Business travel reimbursement data verification method and system based on application form association

Abstract

The invention provides a business travel reimbursement data verification method and system based on application form association, and relates to the technical field of reimbursement, and the method comprises the steps: obtaining a traveler list and itinerary planning information corresponding to a business trip application form in response to the operation that a user associates the approved business trip application form in a reimbursement form filling interface, generating a selectable range of the business trip personnel and an allowable reimbursement place set; the method comprises the following steps: sending a front-end control instruction to a client to limit input options of personnel and place fields when cost details are input; and receiving the reimbursement bill data and verifying the expense details, if the verification is not passed, generating a rejection signal containing a specific error item identifier and a violation description, returning the reimbursement bill to the submission node, and meanwhile, returning prompt information to the client to guide a user to correct the reimbursement bill. The technical problem of how to improve the efficiency, accuracy and compliance of reimbursement data verification is solved, and the technical effects of improving the compliance of expense management and accelerating the reimbursement process are achieved.

Description

Technical Field

[0001] This invention relates to the technical field of expense reimbursement, and more specifically, to a method and system for verifying travel expense reimbursement data based on application form association. Background Technology

[0002] In the process of managing corporate travel expenses, employees are required to process expense reimbursements after completing business trips. The current reimbursement process has the following problems: some companies have not yet established a standardized system for filling out business trip application forms, or there is a lack of an effective linkage mechanism between the reimbursement form and the business trip application form. This management deficiency prevents the system from automatically verifying the travel permissions and destination cities of the applicants, easily leading to discrepancies between the applicants and the approved locations. Such management loopholes not only increase the workload of manual review by the finance department but also significantly enhance the compliance risks of corporate expense management. Summary of the Invention

[0003] The purpose of this invention is to provide a method and system for verifying travel expense reimbursement data based on application form association, so as to solve the technical problem of how to improve the efficiency, accuracy and compliance of reimbursement data verification.

[0004] In a first aspect, embodiments of the present invention provide a method for verifying travel expense reimbursement data based on application form association, executed by a server, the server being communicatively connected to a client providing an expense reimbursement form filling interface; the method includes: responding to a user's operation of associating an approved business trip application form in the expense reimbursement form filling interface, obtaining a list of travelers and itinerary planning information corresponding to the business trip application form, generating a selectable range of personnel for this business trip based on the traveler list, and extracting location information based on the itinerary planning information and generating a set of allowed reimbursement locations; sending a front-end control command to the client to enable the client to automatically process expense details during the expense entry process. The input options for the "Personnel Status Restriction" field are limited to members within the selectable range of personnel for this business trip, and the input options for the "Location" field are limited to locations within the set of allowed reimbursement locations. The system receives reimbursement data submitted by the client, iterates through each expense detail record, and verifies whether the corresponding personnel in the expense detail belong to the selectable range of personnel for this business trip and whether the location belongs to the set of allowed reimbursement locations. If any expense detail fails verification, a rejection signal containing a specific error identifier and a violation explanation is generated, and the reimbursement form is returned to the submission node. Simultaneously, a prompt message is returned to the client to guide the user in making corrections.

[0005] In some optional implementations, the above-mentioned extraction of location information based on itinerary planning information and generation of a set of locations eligible for reimbursement includes: obtaining the itinerary plan consisting of multiple city nodes in the above-mentioned business trip application form; performing deduplication on the city nodes in the above-mentioned itinerary plan to generate a set of unique city names; and determining the above-mentioned set of unique city names as the set of locations eligible for reimbursement.

[0006] In some optional implementations, in response to the user's operation of associating an approved business trip application form in the aforementioned expense report form filling interface, the method further includes: extracting the start and end dates of the business trip from the aforementioned business trip application form, constructing a valid time interval as the business trip time range; verifying whether the occurrence time of each expense detail in the aforementioned expense report form falls within the aforementioned business trip time range; and sending a time constraint instruction to the aforementioned client so that the aforementioned client restricts or prompts the input of the time field during the expense detail entry process, allowing input only within the aforementioned business trip time range or a preset error tolerance period.

[0007] In some optional implementations, after generating the rejection signal, the method further includes: based on the job level of the user who submitted the expense report, invoking a pre-configured set of exception handling rules to perform differentiated processing on the results that failed the verification; the set of exception handling rules includes fault tolerance modes corresponding to different job levels.

