Bank loan interest income detail generation method and device, equipment and medium

Abstract

The invention provides a bank loan interest income detail generation method and device, equipment and a medium, and relates to the technical field of data processing, and the method comprises the steps: carrying out the extraction of loan and interest related information through obtaining a business file, and obtaining a loan balance extraction information file and an interest recovery extraction information file; and writing a Python script, carrying out business processing on the loan balance extraction information file and the recovery interest extraction information file to obtain a complete loan summarized balance district address file and a summarized recovery interest file, and obtaining a complete delivery file of loan balance income details based on the files. According to the method, the Python script used for processing the banking business file is written, so that the risk of repeated misoperation and delivery delay possibly occurring when banking business personnel process a large amount of data is efficiently solved. Through the method, the bank employees can quickly and accurately generate the monthly loan interest income detail report, the working efficiency is greatly improved, and potential errors are reduced.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a method, device, equipment and medium for generating bank loan interest income details. Background Art

[0002] In the era of automation, the development of multiple programming languages ​​meets the specific needs of different fields, but it also brings some challenges. For example, R language excels in the field of data science, while Java and Go dominate in enterprise-level applications. However, these languages ​​may be too complex when dealing with small applications. Python shows obvious advantages in small application development due to its concise syntax and powerful library support, especially in rapid development and data processing. At present, enterprises often ignore manual operation problems in daily operations during the digital transformation process, such as the cumbersome monthly and annual loan interest income detailed reporting work in banking business, which leads to inefficiency and waste of resources.

[0003] At the same time, due to the convenience of transportation and communication, the number of bank customers continues to increase, which brings challenges to front-line operation managers in making detailed statistics on monthly loan interest income. The repetitiveness of manual operations is prone to errors, and processing large amounts of data may cause delivery delays.

[0004] Based on this, there is an urgent need for a method to generate monthly and annual loan interest income details for banks. Summary of the invention

[0005] The present application provides a method, device, equipment and medium for generating bank loan interest income details to solve the above-mentioned problems existing in the existing magnetic target positioning method.

[0006] In a first aspect, the present application proposes a method for generating bank loan interest income details, the method comprising:

[0007] Obtain business files to extract loan and interest related information, and obtain loan balance extraction information files and interest recovery extraction information files;

[0008] Write a Python script to process the loan balance extraction information file and the interest recovery extraction information file, and obtain a complete loan summary balance area address file and a summary interest recovery file;

[0009] Based on the complete loan balance summary area address file and the summarized interest recovery file, a delivery file of complete loan balance income details is obtained.

[0010] Optionally, obtain the business file to extract loan and interest related information, and obtain the loan balance extraction information file and the recovered interest extraction information file, including:

[0011] Obtain loan balance inquiry documents and principal and interest recovery inquiry documents;

[0012] Based on the loan balance query file, extract customer information, loan balance information and district address information to obtain the loan balance extraction information file;

[0013] Based on the principal and interest recovery query file, customer information and interest recovery information are extracted to obtain the interest recovery extraction information file.

[0014] Optionally, a Python script is written to perform business processing on the loan balance extraction information file and the interest recovery extraction information file to obtain a complete loan summary balance area address file and a summary interest recovery file, including:

[0015] Based on the loan balance extraction information file, the loan balance is summarized and the district address is recorded to obtain a loan balance summary file and a district address record file respectively;

[0016] Based on the loan balance summary file and the district address record file, the complete loan summary balance district address file is obtained, wherein the complete loan summary balance district address file includes customer information, loan balance information and district address information;

[0017] Based on the recovered interest extraction information file, the aggregated recovered interest file is obtained.

[0018] Optionally, the loan balance is summarized based on the loan balance extraction information file to obtain a loan balance summary file, including:

[0019] sorting and classifying the loan balance information in the loan balance extraction information file according to the customer number;

[0020] Aggregate and sum all loan balance information under the same customer number to obtain aggregate loan amount information for the same customer number;

[0021] Irrelevant information is filtered out, and the loan balance summary file is obtained based on each customer number and the summary loan amount information corresponding to the customer number.

[0022] Optionally, performing district address recording based on the loan balance extraction information file to obtain a district address record file includes:

[0023] filtering out the loan balance information in the loan balance extraction information file;

[0024] Classify the area address information according to the customer number, select the area address, and obtain the summary area address information corresponding to the same customer number;

[0025] The district address record file is obtained based on the customer number and the aggregated district address information corresponding to the same customer number, and the district address record file includes customer information and district address information.

