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

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

one or more servers, comprising:

one or more hardware processors; and

a memory unit operatively connected to the one or more hardware processors, wherein the memory unit comprises a set of computer-readable instructions in form of a plurality of subsystems, configured to be executed by the one or more hardware processors, wherein the plurality of subsystems comprises:

an authenticated user registration subsystem configured to obtain 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, and to perform authentication using at least one of: biometric authentication and multi-factor authentication, wherein the authenticated user registration subsystem is further configured to dynamically adjust authentication requirements based on contextual risk parameters including at least one of: device information, location, and user behavior patterns;

an asset tracking subsystem configured to:

obtain 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;

obtain 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;

monitor 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;

receive real-time updates on financial account status changes from one or more external systems using webhook subscriptions;

apply rate limiting to control a number of API requests made over time and cache frequently accessed data; and

classify 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,

wherein generating the one or more graphical insights comprises 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;

a legacy planning subsystem configured to:

authorise 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;

generate 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 defined liabilities to the one or more beneficiaries; and

integrate one or more smart contracts on a blockchain network to store the generated digital will, wherein the one or more smart contracts are validated using one or more formal verification techniques;

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 to monitor at least one of: the assets data and the liabilities data for 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

a legacy transfer activation subsystem configured to systematise 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.

2 . The artificial intelligence (AI)-based system as claimed in claim 1 , wherein the one or more assets and the one or more liabilities of one or more users comprise at least one of: one or more equity components, and one or more income streams, one or more fixed assets, one or more digital assets, one or more retirement and pension accounts, one or more foreign currency holdings, loans, mortgages, credit card debt, and other financial obligations.

3 . The artificial intelligence (AI)-based system as claimed in claim 1 , wherein the personal identifiable information (PII) comprises at least one of: name, age, contact details, postal address data, and one or more identification documents, associated with at least one of: the one or more users and the one or more beneficiaries; and

the biometric data comprises at least one of: fingerprint data, facial recognition data, voiceprints, iris or retinal scans, and behavioural biometrics associated with at least one of: the one or more users and the one or more beneficiaries.

4 . The artificial intelligence (AI)-based system as claimed in claim 1 , wherein the authenticated user registration subsystem is configured to exert 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 one or more artificial intelligence (AI) models and the one or more machine learning (ML) models comprise at least one of: one or more Optical Character Recognition (OCR) models and one or more Natural Language Processing (NLP) models, to extract information from at least one of: the personal identifiable information (PII) and the biometric data and the one or more financial documents.

5 . The artificial intelligence (AI)-based system as claimed in claim 1 , wherein the asset tracking subsystem integrates the one or more application programming interfaces (APIs) comprise at least one of: an OAuth 2.0 authentication application programming interfaces (APIs), Representational State Transfer ful (RESTful) application programming interfaces (APIs), Open Financial Exchange (OFX) application programming interfaces (APIs), Financial Information Exchange (FIX) protocols, Payment Services Directive 2 (PSD2) application programming interfaces (APIs), WebSocket application programming interfaces (APIs), International Organization for Standardization (ISO) 20022 application programming interfaces (APIs), and blockchain application programming interfaces (APIs);

the asset tracking subsystem exerting at least one of: the one or more artificial intelligence (AI) models and the one or more machine learning (ML) models comprise at least one of: one or more convolutional neural networks (CNNs), a random forest, one or more gradient boosting machines (GBMs), one or more long short-term memory (LSTM) networks, one or more anomaly detection models, k-mean clustering, hierarchical clustering, Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and one or more pruning techniques;

the asset tracking subsystem exerting at least one of: the one or more artificial intelligence (AI) models and the one or more machine learning (ML) models comprise the one or more Natural Language Processing (NLP) models with one or more Bidirectional Encoder Representations from Transformers (BERT) models to analyse financial broadcast for financial trends to generate one or more graphical insights and depict on a dashboard; and

the asset tracking subsystem is configured with at least one of: one or more data visualization models and one or more time series forecasting models, for depicting the financial performance on the dashboard to track at least one of: the assets data and the liabilities data.