[0008] In some optional implementations, the above method also includes an adaptive rule optimization process: collecting historical verification failure records as abnormal event data; performing cluster analysis on the abnormal event data containing historical verification failure records based on a machine learning model to identify high-frequency abnormal types and root causes; and dynamically adjusting the above abnormal handling rule set or updating the generation strategy of the above-mentioned selection range of personnel and allowed reimbursement location set based on the identification results.

[0009] In some optional implementations, when returning the prompt information to the aforementioned client, the method further includes: generating intelligent replacement recommendation options for each expense detail that fails verification; the intelligent replacement recommendation options are generated based on the user's personal historical correction behavior data, correction preference data of groups with the same job position as the user, and / or contextual information of the current expense report; and providing a one-click adoption interface for the user to select and automatically complete the field correction.

[0010] Secondly, embodiments of the present invention provide a method for verifying travel expense reimbursement data based on application form association, executed by a client providing an expense reimbursement form filling interface. The method includes: receiving configuration data from a server, the configuration data being generated based on an approved travel application form associated with the user, including a selectable range of personnel for the current business trip and a set of allowed reimbursement locations; during the expense detail entry process, dynamically rendering input controls to restrict the input options for the personnel field to only display members within the selectable range of personnel for the current business trip, and restricting the input options for the location field to only display locations within the set of allowed reimbursement locations; responding to a user's search operation in the expense reimbursement form filling interface, performing prefix matching filtering locally based on the set of allowed reimbursement locations, and returning the matching result; responding to the submission operation of the expense reimbursement form, sending expense reimbursement form data containing multiple expense details to the server, so that the server performs compliance verification on the personnel and locations in each expense detail according to the configuration data; if a rejection signal is received from the server, displaying a prompt interface containing specific error information and providing a one-click correction recommendation option for the error item to guide the user to adjust the input content.

[0011] Thirdly, embodiments of the present invention provide a travel expense reimbursement data verification system based on application form association, run by a server, which communicates with a client providing an expense reimbursement form filling interface; the system includes: a data association and range extraction module, used to respond to a user's operation of associating an approved business trip application form in the expense reimbursement form filling interface, obtain the traveler list and itinerary planning information corresponding to the business trip application form, generate a selectable range of personnel for this business trip based on the traveler list, and extract location information based on the itinerary planning information and generate a set of allowed reimbursement locations; and a front-end range control module, used to send front-end control instructions to the client to enable the client to perform expense detail entry process. The input options for the "Dynamically Restricted Personnel" field are limited to members within the selectable range of personnel for this business trip, and the input options for the "Location" field are limited to locations within the set of allowed reimbursement locations. The compliance verification module receives reimbursement data submitted by the client, iterates through each expense detail record, and verifies whether the personnel corresponding to the expense detail belong to the selectable range of personnel for this business trip and whether the location belongs to the set of allowed reimbursement locations. The rejection signal generation module generates a rejection signal containing a specific error identifier and a violation explanation if any expense detail fails verification. It then returns the reimbursement form to the submission node and sends a prompt message to the client to guide the user in making corrections.

[0012] Fourthly, embodiments of the present invention provide an electronic device, including a memory and a processor, wherein the memory stores a computer program that can run on the processor, and the processor executes the computer program to implement the steps of the method described in any of the first aspects above.

[0013] Fifthly, embodiments of the present invention provide a computer-readable storage medium storing computer-executable instructions, which, when invoked and executed by a processor, cause the processor to perform the method described in any of the first aspects above.

[0014] This invention provides a method and system for verifying travel expense reimbursement data based on application form association. The method includes: responding to a user's operation of associating an approved travel application form in the expense reimbursement form filling interface; obtaining the traveler list and itinerary planning information corresponding to the travel application form; and generating a selectable range of personnel and a set of allowed reimbursement locations for this business trip; restricting the input options for personnel and location fields when entering expense details by sending front-end control instructions to the client; receiving expense reimbursement form data and verifying the expense details; if the verification fails, generating a rejection signal containing specific error identifiers and violation explanations, returning the expense reimbursement form to the submission node, and simultaneously returning a prompt message to the client to guide the user in correction. This invention solves the technical problem of how to improve the efficiency, accuracy, and compliance of expense reimbursement data verification, achieving the technical effects of improving expense management compliance and accelerating the reimbursement process. Attached Figure Description