[0026] Optionally, obtaining the aggregated interest recovery file based on the interest recovery extraction information file includes:

[0027] Based on the recovered interest extraction information file, classify the recovered interest information according to the customer number, and summarize all the recovered interest information corresponding to the same customer number;

[0028] All recovered interests corresponding to the same customer number are summed up to obtain the aggregated recovered interest file.

[0029] Optionally, the method further includes:

[0030] Input the loan balance query file and the principal and interest recovery query file into the front-end operability interface to obtain the loan balance extraction information file and the interest recovery extraction information file;

[0031] The loan balance withdrawal information file and the interest recovery withdrawal information file are input into the front-end operability interface, combined to obtain a complete delivery file of loan balance income details, and output through the front-end operability interface.

[0032] In a second aspect, the present application proposes a device for generating bank loan interest income details, the device comprising:

[0033] A business file acquisition module is used to acquire business files to extract loan and interest related information, and obtain loan balance extraction information files and interest recovery extraction information files;

[0034] A processing module, used to write a Python script to perform business processing on the loan balance extraction information file and the recovered interest extraction information file to obtain a complete loan summary balance area address file and a summary recovered interest file;

[0035] The delivery file acquisition module is used to obtain a delivery file of complete loan balance income details based on the complete loan summary balance area address file and the summarized interest recovery file.

[0036] In a third aspect of an embodiment of the present application, an electronic device is proposed, comprising a memory, a processor, and a computer program stored on the memory, wherein the processor executes the computer program to implement the method for generating bank loan interest income details as described in any one of the first aspects above.

[0037] In a fourth aspect of an embodiment of the present application, a computer-readable storage medium is proposed, on which a computer program / instruction is stored. When the computer program / instruction is executed by a processor, the method for generating bank loan interest income details as described in any one of the first aspects above is implemented.

[0038] This application includes the following advantages:

[0039] The present application proposes a method, device, equipment and medium for generating bank loan interest income details. First, the loan and interest related information is extracted by acquiring business files to obtain a loan balance extraction information file and a recovered interest extraction information file; then a Python script is written to perform business processing on the loan balance extraction information file and the recovered interest extraction information file to obtain a complete loan summary balance area address file and a summarized recovered interest file; finally, based on the complete loan summary balance area address file and the summarized recovered interest file, a delivery file of the complete loan balance income details is obtained.

[0040] This method effectively solves the risk of repeated operation errors and delivery delays that may occur when banking staff handle large amounts of data by writing Python scripts for banking business file processing. Through this method, bank employees will be able to quickly and accurately generate monthly loan interest income detailed reports, greatly improving work efficiency and reducing potential errors. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the description of the embodiments of the present application will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0042] Figure 1 This is a schematic diagram of the steps of a method for generating bank loan interest income details proposed in an embodiment of the present application;

[0043] Figure 2 It is a flow chart of a method for generating bank loan interest income details proposed in an embodiment of the present application;

[0044] Figure 3 It is a schematic diagram of a method for generating bank loan interest income details combined with a front-end operability interface proposed in an embodiment of the present application;

[0045] Figure 4 This is a module schematic diagram of a device for generating details of bank loan interest income proposed in an embodiment of the present application;

[0046] Figure 5It is a schematic diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0047] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0048] In the era of automation, various high-level programming languages ​​are constantly emerging and developing to meet the needs and challenges of different fields. Each language has its own unique characteristics and applicable fields. For example, R language is mainly used in the fields of data science and statistics. It is generally more widely used in statistical analysis, data visualization, machine learning and data mining. Although R language packages are suitable for processing statistical data, especially for complex scientific statistics, they may seem a bit cumbersome in daily practical and relatively simple application scenarios; Java, Go and other languages ​​are mainly used for enterprise-level application development, covering large systems and server-side applications, etc., and have received widespread attention and application. However, for small applications, these languages ​​may seem too powerful and complex; C++ language is mainly used for game development and high-performance computing, because its lower-level characteristics make it closer to the hardware bottom layer. C# language is mainly used for Windows desktop application development, but relatively speaking, its learning curve is steeper and the development cost is higher. Python language is widely used in small application development. Its concise and easy-to-read syntax makes it take less time to get started, and it has the characteristics of instant compilation, which is easy to develop and understand. In addition, Python provides a wealth of ready-made toolkits for quickly developing lightweight gadgets, greatly simplifying the development process.

