Artificial intelligence (AI)-based system and method for processing assets and liabilities with integrated legacy planning

An artificial intelligence (AI)-based method for processing one or more assets and one or more liabilities of one or more users with integrated legacy planning, comprising:

• obtaining, by one or more hardware processors, through an authenticated user registration subsystem, at least one of:
• personal identifiable information (PII) and biometric data of at least one of:
• the one or more users and one or more beneficiaries;
• performing, by one or more hardware processors, authentication using at least one of:
• biometric authentication and multi-factor authentication, and dynamically adjusting authentication requirements based on contextual risk parameters including at least one of:
• device information, location, and user behavior patterns;
• obtaining, by the one or more hardware processors, through an asset tracking subsystem, at least one of:
• assets data and liabilities data, associated with the one or more assets and the one or more liabilities of the one or more users by integrating one or more application programming interfaces (APIs) with at least one of:
• one or more financial institutions, one or more investment firms, one or more insurance entities, and one or more global financial institutions;
• obtaining, by the one or more hardware processors, through the asset tracking subsystem, one or more financial documents related to at least one of:
• the assets data and the liabilities data from at least one of:
• the one or more users, the one or more financial institutions, the one or more investment firms, the one or more insurance entities, and the one or more global financial institutions;
• monitoring, by one or more hardware processors, transaction data associated with the one or more assets across one or more blockchain networks using smart contract event listeners to detect and track asset-related events in real-time;
• receiving, by one or more hardware processors, real-time updates on financial account status changes from one or more external systems using webhook subscriptions;
• applying, by one or more hardware processors, rate limiting to control a number of API requests made over time and caching frequently accessed data;
• classifying, by the one or more hardware processors through the asset tracking subsystem, the obtained at least one of:
• assets data, liabilities data, and one or more financial documents by exerting at least one of:
• one or more artificial intelligence (AI) models and one or more machine learning (ML) models for generating one or more graphical insights to depict a financial performance;
• generating the one or more graphical insights by constructing hierarchical data structures representing relationships among the one or more assets and the one or more liabilities, and performing space-optimized mapping of financial data elements within the hierarchical data structures;
• authorising, by the one or more hardware processors through a legacy planning subsystem, the one or more users to designate defined assets of the one or more assets and defined liabilities of the one or more liabilities to the one or more beneficiaries based on the generated one or more graphical insights;
• generating, by the one or more hardware processors through the legacy planning subsystem, a digital will by exerting at least one of:
• the one or more artificial intelligence (AI) models and the one or more machine learning (ML) models based on the designated defined assets and the defined liabilities to the one or more beneficiaries;
• integrating, by the one or more hardware processors through the legacy planning subsystem, one or more smart contracts on a blockchain network to store the generated digital will, and validating the one or more smart contracts using one or more formal verification techniques;
• monitoring, by the one or more hardware processors through an event detection subsystem configured with at least one of:
• the one or more artificial intelligence (AI) models and the one or more machine learning (ML) models, at least one of:
• the assets data and the liabilities data;
• determining one or more predefined triggering events by web scraping at least one of:
• one or more national registries and obituary data, and by obtaining health metrics data from one or more Internet of Things (IoT) devices associated with the one or more users, wherein the one or more predefined triggering events are determined based on anomalous patterns and inactivity detected in financial and sensor data;
• and
• systematising, by the one or more hardware processors through a legacy transfer activation subsystem, a transfer of the defined assets and the defined liabilities to the one or more beneficiaries based on validating the one or more predefined triggering events for legacy planning the one or more assets and the one or more liabilities of the one or more users to the one or more beneficiaries.