[0015] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments of the present invention will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 A flowchart illustrating a method for verifying travel expense reimbursement data based on application form association, provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of the structure of a travel expense reimbursement data verification system based on application form association, provided in an embodiment of the present invention. Figure 3 A flowchart illustrating another method for verifying travel expense reimbursement data based on application form association provided in an embodiment of the present invention; Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] In the process of managing corporate travel expenses, employees need to process expense reimbursement after completing business trips. The current reimbursement process has the following problems: some companies have not yet established a standardized system for filling out business trip application forms, or there is a lack of an effective linkage mechanism between the reimbursement form and the business trip application form. This management deficiency makes it impossible for the system to automatically verify the travel permissions and destination city range of the person requesting reimbursement, easily leading to situations where the person requesting reimbursement does not match the approved location or the travel destination exceeds the approved scope. Such management loopholes not only increase the workload of manual review by the finance department but also significantly increase the compliance risk of corporate expense management. Based on this, this invention provides a method and system for verifying travel reimbursement data based on application form linkage, to solve the technical problem of how to improve the efficiency, accuracy, and compliance of reimbursement data verification.

[0019] To facilitate understanding of this embodiment, a detailed description of a travel expense reimbursement data verification method based on application form association, as disclosed in this embodiment of the invention, will be provided first. (See [link to relevant documentation]). Figure 1 The diagram illustrates a method for verifying travel expense reimbursement data based on application form association. This method can be executed by a server that communicates with a client providing an expense reimbursement form filling interface. The method mainly includes the following steps S102 to S108: Step S102: In response to the user's operation of associating the approved business trip application form in the expense report form filling interface, obtain the traveler list and itinerary planning information corresponding to the business trip application form, generate the selectable range of personnel for this business trip based on the traveler list, and extract location information based on the itinerary planning information to generate a set of allowed reimbursement locations.

[0020] In this embodiment, the expense reimbursement form filling interface can be provided by the client. Specifically, it can be presented by a travel management system or enterprise expense management application on the client (such as a web page, mobile app, desktop client, etc.), and support users to enter and submit form data. Furthermore, the same platform or integrated module on the client can also provide a business trip application form filling interface, enabling users to complete the entire process from application to reimbursement within a unified system, realizing a closed-loop business process.

[0021] The list of travelers corresponding to a business trip application can be obtained by reading the set of employee names or employee IDs recorded in the "Travelers" field of the approved business trip application; the itinerary planning information can be obtained by parsing the city nodes and their order information contained in the "Itinerary Arrangement" component of the application, such as a list of multiple city names represented by a chain structure of "departure point → transit points → destination".

[0022] In step S102 above, the user's operation of associating an approved business trip application with the expense report form in the expense report form filling interface can refer to the user clicking the "Associate Application Form" button, selecting a record from the list of previously submitted business trip applications in the "Approved" state in the pop-up selection window, and binding its unique identifier (such as the application form ID) to the current expense report form. After the user associates the expense report form being filled out with the approved business trip application form, the backend service can be triggered to perform a data query process on the application form, automatically extracting the traveler list, itinerary planning information, and business trip time period, and generating the selectable range of personnel for this expense report, the set of allowed expense report locations, and the valid time interval based on this information, providing a data foundation for subsequent front-end control and compliance verification.

[0023] This step enables the automatic parsing and construction of a compliance boundary constraint set for reimbursement behavior, using approved business trip application forms as a trusted data source. Its core lies in establishing a three-dimensional control baseline comprised of personnel, city, and time.

[0024] In one embodiment, in response to a user's operation of associating an approved business trip application form in the expense report form filling interface, the method further includes: extracting the start date and end date of the business trip from the business trip application form, constructing a valid time interval [start_date, end_date] as the business trip time range; verifying whether the occurrence time of each expense detail in the expense report form is within the business trip time range; and sending a time constraint instruction to the client so that the client restricts or prompts the input of the time field during the expense detail entry process, allowing input only within the business trip time range or a preset error tolerance period.

[0025] The expense report details the specific entries for all reimbursable expenses incurred by the user during this business trip. Each expense entry must include key fields such as expense type (e.g., transportation, accommodation, meal allowance), date of occurrence, amount, location of expenditure, and personnel involved. The date of occurrence typically refers to the actual date the expense was incurred (e.g., flight ticket date, hotel check-in date, invoice date), and is an important basis for determining whether it falls within the current business trip period.