[0049] At present, the focus of enterprise digitalization and AI strategies is mainly on digital database storage, enterprise environment construction, and system application upgrades, including the banking industry. In this process, the tedious manual operations required by front-line bank operations managers to report the details of bank micro-loan interest income every month and every year are often overlooked, which consumes a lot of time and energy. At the same time, due to the advantages of Python programming language development, because Python has a concise and efficient syntax structure and rich third-party library support, it can quickly realize automated processing and data analysis through reasonable programming arrangements.

[0050] The application of existing high-level programming languages ​​in the banking sector is mainly concentrated in data storage and background processing, while there are relatively few automated generation tools for basic business. At present, banks still rely on manual operations to summarize the monthly and annual details of small loan interest income, which is time-consuming and labor-intensive.

[0051] At the same time, with the convenience of transportation and communication, the number of bank customers continues to increase, which brings challenges to front-line operation managers in making detailed statistics on monthly loan interest income. The repetitiveness of manual operations is prone to errors, and processing large amounts of data may cause delivery delays.

[0052] Based on this, this application aims to propose a Python-based automatic generator of bank monthly loan interest income details to automate the bank's monthly and annual loan interest income details delivery documents, thereby improving efficiency and reducing the cost of manual errors, providing an efficient and convenient solution for banking business.

[0053] In the first aspect, the present application embodiment proposes a method for generating bank loan interest income details, wherein the method comprises: Figure 1 , Figure 1 This is a schematic diagram of the steps of a method for generating bank loan interest income details proposed in an embodiment of the present application, the method comprising the following steps:

[0054] Step 101: Obtain business files to extract loan and interest related information, and obtain loan balance extraction information files and interest recovery extraction information files.

[0055] In order to generate accurate bank loan income details, first obtain business documents related to loan business, and extract information related to loans and interests from relevant documents, including but not limited to customer information, loan information, and interest information. Obtain loan balance extraction information documents based on the extracted loan-related information, and obtain interest recovery extraction information documents based on the extracted interest recovery related information.

[0056] Step 102: Write a Python script to perform business processing on the loan balance extraction information file and the interest recovery extraction information file to obtain a complete loan summary balance area address file and a summary interest recovery file.

[0057] In order to solve the problem that banks still rely on manual operations to summarize the monthly and annual details of small loan interest income, which is time-consuming and labor-intensive, this application proposes to use the Python language, which has a concise and efficient syntax structure and rich third-party library support, and can quickly realize automated processing and data analysis through reasonable programming arrangements, to write scripts for business processing.

[0058] Specifically, a Python script is written to perform business processing on the above-mentioned loan balance extraction information file and the above-mentioned interest recovery extraction information file. The business processing includes but is not limited to sorting, classification, aggregation, summing, filtering, range selection, merging, etc., so as to obtain a complete loan summary balance area address file and a summary interest recovery file.

[0059] It should be noted that the detailed statistical scenario of bank loan interest income mentioned in this application has built-in operations for the business processing logic of this scenario in the Python script. The built-in operations refer to specific processing of the C and D fields of Table A and Table B (for example, sorting the E field of Table A, filtering the F field of Table B, summarizing the same G field of Table A and Table B, etc.).

[0060] Step 103: Based on the complete loan balance summary area address file and the summarized interest recovery file, a delivery file of complete loan balance income details is obtained.

[0061] By merging the above complete loan balance district address file and the summarized interest recovery file, a complete delivery file of loan balance income details is obtained.

[0062] It should be noted that during the merging process, the key information of the complete loan summary balance area address file and the summarized interest recovery file are merged.

[0063] This application proposes a method for generating bank loan interest income details. First, the loan and interest related information is extracted by obtaining business files to obtain loan balance extraction information files and interest recovery extraction information files; then a Python script is written to perform business processing on the loan balance extraction information files and the interest recovery extraction information files to obtain a complete loan summary balance area address file and a summary interest recovery file; finally, based on the complete loan summary balance area address file and the summary interest recovery file, a complete loan balance income details delivery file is obtained. This method efficiently solves the risks of repeated operation errors and delivery delays that may occur when bank business personnel process large amounts of data by writing Python scripts for bank business file processing. Through this method, bank employees will be able to quickly and accurately generate monthly loan interest income detail reports, greatly improving work efficiency and reducing potential errors.

