TWM670157U - Integrated account inquiry system for bank customers - Google Patents

Abstract

An integrated account inquiry system for bank customers, which includes an online banking server, a smart income and expenditure ledger web server communicatively connected to the online banking server, a system database communicatively connected to the smart income and expenditure ledger web server to store account information, and a user terminal communicatively connected to the online banking server. The user terminal can access the smart income and expenditure ledger web server through the online banking server for querying the account information stored in the system database. The account information at least includes integrating the bank transaction details and credit card transaction details of bank customers, and automatically classifying the transaction details of the bank transaction details and the credit card transaction details.

Description

Bank Customer Integrated Account Inquiry System

This work relates to a bank enquiry system, in particular to a bank customer integrated account enquiry system.

As today's economy and technology develop more and more, banks are becoming more closely connected to daily life. Financial institutions provide a wide range of transaction services related to customer accounts, such as online banking, funds, gold passbooks, etc., providing customers with functions such as deposits and withdrawals, as well as subscription and redemption of funds. When customers perform account or non-account (such as changing basic data) actions in the system, financial institutions will store these related information in the service system.

However, in the current system, when financial institution staff want to access the account transaction information of customers' financial products, they need to log in to different transaction service systems one by one to query in order to collect complete data, which is not only labor-intensive but also inefficient. In view of this, how to develop and implement a bank transaction behavior integrated recording system that can integrate and record various transaction information has become a problem to be solved in the current technical field.

Therefore, in order to solve the above problems, it is necessary to propose an integrated system that can provide bank customer inquiries.

To achieve the above purpose, this invention discloses an integrated account query system, including: an online banking server; a smart income and expenditure account network server, which is communicatively connected to the online banking server; a system database, which is communicatively connected to the smart income and expenditure account network server, and stores account data; and a user terminal, which is communicatively connected to the online banking server, and accesses the smart income and expenditure account network server through the online banking server, and is used to query the account data stored in the system database; wherein the account data at least includes the bank transaction details and credit card transaction details of the integrated bank customers, and the bank transaction details and the credit card transaction details are automatically classified into transaction details.

In one embodiment, the account data further includes one or any combination of transaction classification, label, note editing, and historical transaction data.

In one embodiment, the above-mentioned bank customer integrated account inquiry system further includes a core download interface database, an online banking transaction database, a core data aggregation system and a credit card data warehouse for storing various data sources. The core download interface database, the online banking transaction database, the core data aggregation system and the credit card data warehouse storing the above-mentioned various data sources are collected to the pre-release server by a computing device through a data source extraction, transposition and loading server.

In one embodiment, the account data is extracted, transposed and loaded by a data source extraction, transposition and loading server, i.e., an ETL server, and the following steps are performed on the source data: data extraction is used to import bank transaction details and customer account list, credit card transaction details and customer card number list and other related tables from the online banking transaction database, the core data aggregation system and the credit card data warehouse; data transposition includes performing online banking logic data preprocessing, cash flow analysis data preprocessing, data aggregation and denormalization and transaction data classification; data loading is used to write the data into the system database in a nested data structure. Among them, online banking logic data preprocessing is used to pre-write the logic of the online banking program display data, and cash flow analysis data preprocessing is used to pre-write the values required for cash flow analysis operations. Bank transaction details and credit card consumption are two different types of data. Data aggregation and denormalization are used to aggregate the above different types of data into a table as a query index, and to re-process the source data from a normalized state to a non-normalized state.

In one embodiment, the data source extraction, transposition and loading server is a data source extraction, transposition and loading (ETL) computing engine, which can construct data source extraction, transposition and loading (ETL) scripts through graphical processes; the above-mentioned online banking server includes a mobile banking server and a large-scale online server. The bank customer integrated account query system disclosed in this invention further includes a smart income and expenditure account middle platform API server, which is set between the smart income and expenditure account online server and the system database to provide data sharing and communication.

