Digital asset securitization and data automation system in the finance sector

Abstract

The invention is reiated to a digital asset securitization and data automation system and method utilized by finance sector players such as banks, financial institutions, asset management companies, i

Description

[0001] DIGITAL ASSET SECURITIZATION AND DATA AUTOMATION SYSTEM IN THE FINANCE SECTOR

[0002] Technical Field

[0003] The invention rebates to a digital asset securitization and data automation system and method that is used by finance sector players such as banks, financial institutions, asset and portfolio management companies, investment funds, insurance companies, capital market organizations, and other service providers. It enables the efficient, transparent, and secure securitization of credits and receivables such as loans, invoice receivables, note receivables, consumer and commercial debts, and future receivables using smart contracts and blockchain technology, thereby enhancing operational excellence and regulatory compliance in the finance sector.

[0004] Backgroung Art

[0005] In existing financial systems, particularly in securitization and security issuance processes, they are often conducted through various manual methods and inadequate automatic systems. These processes are prone to errors, time-consuming, and do not support real-time updates. Specifically, in complex processes such as credit transfers and risk analyses, the necessary data processing and analytical capabilities are limited or entirely lacking. Yet, the accurate and consistent execution of financial analyses is a fundamental part of the system. In the finance sector, the accuracy, currency, and depth of such information are critically important for risk management and regulatory compliance.

[0006] Due to the inadequacies in current systems, there has been a need for a system and method that increases the level of automation and accuracy in financial engineering processes, reduces data entry errors, accelerates transaction processes, and thereby improves the accuracy and consistency of financial analyses.

[0007] Consequently, the existence of the above problems and the inadequacy of current solutions have necessitated a development in the relevant technical field. Objective of the Invention

[0008] The present invention relates to a digital asset securitization and data automation system and method in the finance sector, which eliminates the disadvantages mentioned above and introduces new advantages to the relevant technical field.

[0009] The main objective of the invention is to provide a digital asset securitization and data automation system method that enables banks, financial institutions, and firms generating due invoices and note receivables to efficiently and securely securitize receivables such as loans, invoice receivables, note receivables, and future receivables. This system ensures the secure return of these securities to the user and simultaneously allows users to continuously monitor their transactions without interruption.

[0010] The objective of the invention is to introduce a digital asset securitization and data automation system and method that enhances the level of automation and accuracy in financial engineering processes, reduces data entry errors, accelerates transaction processes, improves the accuracy and consistency of financial analyses, and also, by providing real-time monitoring and updates, increases the transparency and compliance of financial transactions.

[0011] Another objective of the invention is to present a digital asset securitization and data automation system and method that aims to significantly enhance security and transparency in financial engineering processes by using smart contracts and a blockchain-based data structure. Blockchain technology ensures the accuracy and immutability of transactions by securely storing and tracking all transaction summaries (hashes). Smart contracts enable the automation of transaction processes and the calculation of compounding interests, transfer costs, and other critical financial parameters. Web3 technology, while utilizing symmetric and asymmetric encryption mechanisms, also provides users with a secure communication infrastructure resistant to quantum computing, offering secure access to user funds and the necessary infrastructure for real-time monitoring of transactions. This integrated system allows users to have full control over financial transactions and ensures that these transactions are conducted in a transparent, secure, and regulatory-compliant manner. Another objective of the invention is to introduce a digital asset securitization and data automation system and method that focuses on the tokenization process, enabling financial assets to be converted into digital tokens and represented on the blockchain through this technology. With this approach, the digitization of assets contributes to making the management of securities more efficient, transparent, and accessible. Tokenization allows for the fractionalization of assets and provides broader access to different investor segments. Furthermore, integrating this process with blockchain technology not only enhances the security and transparency of tracking and managing securities but also significantly improves the speed and efficiency of transactions. This innovative approach supports liquidity and data accuracy in financial markets, while also contributing to regulatory compliance.

[0012] Another objective of the invention is to present a digital asset securitization and data automation system and method that increases the accuracy of cash flow forecasts by using 'true sale' transactions and models based on historical data. For this purpose, it aims to model the cash flows of assets and financial products more precisely and reliably by utilizing automated machine learning technology. This technology significantly improves the accuracy in coupon and interest predictions, enhancing the performance and analytical capabilities of the financial data automation system. This approach increases efficiency in the valuation and management of financial assets, providing results based on more robust foundations for risk management and investment decisions.