[0064] In an optional implementation, the above step 101, obtaining the business file to extract loan and interest related information, and obtaining the loan balance extraction information file and the recovered interest extraction information file, specifically includes the following sub-steps:

[0065] Step 1011: Obtain the loan balance inquiry file and the principal and interest recovery inquiry file.

[0066] In order to extract loan balance information and interest recovery information, the first business files obtained include: loan balance query file and principal and interest recovery query file. The loan balance query file contains customer information, loan balance information, loan details, repayment information, interest rate adjustment information, etc. The principal and interest recovery query file contains customer information, interest information, loan interest rate information, loan balance information, loan details, repayment information, interest rate adjustment information, etc.

[0067] Step 1012: extracting customer information, loan balance information and district address information based on the loan balance query file to obtain the loan balance extraction information file.

[0068] In this business scenario, the information that needs to be obtained is loan balance, interest, address, etc., and the above loan balance query file and principal and interest recovery query file contain a lot of irrelevant information. Based on this, it is necessary to extract the required information from each file to filter out other irrelevant information and improve processing efficiency.

[0069] Specifically, for the loan balance query file, the customer information, loan balance information and district address information in the file are extracted to obtain a loan balance extraction information file.

[0070] It should be noted that in the bank loan business scenario, customer information is a unique identity, and subsequent file processing and information merging require customer information. The customer information also includes basic customer information, loan information, credit status, asset disposal information, guarantee information, customer number, etc.

[0071] Step 1013: Based on the principal and interest recovery query file, extract customer information and interest recovery information to obtain the interest recovery extraction information file.

[0072] Specifically, with respect to the principal and interest recovery query file, the customer information and interest recovery information in the file are extracted to obtain an interest recovery extraction information file.

[0073] In an optional implementation, the above step 102, writing a Python script to perform business processing on the loan balance extraction information file and the interest recovery extraction information file to obtain a complete loan summary balance area address file and a summary interest recovery file, specifically includes the following sub-steps:

[0074] Step 1021: performing loan balance summary and district address record based on the loan balance extraction information file, and obtaining a loan balance summary file and a district address record file respectively.

[0075] By performing business processing on the obtained loan balance extraction information file, namely, loan balance summary and district address record, a loan balance summary file and a district address record file are obtained respectively.

[0076] It should be noted that the above loan balance summary file and district address record file are both in .csv file format as the output file format. .csv file (Comma-Separated Values) is a commonly used text file format for storing table data. This file format is simple, easy to read and write, and is widely used for data exchange and backup.

[0077] Step 1022: Based on the loan balance summary file and the district address record file, the complete loan summary balance district address file is obtained, and the complete loan summary balance district address file includes customer information, loan balance information and district address information.

[0078] The business process of merging, summarizing and extracting the loan balance summary file and the district address record file is to obtain a complete loan summary balance district address file. The specific operation is: merge the information in the two files according to the customer number, and the merged file is used as the key information file, that is, the complete loan summary balance district address file, which does not contain irrelevant information, but only contains customer information, loan balance information and district address information.

[0079] Step 1023: Based on the interest recovery information file, the aggregated interest recovery file is obtained.

[0080] A summarized interest recovery file is obtained based on the customer number and interest recovery information contained in the interest recovery extraction information file.

[0081] In an optional implementation, the above step 1021, summarizing the loan balance based on the loan balance extraction information file to obtain a loan balance summary file, specifically includes the following steps:

[0082] Step 10211: Sort and classify the loan balance information in the loan balance extraction information file according to the customer number.

[0083] In this business scenario, the customer number is used as the only information to process all relevant information. The customer number is a special number in the banking business scenario and is obtained from the customer information.

[0084] First, the loan balance information in the loan balance extraction information file is sorted and classified according to the customer number, and the loan balance information under the same customer number is grouped together for subsequent aggregation and merging processing.

[0085] Step 10212: Aggregate and sum all loan balance information under the same customer number to obtain the aggregate loan amount information of the same customer number.

[0086] Based on the above classified loan balance information, all loan balance information under the same customer number is aggregated and summed to obtain the aggregated loan amount information of the same customer number.