101: Web page level

103: Application level

103a: Transaction details list query module

103b: Single transaction details query module

103c: Transaction details list cash flow calculation module

103d: Transaction details list classification statistics module

105: Data level

105a: Scheduling module

105b: Data source acquisition, transposition and loading module

200: Bank customer integrated account inquiry system

201: Mobile banking network server

202: Bank customers

202a: User terminal

203: Large network server

205: Smart income and expenditure account network server

207: Smart income and expenditure account middle platform API server

211: User Interface

221: Core download interface database

223: Online banking transaction database

225: Core data aggregation system

227: Credit card data storage

229: System database

231:ETL server

233: Pre-release server

S301, S302, S303, S304, S305, S306, S307, S308, S309, S311, S312, S313, S314, S315, S316, S317, S318: Steps

S401, S402, S403, S404, S405: Steps

510: Server/Computer System

512: Bus subsystem

514: Processor

516: Network interface subsystem

520: User output interface device

522: User input interface device

524: Storage subsystem

525:Memory subsystem

526: File storage subsystem

530: Main random access memory (RAM)

532: Read-only storage memory (ROM)

[Figure 1] shows the software architecture of this creation.

[Figure 2] shows the functional block diagram of the system hardware architecture of this creation.

[Figure 3A] shows the process of account transaction classification according to the present invention embodiment.

[Figure 3B] shows the process of credit card transaction classification according to the present invention embodiment.

[Figure 4] shows the process of constructing an integrated account inquiry system for bank customers in this creation.

[Figure 5] shows a block diagram of a server or similar computer system suitable for use with this creation.

Here, this creation will be described in detail for the specific embodiments and viewpoints of the invention. Such description is to explain the structure or step flow of this creation, which is for illustrative purposes rather than to limit the scope of the patent application of this creation. Therefore, in addition to the specific embodiments and preferred embodiments in the specification, this creation can also be widely implemented in other different embodiments. The following is a specific embodiment to illustrate the implementation of this creation. People familiar with this technology can easily understand the effectiveness and advantages of this creation through the content disclosed in this specification. In addition, this creation can also be used and implemented through other specific embodiments. The details described in this specification can also be applied based on different needs, and various modifications or changes can be made without deviating from the spirit of this creation.

The purpose of this work is to disclose a bank customer integrated account inquiry system. This system mainly provides bank customers with integrated inquiries for the past ten years, consolidates account transaction details and credit card transaction details, and especially automatically classifies transaction details. It also supports single or multiple transaction classification, labeling, and note editing to organize and filter historical transaction data. The smart income and expenditure account book provides personalized applications such as cash flow analysis to help customers understand their financial income and expenditure status.

Figure 1 shows the software architecture of this creation, which includes three layers: web layer (also called front-end, presentation layer or user interface) 101, application layer (also called middle layer) 103, and data layer (also called back-end) 105. The web layer provides a graphical user interface (GUI) to display information and collect user information, the application layer processes business logic and user input, and the database layer stores and manages information.

The bank customer integrated account inquiry system constructed by this creation also adopts the above three-tier application architecture. Since each layer is independent, system developers can develop, update and expand one layer without affecting other layers. Different development teams can independently develop, expand and push functions at each layer at the same time, thereby speeding up the development and provision of functions. In addition, the client cannot directly access the database, so this architecture can also achieve data integrity and security. The above three layers and the communication between them, where the first layer is responsible for presenting the interaction between users and the first-layer components. These client-side components allow users to interact with the second-layer processing program in a safe and intuitive way. The second layer of programs is often referred to as the application logic layer. These programs manage the business logic of the application and allow access to the third layer of services. The application logic layer is where most of the processing occurs. Multiple client components can access the second layer of processing programs at the same time, so this application logic layer must manage its own transactions. The third layer of services are protected from direct access by client components located within a secure network. Interaction must occur through the second layer of programs.

