction of the user with the system (100). Each of these modules is designed to operate together seamlessly so that the system (100) can provide financial consulting integrated services. The real-time computing module feeds current financial information to the risk assessment and machine learning modules and ensures that the generated recommendations are relevant and compliant. The natural language processing module provides for the integration of users while the proactive alert module keeps the users on the fly about critical developments. The security and compliance module provides the integrity of the system (100) by providing secure and lawful data processing. By integrating these modules, the AI-controlled financial consulting system (100) provides personalized, adaptive, and secure financial consulting that continues to develop in real time with changing market conditions and user preferences.List of reference characters100 System

Claims

A AI-controlled system (100) for a personalized chatbot for financial consulting using LLMS and real-time data integration, comprising: a chatbot module based on a large language model (LLM) configured to process user requests and generate personalized financial recommendations using natural language understanding and historical data patterns; a real-time data processing module configured to retrieve and process financial data from exchanges, banking systems, state business reports, and financial messaging sources, wherein relevant financial information such as stock prices, interest sets, and business indicators is continuously updated; a risk assessment module configured to analyze a user's financial profile including its risk tolerance, investment history, and financial goals to ensure compliance with rules and suitability of investment recommendations in accordance with the relevant financial rules; a machine learning based adaptive module configured to refine and optimize financial recommendations based on user interactions, financial trends, historical data, and evolving market conditions, learning from the prior user behavior and adapting to the changing market dynamics; a natural language processing module that facilitates interactive interaction with the user through text, speech, and graphical financial reports, thus allowing multimodal interaction to improve user experience and understanding of complex financial information; a proactive alert module configured to inform the users about installation capabilities, market risks, and necessary portfolio adjustments based on real-time market data, trend analysis, and prediction models; a security and compliance module that ensures encrypted data transmission, user authentication, and compliance with financial data protection regulations, including secure storage of sensitive financial data and compliance with industry standards such as GDPR and PCI-DSS.The system (100) of claim 1, wherein the LLM-based chatbot module dynamically adjusts financial strategies in response to real-time market fluctuations such as stock quote changes, business data publications, and geopolitical events, as well as user behavior patterns including risk tolerance changes and investment preferences changes.The system (100) of claim 1, wherein the real-time computing module continuously retrieves and processes financial data including stock prices, interest rates, change rates, and business indicators from multiple live data sources such as APIs, market feeds, and state databases to provide current financial advice and recommendations to users.The system (100) of claim 1, wherein the risk assessment module includes a user interface for users to manually input financial goals, preferences, and other relevant data, enabling personalized risk profiles and customized financial consulting.The system (100) of claim 1, wherein the machine learning based adaptive module uses reinforcement learning techniques to optimize plant recommendations by continuously analyzing past user interactions, financial results, and market trends.The system (100) of claim 1, wherein the proactive alert module includes a user preference configuration function that enables users to adjust the type, frequency, and method of conveying alerts such as email, text message, or push notification.The system (100) of claim 1, wherein the natural language processing module comprises mood analysis to evaluate and interpret emotional sound of user requests and responses and provide a more contextual financial advice based on the mood of the user.The system (100) of claim 1, wherein the security and conformance module is integrated with third party authentication services, such as two-factor authentication, for enhanced user verification and protection of sensitive financial data.The system (100) of claim 1, wherein the financial consulting system (100) is deployed on a cloud-based platform that ensures scalability, high availability, and secure storage of user data in accordance with the regulations of the financial industry.The system (100) of claim 1, wherein the system (100) further includes a control optimization module configured to generate control-efficient plant strategies and portfolio recommendations that ensure compliance with control rules based on the control information provided by the user.

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