[0087] Step 10213: Filter irrelevant information, and obtain the loan balance summary file based on each customer number and the summary loan amount information corresponding to the customer number.

[0088] Filter out information that is irrelevant to the loan month information, where the irrelevant information is the district address information. Based on each customer number and the summary loan amount information corresponding to the customer number, obtain a loan balance summary information table. Save the processed loan balance summary information table into a new .csv file to obtain a loan balance summary file.

[0089] In an optional implementation, the above step 1021, performing district address recording based on the loan balance extraction information file to obtain a district address record file, specifically includes the following steps:

[0090] Step 10214: Filter out the loan balance information in the loan balance extraction information file.

[0091] In the district address record file, only the customer information and district address information need to be recorded, so the loan balance information in the loan balance extraction information file is first filtered out as irrelevant information.

[0092] Step 10215: Classify the area address information according to the customer number, select the area address, and obtain the aggregated area address information corresponding to the same customer number.

[0093] The district address information is classified according to the customer number, the district address information under the same customer number is divided into the same group, and the district address information based on the same group is selected to obtain the aggregated district address information corresponding to the same customer number.

[0094] Specifically, the district address is selected, that is, a large-scale selection is made on all district addresses under the same customer number. If the district address information under the same customer number includes Xisanqi, Haidian District, Beijing, and Suzhou Street, Haidian District, Beijing, then the final summary district address information corresponding to the same customer number is Haidian District, Beijing.

[0095] Specifically, in this example, if the first loan record of the customer is handled at the Bank of China branch in Xisanqi, Haidian District, Beijing, the address record information is Xisanqi, Haidian District, Beijing; if the second loan record is handled at Suzhou Street, Haidian District, Beijing, the address record information is Suzhou Street, Haidian District, Beijing. This business scenario is to aggregate information, and the original two records will be counted as one record, and the address information of the customer record will be updated to Haidian District, Beijing.

[0096] Step 10216: The district address record file is obtained based on the customer number and the aggregated district address information corresponding to the same customer number, and the district address record file includes customer information and district address information.

[0097] The customer number and the summary area address information corresponding to the same customer number are summarized and merged to obtain the area address record file, and the area address record file only contains customer information and area address information.

[0098] In an optional implementation, the above step 1023, based on the recovered interest extraction information file, obtains the aggregated recovered interest file, specifically including the following sub-steps:

[0099] Step 10231: Based on the recovered interest extraction information file, the recovered interest information is classified according to the customer number, and all the recovered interest information corresponding to the same customer number is summarized.

[0100] Based on the customer information and interest recovery information contained in the interest recovery information file, the interest recovery information is classified according to the customer number, and all interest recovery information under the same customer number is summarized. If there is information unrelated to the customer number and interest recovery information, it is filtered; if not, it is not filtered.

[0101] Step 10232: sum up all recovered interests corresponding to the same customer number to obtain the summarized recovered interest file.

[0102] All the recovered interests corresponding to the same customer number are summed up to obtain a summary recovered interest file under each customer number.

[0103] For example, see Figure 2 , Figure 2It is a flow chart of a method for generating bank loan interest income details proposed in an embodiment of the present application. The method is applied to an automated data processing module. First, a business file is obtained, which includes a loan balance query file and a principal and interest recovery query file. Then, the loan balance query file is processed, the loan balance information is summarized according to the customer number to obtain a loan balance summary file, the district address is recorded according to the customer number to obtain a district address record file, and the loan balance summary file and the district address record file are summarized and merged to obtain a complete loan summary balance district address file. Furthermore, the interest recovery information in the principal and interest recovery information extraction file is processed according to the customer number to obtain a summarized interest recovery file. Finally, the complete loan summary balance district address file and the summarized interest recovery file are merged to obtain a complete loan balance income details delivery file.

[0104] The embodiment of the present application also proposes a front-end operability interface, which can improve scalability, so that bank business personnel can not only deal with the classic loan interest income detail summary business scenario, but also can customize and add new functions to deal with other business scenarios by operating the front-end interface. Specifically, the above method also includes the following steps:

[0105] Step 104: Input the loan balance query file and the principal and interest recovery query file into the front-end operability interface to obtain the loan balance extraction information file and the principal and interest recovery extraction information file.

[0106] The loan balance query file and the principal and interest recovery query file are input into the front-end operability interface, and the relevant information, such as customer information, loan information, and interest information, are extracted based on the built-in Python script to obtain the loan balance extraction information file and the interest recovery extraction information file.