Referring to Figure 1, the web page layer (user interface) 101 uses ASP.NET Core to build new, cloud-enabled, and Internet-connected applications. ASP.NET Core is a cross-platform, high-performance open source architecture that can be cloud-enabled and Internet-connected via Internet Information Service (IIS), and provides website administrators with the ability to regenerate URLs to their corresponding web pages, services, and applications through URL Rewrite and redirection tools integrated with IIS. These friendly URLs make it easy for users to remember and for search engines to easily create indexes or keep service URLs consistent.

As shown in Figure 1, the programs in the application layer (or middle layer) 103 manage the business logic of the application and allow access to the third layer services. The above application includes at least a transaction detail list query module 103a, a single transaction detail query module 103b, a transaction detail list cash flow calculation module 103c and a transaction detail list classification statistics module 103d. Among them, the transaction details list query module 103a provides users with the ability to view the transaction details list (view by year-month-day interval/custom date); the single transaction details query module 103b provides users with the ability to view and edit single transaction details; the transaction details list cash flow calculation module 103c provides users with real-time calculation of transaction details; the transaction details list classification statistics module 103d provides users with real-time income and expenditure classification statistics of transaction details.

As shown in FIG1 , the data layer (or backend) 105 includes at least a scheduling module 105a and a data source extraction, transposition and loading (Extract, Transform and Load, ETL) module 105b for data processing. The scheduling module 105a is used as a data pipeline to complete common ETL tasks through workflow orchestration software, such as Airflow as a scheduling tool but not limited to this. Airflow is a workflow scheduling management tool developed in Python that can help developers define scheduling dependencies and make standardized and repetitive processes. For example, Airflow uses DAG (Directed Acyclic Graph), that is, a directed acyclic graph, to define the work process to ensure that tasks can be executed in sequence. In addition, the Web UI can be used to conveniently monitor and trace the status between each process. According to the implementation example of the present invention, the present invention can control the above-mentioned data source extraction, transformation and loading (Extract, Transform and Load, ETL) module 105b, i.e., the ETL module, through Airflow to execute ETL work scheduling and management, but it is not limited to this. Other similar scheduling tools, such as Luigi, Argo, Kubeflow or MLflow, etc., can also be equally applied to the task scheduling of the present invention without deviating from the spirit of the present invention. According to the embodiment of the present invention, the above-mentioned ETL module 105b is Pentaho ETL tool, which is an open source tool that can be used as an ETL computing engine. It can construct ETL scripts with graphical processes through Client UI. It has built-in database integration data import and export, string processing, condition judgment processing, mathematical operation processing and other functions and can support JSON nested data writing.

FIG2 shows a functional block diagram of the system hardware architecture of the present invention. Referring to FIG2, the bank customer integrated account inquiry system 200 provided by the present invention is implemented on a computing device. The bank customer integrated account inquiry system 200 at least includes an application-level network banking server (including a mobile banking network server (WEB The mobile banking network server 201, the large customer network server 203), the smart income and expenditure account network server 205 and the smart income and expenditure account middle platform API server 207, etc., and a database storing various data sources; wherein the bank customer 202, such as User, can access the mobile banking network server 201 and the large customer network server 203 through the customer's user terminal 202a and other devices through the mobile banking/large customer related user interface 211 set on the user terminal, and the mobile banking network server 201 and the large customer network server 203 are connected through the IIS of the Internet Information Service Rewrite queries the account data of the smart income and expenditure account network server 205, including integrating the bank customer's bank transaction details and credit card transaction details, especially automatically classifying the bank transaction details and credit card transaction details, and supporting single or multiple transactions Classification, labeling, and remark editing of account affairs and filtering historical transaction data; wherein the user terminal 202a may include, for example, a portable electronic or computing device, such as a smart phone, a tablet computer, a laptop, etc. The user terminal 202a is connected to the mobile banking network server 201 and the large customer network server 203 through Internet communication. The database storing various data sources at least includes the core download interface database (EAINET database) 221, the online banking transaction database (MMA Data Base) 223, the core data aggregation system (bank Operational Data Store, ODS) 225, the credit card data warehouse (Credit Card Data Warehouse) 227 and the system database (MongoDB) 229. The database storing various data sources can be collected by the ETL server 231, i.e., the data source acquisition, transposition and loading server, to the pre-release server (stage server) 233, so as to facilitate data pre-processing and problem troubleshooting, and avoid affecting the source host when re-operating. Some related tables also need to be saved in the pre-release server 233 in the form of SQL tables for providing ETL operation reading.