[0026] In the above embodiments, compliance control over the time period of each expense detail can be achieved by comparing it with the valid time interval extracted from the business trip application. For example, if the business trip is from January 10th to January 15th, 2025, expenses incurred outside this period will generally not be reimbursed. To further improve user experience and business adaptability, a "preset tolerance period" can be set, such as extending it by one day before or after, or dynamically adjusting it in conjunction with the mode of transportation (e.g., flight delay support + 3-hour buffer), to accommodate time deviations caused by fluctuations in the actual itinerary.

[0027] After receiving the time constraint instruction, the front end can implement the following control strategy in the time input control of the cost details: Hard restriction mode: Time outside the range cannot be selected (e.g., calendar controls are grayed out and are not valid dates); Soft prompt mode: Allows users to input but pops up a warning dialog box, prompting "The time when the expense occurred is not within the business trip period, please confirm whether it is reasonable".

[0028] This mechanism provides dual protection through both proactive prevention and post-event verification in the time dimension. It reduces invalid entries and enhances the automation level of expense authenticity verification, further improving the compliance and efficiency of the travel reimbursement process.

[0029] In one embodiment, extracting location information based on itinerary planning information and generating a set of locations eligible for reimbursement includes: obtaining an itinerary plan consisting of multiple city nodes from a business trip application form; deduplicating the city nodes in the itinerary plan to generate a set of unique city names; and determining the set of unique city names as the set of locations eligible for reimbursement.

[0030] The above steps are the starting point for data initialization of the entire verification mechanism. Once the associated application form is completed, data reading of the target application form is triggered. Key information extracted can include a list of travelers, constructing a "selectable range of personnel for this business trip," which serves as a whitelist for the "personnel" field in all subsequent expense details. Key information extracted can also include itinerary planning (e.g., Beijing → Shanghai → Guangzhou), which, after deduplication, forms a "set of allowed reimbursement locations," used to limit the range of cities eligible for reimbursement. Simultaneously, the start and end dates of the business trip can be extracted, constructing an effective time interval [start_date, end_date], and a preset tolerance period (e.g., ±1 day before or after) can be introduced to enhance practical applicability.

[0031] For example, an application form contains travelers [A, B, C], an itinerary [Beijing → Shanghai → Beijing → Guangzhou], and dates from January 10th to 15th, 2025. For this application form, the following can be automatically extracted: the range of travelers {A, B, C}, the range of cities {Beijing, Shanghai, Guangzhou}, and the time range [2025-01-10, 2025-01-15] (extended to [2025-01-09, 2025-01-16] if error tolerance is included). These three elements together form the basis for subsequent control and verification.

[0032] The above process embodies the design of transforming static approval results into dynamic control parameters, converting text data that was originally only used for approval record keeping into a structured rule set that can be used for programmatic verification.

[0033] Step S104: Send a front-end control instruction to the client so that the client can dynamically restrict the input options of the personnel field to only include members within the selectable range of personnel on this business trip, and the input options of the location field to only include locations in the set of allowed reimbursement locations during the expense details entry process.

[0034] The front-end control instructions can be a set of structured configuration data or lightweight control commands generated by the server, such as a JSON-formatted message body. The content includes, but is not limited to: the selectable range of personnel for this business trip (e.g., a list of employee IDs or names), the set of allowed reimbursement locations (e.g., an array of city names), the valid time interval (start_date and end_date), and optional constraint mode identifiers (e.g., "strict restriction" or "warning"). These instructions are pushed to the client via an API interface and take effect immediately after the reimbursement form initialization or associated application form operation is completed. They are used to guide the front-end interface components in data rendering and interaction logic control.

[0035] Upon receiving control instructions, the input options for the "Personnel" field are dynamically bound by the client to the "Selectable Personnel for This Business Trip." Specifically, when a user clicks the "Select Personnel" dropdown or selector, only the list of approved travelers for this business trip is displayed; other unrelated personnel are not shown in the candidate list and cannot be added manually. This mechanism eliminates the possibility of unauthorized personnel participating in expense reimbursement from the outset, ensuring the authenticity and compliance of expense attribution.