[0107] Step 105: Input the loan balance extraction information file and the interest recovery extraction information file into the front-end operability interface, merge them to obtain a complete delivery file of loan balance income details, and output it through the front-end operability interface.

[0108] Based on the obtained loan balance extraction information file and interest recovery extraction information file, they are input into the front-end operability interface, and the loan balance information, district address information and interest recovery information with the same customer number are summarized and merged to obtain a delivery file with complete loan balance income details, which is output through the front-end operability interface.

[0109] The above-mentioned front-end operability interface can adapt to different scenarios. For example, the user has other banking business scenarios other than loan business, involving 5 files (a, b, c, d, e). The user has specific business operations on the above-mentioned files, such as sorting the l field of file a, aggregating the n field of file a and file d, etc. These files can also be imported through the above-mentioned front-end operability interface, and specific fields can be customized to perform other operations of related business scenarios on different fields of different files.

[0110] The above method proposed in this application combines an operable front-end page design to provide banking staff with an intuitive and friendly user interface, and provides customized operation functions to enable them to respond to new business scenarios more quickly and improve scalability. Such a design can not only speed up the delivery process, but also help employees better understand and process data and enhance their ability to deal with risks and challenges.

[0111] For example, see Figure 3 , Figure 3 It is a schematic diagram of a method for generating detailed information of interest income of bank loans combined with a front-end operability interface proposed in an embodiment of the present application. In this front-end operability interface, the following functions can be realized: custom adding business files. Enter the key column name in the interface so that the generator automatically sorts, summarizes, classifies, sums, filters and other operations on a single business file according to the specified key column, and supports custom operations, that is, directly develop Python scripts to access the generator to support more operations, and give 3 lines of real-time operation to display the correctness of the click operation. Enter the key column name in the interface so that the generator automatically merges and summarizes multiple business files according to the specified key column, and also gives the effect display of the operation in real time for user verification. The interface provides export functions and the function of saving intermediate files, which is convenient for users to customize the download of required files. When the user clicks to download, a compressed package will be downloaded, which includes intermediate files, final output files, the underlying Python code implementation of intermediate files, and the entire process Python code implementation of final output files, so that users can learn and refer to the code to realize the realization of custom demand functions.

[0112] Taking the bank's fixed business scenario of micro-loan interest income details as an example, the results of the above method are demonstrated with a specific example.

[0113] First, input the loan balance query file (including the column attributes shown in Table 1). After uploading the single file in the operability interface, click the built-in operation (or custom operation) to process the file in sequence. The underlying layer is based on Python scripts for automated processing. In this example, operations such as sorting, classification, aggregation, summing, filtering, range selection, and merging are performed in sequence.

[0114] Table 1 Example table of column attributes of loan balance query file

[0115]

[0116] Then, input the recovered principal and interest query file (including the column attributes shown in Table 2). Similarly, after uploading the single file on the interface, click the built-in operation (or custom operation) to process the file in sequence. The underlying layer is based on Python scripts for automated processing. In this example, operations such as classification, filtering, aggregation, and summing are performed in sequence.

[0117] Table 2 Example of column attributes of the principal and interest recovery query file

[0118]

[0119] Finally, output the loan balance income detail delivery file (including the column attributes shown in Table 3) through the front-end operability interface. Click on the interface to save the two intermediate files obtained after the above processing (the complete loan summary balance area address file and the summary interest recovery file), then click to select multiple files to upload, enter the key column name after uploading and click the merge operation. The underlying Python script automatically merges the two files according to the specified column name. Finally, click to download the file to get the final delivery file (loan balance income detail delivery file).

[0120] Table 3 Example table of column attributes of loan balance income detail delivery file

[0121]

[0122] It can be seen that in the method proposed in this application, by combining with the front-end operability interface, manual repetitive operations can be avoided, and the delivery file can be obtained with a simple click operation.

[0123] In a second aspect, the present application embodiment provides a bank loan interest income details generating device, see Figure 4 , Figure 4 This is a module schematic diagram of a device for generating bank loan interest income details proposed in an embodiment of the present application, the device comprising:

[0124] The business file acquisition module 401 is used to acquire business files to extract loan and interest related information, and obtain a loan balance extraction information file and a recovered interest extraction information file;

[0125] Processing module 402, used to write a Python script to perform business processing on the loan balance extraction information file and the recovered interest extraction information file to obtain a complete loan summary balance area address file and a summary recovered interest file;

[0126] The delivery file acquisition module 403 is used to obtain a delivery file of complete loan balance income details based on the complete loan summary balance area address file and the summarized interest recovery file.