[0013] Another objective of the invention is to introduce a digital asset securitization and data automation system and method that enhances the security and transparency of financial transactions through blockchain and smart contracts, ensuring the accuracy and immutability of transactions. This approach offers improvements in financial reporting and regulatory compliance.

[0014] Another objective of the invention is to present a digital asset securitization and data automation system and method that facilitates the conversion of assets into digital tokens and provides broader access to these assets for a wider range of investors, thereby increasing liquidity in the securitization process. Additionally, it aims to make traditional asset classes more accessible and divisible through tokenization. Another objective of the invention is to present a digital asset securitization and data automation system and method that, through the Web3 infrastructure, offers users the ability to manage their financial transactions in a secure and encrypted environment, enabling users to conduct and monitor their transactions with their own keys in blockchain-based applications.

[0015] Another objective of the invention is to introduce a digital asset securitization and data automation system and method that automates complex financial transactions through smart contracts, speeding up processes and reducing error rates, thereby increasing operational efficiency and lowering transaction costs.

[0016] Another objective of the invention is to introduce a digital asset securitization and data automation system and method that offers flexible and scalable solutions for financial institutions of different sizes, enabling systems to quickly adapt to various financial scenarios and changing market conditions.

[0017] Another objective of the invention is to present a digital asset securitization and data automation system and method that enables companies and ventures operating in the field of blockchain technology and smart contracts to benefit from the advantages of data accuracy, security, and automation.

[0018] Another objective of the invention is to present a digital asset securitization and data automation system and method that enables institutions conducting risk management and investment analysis to make more accurate risk assessments and investment decisions with advanced data analysis and modeling capabilities.

[0019] Another objective of the invention is to introduce a digital asset securitization and data automation system and method that enables companies providing financial technology solutions and software developers to enhance the development of their financial products and services.

[0020] Another objective of the invention is to introduce a digital asset securitization and data automation system and method that enables financial regulatory bodies and companies concerned with legal compliance to more easily adhere to regulatory requirements with enhanced transparency and traceability. The structural and characteristic features of the invention and all its advantages will be understood more clearly through the detailed description written with references to the provided figures. Therefore, the evaluation should be made considering these figures and the detailed description.

[0021] Figures to Aid in Understanding the Invention

[0022] Figure 1 : Schematic diagram of the digital asset securitization and data automation system subject to the invention.

[0023] Explanation of Part References

[0024] 10. Data Center

[0025] 11. Asset Selection User Interface

[0026] 20. Automated Machine Learning System

[0027] 30. Design System

[0028] 40. Smart Contract

[0029] 50. Blockchain Infrastructure

[0030] 60. Web3 Infrastructure

[0031] 70. Continuous Monitoring Environment

[0032] O. Originator

[0033] UF. User Fund

[0034] Detailed Description of the Invention

[0035] In this detailed description, the preferred alternatives of the digital asset securitization and data automation system subject to the invention are explained in a manner aimed solely at facilitating a better understanding of the topic, without any limiting effect.

[0036] Figure 1 provides the schematic diagram of the digital asset securitization and data automation system subject to the invention. Accordingly, at its most basic level, the financial data automation system is designed based on data dictionaries arranged according to the type of asset (such as individual and commercial loans, invoice receivables, note receivables, leasing agreements, rent certificates, consumer finance receivables, credit card debts, mortgage receivables, commercial and real estate mortgage receivables, supply chain finance receivables, healthcare receivables, student loans, automobile finance receivables, and other future receivables). It involves a data center (10) that collects data from the database of the originator (O), referencing the designed data dictionaries based on the asset type. An automated machine learning system (20) that models the data transmitted from the data center (10) using software it possesses, by employing hyperparameter tuning machine learning algorithms, determines the model that achieves the highest performance through hyperparameter tuning and applies it to the receivables according to criteria set by the user to generate future forecasts. A design system (30) that uses the forecasts and cash flows obtained from the model created in the automated machine learning system (20) to design the securitization product according to the user's financial engineering. A smart contract (40) that automates the data designed in the design system (30) and calculates compounding interest, asset transfer costs, and other parameters. A blockchain infrastructure (50) that, through the smart contract (40), processes gains and yield parameters using both private and public ledgers to ensure the security and privacy of user data, converting the user's asset into a stable crypto asset indexed in a one-to-one manner. A Web3 infrastructure (60) that ensures secure access of users to their user fund (UF). A continuous monitoring environment (70) that allows users to monitor and inspect their unique transactions through the application programming interface (API) using their registered key pair (public-private) on the system.