6 . The artificial intelligence (AI)-based system as claimed in claim 1 , wherein the one or more graphical insights comprise at least one of: a portfolio diversification analysis, risk assessment reports, a performance attribution analysis, tax efficiency recommendations, personalized investment opportunities, and scenario analysis for potential market events; and

the one or more graphical insights are generated based on at least one of: historical data associated with at least one of: the assets data, the liabilities data, and the one or more financial documents, statistical forecasting data, and predictive analytics data, to depict the financial performance.

7 . The artificial intelligence (AI)-based system as claimed in claim 1 , wherein the legacy planning subsystem is configured to suggest optimal allocation of the defined assets and the defined liabilities for legacy planning by exerting at least one of: the one or more artificial intelligence (AI) models and the one or more machine learning (ML) models comprise at least one of: one or more deep Q-networks, one or more policy gradient procedures, and one or more multi-agent reinforcement learning models;

the legacy planning subsystem comprises a beneficiary verification module, the beneficiary verification module is configured to authenticate the one or more beneficiaries by means of at least one of: government-issued identification, social security numbers, and the biometric data;

the legacy planning subsystem comprises a notification module configured to provide one or more alerts to the one or more beneficiaries about the designated defined assets and defined liabilities and the generated digital will; and

the legacy planning subsystem is configured to exert at least one of: the one or more artificial intelligence (AI) models and the one or more machine learning (ML) models comprise at least one of: the one or more Natural Language Processing (NLP) models, one or more generative pre-trained transformer (GPT) models, one or more named entity recognition (NER) models, one or more legal language generation models, one or more sentiment analysis models, one or more contextual embedding models, and one or more compliance check models, to generate the digital will in legally compliant language.

8 . The artificial intelligence (AI)-based system as claimed in claim 1 , wherein the 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 comprises at least one of: the one or more Natural Language Processing (NLP) models, the one or more named entity recognition (NER) models, the one or more sentiment analysis models, for web scraping.

9 . The artificial intelligence (AI)-based system as claimed in claim 1 , wherein the one or more predefined triggering events comprises at least one of: account inactivity, death of the one or more users, significant health events notified by the one or more users, and abnormal metrics data detected by one or more Internet of Things (IoT) devices associated with the one or more users.

10 . The artificial intelligence (AI)-based system as claimed in claim 1 , wherein the legacy transfer activation subsystem is configured with a multi-signature approval module,

the multi-signature approval module is configured to validate the transfer of the defined assets and the defined liability, requiring signatures from one of: at least two trusted contacts and at least two legal representatives to confirm the one or more predefined triggering events;

the legacy transfer activation subsystem is configured to obtain health metrics data through the one or more Internet of Things (IoT) devices associated with the one or more users for detecting the abnormal metrics data.

11 . The artificial intelligence (AI)-based system as claimed in claim 1 , wherein the plurality of subsystems comprises a data security subsystem,

the data security subsystem configured to encrypt at least one of: the personal identifiable information (PII), the biometric data, the assets data, the liabilities data, and the one or more financial documents with one or more tokenization procedures for at least one of:

secure data storage, safeguarding sensitive information, averting unauthorized access, and supporting auditability and traceability;

the data security subsystem is configured with one or more cryptographic proof models to authenticate the one or more beneficiaries while preserving a confidentiality of at least one of: the personal identifiable information (PII), the biometric data, the assets data, the liabilities data, and the one or more financial documents; and

the data security subsystem configured with a continuous penetration testing module, the continuous penetration testing module is configured to perform a continuous testing security of the artificial intelligence (AI)-based system for identifying vulnerabilities by exerting at least one of: Nessus® and Qualys®.

12 . The artificial intelligence (AI)-based system as claimed in claim 1 , wherein the plurality of subsystems comprises a beneficiary assistance subsystem,

the beneficiary assistance subsystem is configured to:

provide guidance to the one or more beneficiaries on accessing and claiming the designated defined assets and the defined liabilities;

recover the one or more assets and the one or more liabilities by integrating with at least one of: data mining procedures, network analysis procedures, blockchain explorers and multi-signature wallets;

provide at least one of: a tax guidance and an inheritance guidance using one or more artificial intelligence (AI)-driven tax optimization tools and one or more compliance tools to reduce tax liabilities associated with the defined assets and the defined liabilities; and

connect the one or more beneficiaries with one or more certified professionals for personalized assistance and support through an inheritance process of the defined assets and the defined liabilities.

13 . 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.