In addition, the ETL server 231 will perform data extraction (i.e., collect SQL source data) from the online banking transaction database (MMA Data Base) 223, the core data aggregation system (bank operational data store, ODS) 225, and the credit card data warehouse (credit card data Warehouse)227 imports bank transaction details and customer account list, credit card transaction details and customer card number list and other related tables; then, performs data transposition, wherein the steps of performing data transposition include (i) online banking logic data preprocessing, which is used to pre-write the logic of the online banking program display data in the ETL process, (ii) cash flow analysis data preprocessing, which is used to pre-write the values required for cash flow analysis operations in the ETL process, and (iii) data aggregation/denormalization, which is used to aggregate bank transaction details and credit card consumption into two different data types. Data of the same category are aggregated into the same table and written into the customer unified index as a query index. Denormalization is a process of reprocessing the above source data and converting the data from a normalized state to a non-normalized state. (iv) Transaction data classification is used to define transaction classification logic and rules. The data transposition process refers to the classification rules to classify transactions. Subsequently, data loading (i.e., JSON nested data writing) is executed to write the data into the system database (MongoDB) in a nested data structure229. Therefore, a bank customer 202, such as User, can access the mobile banking network server 201 and the large customer network server 203 through the user terminal 202a and other devices of the customer through the mobile banking/large customer related user interface 211 set on the user terminal, and then obtain the account data stored in the system database (MongoDB) 229 through the smart income and expenditure account network server 205.

According to the embodiment of the present invention, the above-mentioned bank customer integrated account inquiry system 200 further includes a smart income and expenditure account middle platform API server 207, which is set between the smart income and expenditure account network server 205 and the system database (MongoDB) 229 to realize flexible sharing and communication of data. The smart income and expenditure account middle platform API server 207 is a centralized data storage and management platform, which mainly integrates data from various departments, business systems and data sources to provide comprehensive, accurate and unified data services. The smart income and expenditure account middle platform API server 207 can protect the security of data through security measures such as access control, identity authentication and data encryption. Only authorized users and systems can access and use the API interface.

According to the embodiment of the present invention, the above-mentioned system database (MongoDB) 229 is a distributed document database constructed based on sharding technology, supporting horizontal expansion of massive data and multi-availability zone deployment, and providing full physical backup function.

The following paragraphs will discuss how to establish transaction classification rules based on the bank transaction details and credit card transaction data of customers (bank users). First, regarding how to establish transaction classification rules for bank transaction details, the process includes the following steps: (i) extract the transaction summary field for classification and establish the summary classification rule table (memoArray); (ii) use the word-breaking tool to match the remark classification rule table (termArray). This step mainly uses Python word-breaking technology to process the remark field in the bank transaction details, extract recognizable and high-frequency words, and establish the remark classification rule table (termArray) and classification. (iii) establish an anti-term array to eliminate incorrect classification. Since the fuzzy matching between the remark field and the remark classification rule table (termArray) may cause classification errors, for example, if the remark field contains the word "netflix", it will be successfully matched with the ETF, and the transaction will be pushed to the investment category instead of the entertainment category. In order to avoid this situation, this work proposes to generate an anti-term array to eliminate the improper classification results generated by the above fuzzy matching. Next, regarding how to establish transaction classification rules for credit card transaction details, the process includes the following steps: (i) extracting the transaction description field of the credit card transaction details to match the store's mapping table for the first-level transaction classification, where the store's mapping table is established by optimizing a SAS code (Statistical Analysis System code) that produces credit card consumption analysis for retail units; (ii) extracting the MCC code field of the credit card transaction details to perform the second-level transaction classification, where the MCC code is the business industry code (merchants must determine their business types when registering and applying for card machines from various card issuing organizations). For example, major international card issuing organizations such as Visa, Mastercard, JCB, AMEX, etc. directly assign category codes to stores when importing stores into the acquiring service. MCC is mainly used to indicate the types of goods or services provided by merchants, such as restaurants, department stores, movies, or hypermarkets. Through this field, transactions can be initially classified; (iii) the transaction code field (transactionCode) of the credit card transaction details is captured. This field represents different transaction categories, such as request for payment, payment, and fees, which is used for the third-level classification.