[0037] The data center (10), which forms the core structure of the digital asset securitization and data automation system subject to the invention, is a unit that collects data from the database of the originator (O) based on data dictionaries designed according to the type of asset (such as individual and commercial loans, invoice receivables, note receivables, leasing agreements, rent certificates, consumer finance receivables, credit card debts, mortgage receivables, commercial and real estate mortgage receivables, supply chain finance receivables, healthcare receivables, student loans, automobile finance receivables, and other future receivables), through electronic devices. The mentioned originator (O) includes institutions that provide loans or receivables and special purpose vehicles (funds). The data center (10), operated through an electronic device, generates data for the automated machine learning system (20). The asset selection interface (1 1 ) located in the data center (10) is an interface that allows users to select the assets they want to securitize from the data available in the data center (20), based on the characteristics they desire.

[0038] The automated machine learning system (20) is a system that models the data transmitted from the data center (10) using hyperparameter tuning machine learning algorithms, identifies the model that provides the highest performance through hyperparameter adjustment, and applies it to the receivables according to criteria set by the user to generate future forecasts. In the automated machine learning system (20), advanced modeling for receivables and loans is conducted, and cash flows are planned.

[0039] The design system (30) is a system that utilizes the models created and approved by the automated machine learning system (20) to design securities products. In the design system (30), forecasted cash flows and other critical financial data are integrated, allowing the shaping of the securities' maturity, payment type, and other significant features according to parameters defined by the user. Users can adjust the potential returns on investment and reinvestment rates based on expected cash flows. Using this information, they calculate the total cost of the security and the structure of related financial products. Furthermore, the design system (30) supports the necessary internal approval processes for asset transfers and securitization transactions, thereby managing the entire process in a transparent and efficient manner.

[0040] The smart contract (40) enables the automatic application of the features of financial products designed in the design system (30) via the blockchain infrastructure (50). The smart contract (40) flexibly manages financial parameters, such as interest rates, which can be set by the user. After users adjust these parameters according to their requirements, the smart contract (40) calculates asset transfer costs and, working in integration with the blockchain infrastructure (50), confirms the security and accuracy of this data. Additionally, the smart contract (40) facilitates the preparation of these financial products for the credit rating process, thus providing a more transparent evaluation for investors and other stakeholders.

[0041] The blockchain infrastructure (50) processes user-defined parameters through the smart contract (40) using both private and public ledgers to ensure the security and privacy of user data. Public ledgers store data common to all users, while private ledgers protect information specific to an individual user. Transactions are hashed to ensure their accuracy and immutability (integrity). Assets owned by the user are converted one-to-one into a stable crypto asset indexed to the blockchain infrastructure (50), enabling the instant and 24 / 7 swapping of the user's assets through a stable crypto asset.

[0042] In the blockchain infrastructure (50), the conversion of assets into digital tokens enhances the liquidity and accessibility of financial transactions. The tokenization process makes traditional asset classes more accessible and divisible, increasing the efficiency and transparency of financial transactions.

[0043] The Web3 infrastructure (60) provides users with secure access to their user fund (UF). It features advanced communication infrastructure that facilitates secure access to the user fund (UF). In the Web3 infrastructure (60), quantum-resistant encryption and key infrastructures are used with the deployment of next-generation technology, whereas public key infrastructure (PKI), symmetric, and asymmetric encryption infrastructures are utilized with current technology. The Web3 infrastructure (60) ensures the processes of trust accounting and converting assets into cash are conducted between the blockchain infrastructure (50) and the user fund (UF).

[0044] The continuous monitoring environment (70) allows users to monitor and inspect their unique transactions via the application programming interface (API) using their registered key pair (public-private) on the system.