[0127] Wherein, the business file acquisition module includes:

[0128] The acquisition submodule is used to obtain the loan balance query file and the principal and interest recovery query file;

[0129] A first extraction submodule is used to extract customer information, loan balance information and district address information based on the loan balance query file to obtain the loan balance extraction information file;

[0130] The second extraction submodule is used to extract customer information and interest recovery information based on the principal and interest recovery query file to obtain the interest recovery extraction information file.

[0131] Wherein, the processing module includes:

[0132] A first processing submodule is used to summarize the loan balance and record the district address based on the loan balance extraction information file, and obtain a loan balance summary file and a district address record file respectively;

[0133] A second processing submodule is used to obtain the complete loan summary balance district address file based on the loan balance summary file and the district address record file, wherein the complete loan summary balance district address file includes customer information, loan balance information and district address information;

[0134] The third processing submodule is used to obtain the summarized interest recovery file based on the interest recovery extraction information file.

[0135] Wherein, the first processing submodule includes:

[0136] A first processing unit, configured to sort and classify the loan balance information in the loan balance extraction information file according to the customer number;

[0137] The second processing unit is used to aggregate and sum all loan balance information under the same customer number to obtain aggregate loan amount information of the same customer number;

[0138] The third processing unit is used to filter irrelevant information and obtain the loan balance summary file based on each customer number and the summary loan amount information corresponding to the customer number.

[0139] Wherein, the first processing submodule further includes:

[0140] a fourth processing unit, configured to filter out the loan balance information in the loan balance extraction information file;

[0141] A fifth processing unit is used to classify the area address information according to the customer number, select the area address, and obtain the aggregated area address information corresponding to the same customer number;

[0142] The sixth processing unit is used to obtain the district address record file based on the customer number and the aggregated district address information corresponding to the same customer number, wherein the district address record file includes customer information and district address information.

[0143] Wherein, the third processing submodule includes:

[0144] a seventh processing unit, configured to classify the recovered interest information according to the customer number based on the recovered interest extraction information file, and to summarize all recovered interest information corresponding to the same customer number;

[0145] The eighth processing unit is used to sum up all the recovered interests corresponding to the same customer number to obtain the summarized recovered interest file.

[0146] Wherein, the device further comprises:

[0147] An input module, used to input the loan balance query file and the principal and interest recovery query file into the front-end operability interface to obtain the loan balance extraction information file and the interest recovery extraction information file;

[0148] The output module is used to input the loan balance extraction information file and the interest recovery extraction information file into the front-end operability interface, merge them to obtain a complete delivery file of loan balance income details, and output it through the front-end operability interface.

[0149] Based on the same application concept, the embodiment of the present application discloses an electronic device in a third aspect. Figure 5 A schematic diagram of an electronic device disclosed in an embodiment of the present application is shown. Figure 5 As shown, the electronic device 100 includes: a memory 110 and a processor 120, the memory of the electronic device is not less than 12G, the main frequency of the processor is not less than 2.4GHz, the memory 110 and the processor 120 are connected via a bus communication, and a computer program is stored in the memory 110. The computer program can be run on the processor 120 to implement a bank loan interest income details generation method disclosed in an embodiment of the present application.

[0150] Based on the same application concept, the fourth aspect of the embodiment of the present application discloses a computer-readable storage medium, on which a computer program / instruction is stored. When the computer program / instruction is executed by a processor, a method for generating bank loan interest income details disclosed in the embodiment of the present application is implemented.

[0151] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0152] The embodiments of the present application are described with reference to the flowcharts and / or block diagrams of the methods, apparatuses, electronic devices, and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing terminal device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0153] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing terminal device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0154] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device so that a series of operating steps are executed on the computer or other programmable terminal device to produce a computer-implemented process, thereby providing instructions for executing on the computer or other programmable terminal device to implement the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0155] Although the preferred embodiments of the present application have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the embodiments of the present application.

[0156] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or terminal device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or terminal device. In the absence of further restrictions, the elements defined by the sentence "including one..." do not exclude the existence of other identical elements in the process, method, article or terminal device including the elements.