According to the present invention, the transaction classification rules established for bank transaction details at least include establishing a summary classification rule table (memoArray) for mapping with the transaction notes (transactionMemo) field; establishing a notes classification rule table (termArray) for mapping with the online banking notes field; establishing an anti-note classification rule table (antiTermArray) for mapping with the description field, mainly to eliminate some misleading keywords.

According to the present invention, the transaction classification rules established for the credit card transaction details at least include establishing a transaction code classification rule table (tcCodeArray) for mapping with the transaction code (transactionCode) field; establishing a business code (MCC code) classification rule table (mccCodeArray) for mapping with the business code (merchantMCC) field; establishing a store classification rule table (storeNameArray) for mapping with the store name field.

Regarding the classification of account transactions, FIG3A shows the process of classifying account transactions. First, the transaction class (transactionClass) of all transactions is preset to a similar term "what is this transaction". Here, this term or term "what is this transaction" is only used as an example and is not used to limit the present invention. Anyone in this field can replace it with any term such as "what is this transaction" without departing from the spirit of the present invention. Then, each transaction is preliminarily classified according to its [TXNMEMO field], that is, the remark field (step S301). When the remark field is "charge card" or "collection of fees and taxes", the [online banking remark] field of the transaction will be classified according to its mapped remark classification rule table (termArray) Classify (step S302) to obtain the transaction classification result (step S303); if the remark field does not meet the above conditions, the remark field of each transaction is classified according to its mapped summary classification rule table (memoArray) (step S304); then, determine whether the transaction classification is the default "What is this transaction" (step S305). If the classification is not "What is this transaction", use this classification as the transaction classification result (S306); if the classification is "What is this transaction", the [Online Banking Remarks] field of the transaction is classified according to its mapped remark classification rule table (termArray) (step S308) to obtain the transaction classification result (step S309).

Regarding the classification of credit card transactions, FIG3B shows the process of credit card transaction classification. First, the transaction class (transactionClass) of all transactions is preset to "What is this transaction?"; the [storeName] field of each transaction, i.e., the store name field, is classified according to the store classification rule table (storeNameArray) mapped thereto (step S311); then, it is determined whether the transaction class is the default "What is this transaction?" (step S312); if the class is not "What is this transaction?", this class is used as the transaction classification result (step S313); if the class is "What is this transaction?", the [mcc [code] field, i.e., the business industry code field, is classified according to the business industry code classification rule table (mccCodeArray) to which it is mapped (step S314); then, it is determined whether the classification is successful (step S315). If the classification is successful, this classification is used as the transaction classification result (S316); if the classification fails (cannot be classified with mccCode or mccCode is 0), the [tc code] field of the transaction, i.e., the transaction code field, is classified according to the transaction code classification rule table (tcCodeArray) to which it is mapped (step S317) to obtain the transaction classification result (step S318).