[0045] The operational steps of the digital asset securitization and data automation method subject to the invention are as follows: a) The user initiates the process by conducting transactions through the data center (10) based on criteria determined via the asset selection interface (11 ), b) The data in the data center (10), after undergoing data preparation processes, is transmitted to the automated machine learning system (20), where modeling data on the assets is created, c) Designing the securities product using forecasts and cash flows obtained from the model through the design system (30), d) After the reevaluation process in the design system (30) is completed, processing the parameters determined by the user with smart contracts (40) that have a data structure, where smart contracts (40) receive variables from the user to calculate the asset transfer costs and transfer this information to the distributed ledger in the blockchain infrastructure (50), e) Processing the data received from the smart contracts (40) with the blockchain infrastructure and converting user assets into stable crypto assets on the blockchain infrastructure (50), f) Providing secure access for users of the blockchain infrastructure (50) to the user fund (UP) via the Web3 infrastructure (60), g) Users monitoring and reviewing their own transactions through the continuous monitoring environment (70).

[0046] In the mentioned step (b), the automated machine learning system (20) generates various models using model production and hyperparameter tuning machine learning algorithms. It determines the model that achieves the highest performance through hyperparameter tuning. Additionally, the selected model is applied to the receivables based on criteria defined by the user to generate future forecasts.

[0047] In the mentioned step (c), within the design system (30), the characteristics of the security (such as maturity, type of payment, etc.) are determined. The user calculates a turnover cost for the final entity by setting the reinvestment rate for cash flows, and the final assets to be transferred and the security product are finalized through internal approval mechanisms.

[0048] In the mentioned step (e), within the blockchain infrastructure (50), both private and public ledgers are used, where common characteristics of each user's transaction are stored in public ledgers, and private information is protected in private ledgers. This ensures the integrity and security of the transactions. Additionally, in this step (e), assets within the blockchain infrastructure (50) can be indexed and swapped.

Claims

CLAIMS1. A digital asset securitization and data automation system used in the fields of financial services and data science, particularly for the digital end-to-end automation of securitization transactions and data analysis processes, characterized by:- data center (10) that operates through electronic devices and collects data from the originator's (O) database based on data dictionaries designed according to the type of asset (such as individual and commercial loans and credits, invoice receivables, note receivables, leasing agreements, rent certificates, consumer finance receivables, credit card debts, mortgage receivables, commercial and real estate mortgage receivables, supply chain finance receivables, healthcare receivables, student loans, automobile finance receivables, and other future receivables),- automated machine learning system (20) that models the data transmitted from the data center (10) using hyperparameter tuning machine learning algorithms, identifies the model that achieves the highest performance through hyperparameter tuning, and generates future forecasts based on the receivables according to criteria defined by the user,- design system (30) that uses the models created and approved by the automated machine learning system (20) to design securities products,- smart contract (40) in the design system (30) that automatically applies the features of financial products and calculates asset transfer costs,- blockchain infrastructure (50) that processes user-defined parameters through the smart contract (40), using both private and public ledgers to ensure the security and privacy of user data and converts the user's asset into a stable crypto asset indexed in a one-to-one manner,- Web3 infrastructure (60) that provides secure access for users to their user fund (UF), continuous monitoring environment (70) that enables users to monitor and review their unique transactions through the application programming interface (API) using their registered key pair (publicprivate).

2. A digital asset securitization and data automation system according to claim 1 , characterized by including an asset selection interface (11 ) located in the data center (10) that enables users to select the assets they want to securitize from the data in the data center (20) according to the desired characteristics.

3. A digital asset securitization and data automation method used in the fields of financial services and data science, particularly for the digital end-to-end automation of securitization transactions and data analysis processes, characterized by the following operational steps: a) The user initiating the process by conducting transactions through the data center (10) based on criteria determined via the asset selection interface (11 ), b) The data in the data center (10), after undergoing data preparation processes, being transmitted to the automated machine learning system (20), where modeling data on the assets is created, c) Designing the securities product using forecasts and cash flows obtained from the model through the design system (30), d) After the reevaluation process in the design system (30) is completed, processing the parameters determined by the user with smart contracts (40) that have a data structure, and these smart contracts (40) calculating the asset transfer costs and transferring this information to the distributed ledger in the blockchain infrastructure (50), e) Processing the data received from the smart contracts (40) with the blockchain infrastructure and converting user assets into stable crypto assets on the blockchain infrastructure (50), f) Providing secure access for users of the blockchain infrastructure (50) to the user fund (UP) via the Web3 infrastructure (60), g) Users monitoring and reviewing their own transactions through the continuous monitoring environment (70).

Images