[0157] The above is a detailed introduction to the method, device, equipment and medium for generating bank loan interest income details provided by the present application. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea; at the same time, for general technical personnel in this field, according to the idea of ​​the present application, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A method for generating bank loan interest income details, characterized in that: The method comprises: Obtain business files to extract loan and interest related information, and obtain loan balance extraction information files and interest recovery extraction information files; Write a Python script to process the loan balance extraction information file and the interest recovery extraction information file, and obtain a complete loan summary balance area address file and a summary interest recovery file; Based on the complete loan balance summary area address file and the summarized interest recovery file, a delivery file of complete loan balance income details is obtained.

2. The method for generating bank loan interest income details according to claim 1, characterized in that: Obtain business files to extract loan and interest related information, and obtain loan balance extraction information files and interest recovery extraction information files, including: Obtain loan balance inquiry documents and principal and interest recovery inquiry documents; Based on the loan balance query file, extract customer information, loan balance information and district address information to obtain the loan balance extraction information file; Based on the principal and interest recovery query file, customer information and interest recovery information are extracted to obtain the interest recovery extraction information file.

3. The method for generating bank loan interest income details according to claim 1, characterized in that: Write a Python script to process the loan balance extraction information file and the interest recovery extraction information file, and obtain a complete loan summary balance area address file and a summary interest recovery file, including: Based on the loan balance extraction information file, the loan balance is summarized and the district address is recorded to obtain a loan balance summary file and a district address record file respectively; Based on the loan balance summary file and the district address record file, the complete loan summary balance district address file is obtained, wherein the complete loan summary balance district address file includes customer information, loan balance information and district address information; Based on the recovered interest extraction information file, the aggregated recovered interest file is obtained.

4. The method for generating bank loan interest income details according to claim 3, characterized in that: The loan balance is summarized based on the loan balance extraction information file to obtain a loan balance summary file, including: sorting and classifying the loan balance information in the loan balance extraction information file according to the customer number; Aggregate and sum all loan balance information under the same customer number to obtain aggregate loan amount information for the same customer number; Irrelevant information is filtered out, and the loan balance summary file is obtained based on each customer number and the summary loan amount information corresponding to the customer number.

5. The method for generating bank loan interest income details according to claim 3, characterized in that: The district address record is performed based on the loan balance extraction information file to obtain a district address record file, including: filtering out the loan balance information in the loan balance extraction information file; Classify the area address information according to the customer number, select the area address, and obtain the summary area address information corresponding to the same customer number; The district address record file is obtained based on the customer number and the aggregated district address information corresponding to the same customer number, and the district address record file includes customer information and district address information.

6. The method for generating bank loan interest income details according to claim 3, characterized in that: Based on the recovered interest extraction information file, the aggregated recovered interest file is obtained, including: Based on the recovered interest extraction information file, classify the recovered interest information according to the customer number, and summarize all the recovered interest information corresponding to the same customer number; All recovered interests corresponding to the same customer number are summed up to obtain the aggregated recovered interest file.

7. The method for generating bank loan interest income details according to claim 1, characterized in that: The method further comprises: Input the loan balance query file and the principal and interest recovery query file into the front-end operability interface to obtain the loan balance extraction information file and the interest recovery extraction information file; The loan balance withdrawal information file and the interest recovery withdrawal information file are input into the front-end operability interface, combined to obtain a complete delivery file of loan balance income details, and output through the front-end operability interface.

8. A device for generating details of bank loan interest income, characterized in that: The device comprises: A business file acquisition module is used to acquire business files to extract loan and interest related information, and obtain loan balance extraction information files and interest recovery extraction information files; A processing module, used to write a Python script to perform business processing on the loan balance extraction information file and the recovered interest extraction information file to obtain a complete loan summary balance area address file and a summary recovered interest file; The delivery file acquisition module is used to obtain a delivery file of complete loan balance income details based on the complete loan summary balance area address file and the summarized interest recovery file.

9. An electronic device comprising a memory, a processor and a computer program stored in the memory, characterized in that: The processor executes the computer program to implement the bank loan interest income details generation method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that: A computer program / instruction is stored thereon, and when the computer program / instruction is executed by a processor, the method for generating bank loan interest income details as described in any one of claims 1-7 is implemented.

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