FIG4 shows the process of constructing the bank customer integrated account query system of this invention, which specifically includes the following steps: First, in step S401, according to the needs of bank users, provide account integration (for example, transaction details list, individual account management), cash flow analysis (for example, analysis chart, periodic expenditure management, credit card installment statistics), budget management and other query services; in step S402, confirm the customer data source stored in the individual database, such as customer files, account lists, account transaction lists and other data stored in the core data aggregation system 225, credit card transaction records (daily/monthly/historical files) stored in the credit card data warehouse 227, credit card product files and other data stored in the pre-release server (stage In step S403, data extraction, transposition and loading (ETL) are performed on the above customer data source, including performing data extraction (i.e., collecting SQL source data) through the above ETL server 231 (refer to FIG. 2) to import bank transaction details and customer account list, credit card transaction details and customer card number list and other related tables; then, data transposition is performed, wherein the step of performing data transposition by the above ETL server 231 (refer to FIG. 2) includes (i) pre-processing the online banking logical data; (ii) cash flow analysis data preprocessing, (iii) data aggregation/denormalization, and (iv) transaction data classification; then, execute data loading (i.e., JSON nested data writing) to write the data into the system database (MongoDB) 229 in a nested data structure; in step S404, design an application programming interface, wherein the above application programming interface enables bank users to query transaction amounts, transaction lists, transaction details, and edit transaction details, and provides bank users with functions such as adding/editing tags and tag search; in step S405, provide users with browsing pages, and the above browsing pages can at least include an income and expenditure account page, a cash flow analysis page, a credit card installment page, a subscription service page, and scattered income.

According to this creative implementation example, the above-mentioned income and expenditure notebook page is used to provide a list of transaction details (year-month-day interval/custom date), transaction details and real-time income and expenditure calculations, classification statistics, viewing and editing of single transaction details, and providing multiple labeling of detail lists, detail search label filtering, and label management.

According to the present invention, the cash flow analysis page is used to provide a revenue and expenditure trend chart (histogram, line chart).

The methods, steps or embodiments proposed in the above invention can be executed in a server or a similar computer system. FIG. 5 shows a block diagram of a server or a similar computer system applicable to the invention. It should be emphasized here that the server/computer system 510 shown in FIG. 5 is only used as an example and should not bring any limitation to the embodiments and scope of use of the invention.

As shown in FIG. 5 , the server/computer system 510 is represented in the form of a general-purpose computing device. The server/computer system 510 typically includes at least one processor 514, which is communicatively connected to multiple peripheral devices via a bus subsystem 512. These peripheral devices may include a storage subsystem (e.g., a memory subsystem 525 and a file storage subsystem 526) 524, a user output interface device 520, a user input interface device 522, and a network interface subsystem 516. The input and output devices allow the user to communicate with the computer system. The network interface subsystem 516 provides a connection interface to an external network and is coupled to corresponding interface devices of other computing devices.

User input devices may include keyboards, pointing devices such as mice, trackballs, touchpads or graphics tablets, scanners, touch screens integrated into displays, voice input devices such as voice recognition systems, microphones, and other types of input devices.

User output devices may include a display subsystem, a printer, a fax machine, or a non-visual display such as an audio output device. The display subsystem may include a cathode ray tube display (CRT), a flat panel device such as a liquid crystal display (LCD), a projection device, or other mechanism for producing a visual image. The display subsystem may also provide a non-visual display with an audio output device.

The storage subsystem 524 stores programming and data constructs that provide the functionality of some or all modules described in the present invention. For example, the program or program module of the storage subsystem can be configured to execute the functionality of various embodiments of the present invention. The above program or program module can be executed by the processor alone or in combination with other processors.

The memory subsystem 525 of the storage subsystem 524 can include a plurality of memories including a main random access memory (RAM) 530 for storing instructions and data during program execution, and a read-only memory (ROM) 532 for storing fixed instructions. The file storage subsystem 526 can provide permanent storage for program and data files, and can include a hard disk drive, an optical disk drive, or removable media cartridges. Functional modules implementing certain embodiments may be stored in storage subsystem 524 via file storage subsystem 526, or stored in other machines that can be retrieved/accessed by one or more processors.

The bus subsystem 512 provides a mechanism by which the various components and subsystems of the computing device/apparatus can communicate with each other in an intended manner. Although the bus subsystem 512 is schematically presented as a single bus, alternative implementations of the bus subsystem 512 may use multiple buses.

A computing device can be of various types, including a workstation, server, computing cluster, or other data processing system or computing device.

The above is a preferred embodiment of this creation. Those skilled in this field should understand that it is used to illustrate this creation, not to limit the scope of the patent rights claimed by this creation. The scope of patent protection shall be determined by the scope of the attached patent application and its equivalent field. Those who are familiar with this field of technology, without departing from the spirit or scope of this patent, make changes or modifications, which are equivalent changes or designs completed under the spirit disclosed by this creation, and should be included in the scope of the patent application described below.

200: Bank customer integrated account inquiry system

201: Mobile banking network server

202: Bank customers

202a: User terminal

203: Large network server

205: Smart income and expenditure account network server

207: Smart income and expenditure account middle platform API server

211: User Interface

221: Core download interface database

223: Online banking transaction database

225: Core data aggregation system

227: Credit card data storage

229: System database

231:ETL server

233: Pre-release server

Claims (11)

A bank customer integrated account inquiry system, comprising: an online banking server; a smart income and expenditure account network server, communicatively connected to the online banking server; a system database, communicatively connected to the smart income and expenditure account network server, storing account data; and a user terminal, communicatively connected to the online banking server, accessing the smart income and expenditure account network server via the online banking server, for inquiring the account data stored in the system database; wherein the account data at least includes integrating the bank customer's bank transaction details and credit card transaction details, and automatically classifying the bank transaction details and the credit card transaction details. The bank customer integrated account inquiry system as described in claim 1, wherein the above-mentioned account data further includes one or any combination of transaction classification, label, note editing, and historical transaction data. The bank customer integrated account inquiry system as described in claim 2 further includes a core download interface database, an online banking transaction database, a core data aggregation system and a credit card data warehouse for storing various data sources. The bank customer integrated account inquiry system as described in claim 3, wherein the core downlink interface database, the online banking transaction database, the core data aggregation system and the credit card data warehouse storing the above-mentioned various data sources are collected to the pre-release server by a computing device through a data source extraction, transposition and loading server. The bank customer integrated account query system as described in claim 4, wherein the account data is extracted, transposed and loaded into the server through the data source, and the computing device performs the following steps on the source data: Data extraction, used to import the bank transaction details and customer account list, the credit card transaction details and customer card number list and other related tables from the online banking transaction database, the core data aggregation system and the credit card data warehouse; Data transposition, including performing online banking logic data preprocessing, cash flow analysis data preprocessing, data aggregation and denormalization and transaction data classification; Data loading, used to write data into the system database in a nested data structure. The bank customer integrated account inquiry system as described in claim 5, wherein the above-mentioned online banking logic data pre-processing is used to pre-write the logic of the online banking program display data. The bank customer integrated account inquiry system as described in claim 5, wherein the cash flow analysis data preprocessing is used to pre-write the required values related to the cash flow analysis operation. The bank customer integrated account inquiry system as described in claim 5, wherein the above-mentioned data aggregation and denormalization are used to aggregate the two different types of data, namely the bank transaction details and the credit card transaction details, into one table as a query index, and to reprocess the source data from a normalized state to a denormalized state. The bank customer integrated account inquiry system as described in claim 5, wherein the above-mentioned transaction data classification is used to define transaction classification logic and rules. The bank customer integrated account query system as described in claim 5, wherein the data source extraction, transformation and loading server is a data source extraction, transformation and loading (ETL) operation engine, which constructs the data source extraction, transformation and loading (ETL) script through a graphical process. The bank customer integrated account inquiry system as described in claim 1 further includes a smart income and expenditure account middle platform API server, which is set between the smart income and expenditure account network server and the system database to provide data sharing and communication.