[0036] The input options for the location field can be filtered and constrained in real time based on the set of allowed reimbursement locations. After the client loads this city set locally, it can perform the following interactive behaviors: When a user selects a city from the dropdown menu, the candidate city list only includes cities appearing in the approved itinerary (such as Beijing, Shanghai, and Guangzhou). When a user enters keywords (such as "Guangzhou") using the search function, the system performs a prefix matching algorithm within the allowed set and returns results that meet the criteria (such as "Guangzhou"), without displaying other irrelevant cities (such as "Hangzhou" or "Nanning"). If no matching results are found, an empty status message is displayed, such as "No relevant city found. Please confirm whether it is within the scope of your business trip itinerary," thus guiding the user to enter the correct information.

[0037] Furthermore, the front-end control can employ a dynamic rendering mechanism, which updates the data source and availability status of the input controls in real time based on different reimbursement business scenarios and associated application form content, avoiding the lack of flexibility caused by static configuration. Simultaneously, all constraint rules are executed locally on the front end, eliminating the need for frequent backend requests and improving response speed and user experience.

[0038] In summary, step S104, by issuing precise front-end control commands from the server, achieves intelligent and context-aware input constraints on key fields, constructs a proactive data entry environment that "prevents errors before they occur," significantly reduces non-compliant submissions caused by human negligence or misoperation, and lays the foundation for efficient verification and rapid workflow in the future.

[0039] Step S106: Receive the expense report data submitted by the client, traverse each expense detail record, and verify whether the corresponding personnel in the expense detail are within the selectable range of personnel for this business trip, and whether the location is within the set of allowed reimbursement locations.

[0040] In this embodiment, although input restrictions have been implemented on the personnel and location fields at the front end, a final compliance check still needs to be performed independently on the server side to ensure the overall security and compliance loop of the system. This step, as a key verification node in the reimbursement process, bears the responsibility of "fallback verification" to prevent non-compliant data from entering the approval process due to potential risks such as interface bypass, data tampering, multi-terminal collaboration anomalies, or front-end logic failure.

[0041] Specifically, after receiving the expense report data submitted by the client, the server first queries and loads the corresponding original approval data based on the business trip application ID associated with the expense report. This data includes: a list of travelers (used to construct the selectable range of personnel for this business trip); a set of allowed reimbursement locations generated after deduplication of the itinerary planning information; and the business trip time range (including the time interval of the preset error tolerance period [start_date, end_date]). Subsequently, the system initiates a two-dimensional cross-validation algorithm to check each expense detail in the reimbursement form: (1) Personnel dimension verification: Determine whether the "personnel involved" filled in the expense detail exists in the list of travelers extracted from the application form. If the person claiming a certain accommodation or transportation expense is not on the approved list, it is considered an unauthorized reimbursement and triggers a violation mark; (2) Location dimension verification: Determine whether the place where the expense occurred belongs to the "set of allowed reimbursement locations". For example, if the itinerary only includes Beijing, Shanghai, and Guangzhou, but the location of a certain catering invoice is "Shenzhen", it is determined that it exceeds the authorized city range; (3) Time dimension verification: Further verify whether the time of expense occurrence falls within the valid business trip period or the tolerance period, so as to achieve comprehensive compliance control in three dimensions.

[0042] During the verification process, the system maintains a set of error records to collect all detailed entries that failed verification and their specific reasons (e.g., "Line 3: Personnel 'Zhang San' is not a member of this business trip," "Line 5: City 'Chengdu' is not within the itinerary range"). Only when all expense details pass verification is the reimbursement data considered compliant overall and can proceed to the subsequent approval stage; otherwise, it proceeds to step S108 for rejection processing.

[0043] This backend verification mechanism adopts a design principle of decoupling from the frontend. It does not rely on client-side constraints but recalculates and compares based on the original approval data, ensuring the independence, authority, and tamper-proof capability of the verification process. Simultaneously, through structured traversal and batch judgment, it improves verification efficiency and is suitable for complex reimbursement scenarios with high concurrency and numerous details.

[0044] In summary, step S106 achieves a precise mapping from business rules to technical execution, which is a core technical step in ensuring the authenticity, legality, and controllability of travel expense reimbursement data.

[0045] In step S108, if any expense detail fails the verification, a rejection signal containing the specific error item identifier and violation explanation is generated, and the expense report is returned to the submission node. At the same time, a prompt message is returned to the client to guide the user to make corrections.

[0046] In this embodiment, this step not only intercepts and provides feedback on non-compliant data, but also further constructs an explainable, operable, and optimizable intelligent correction guidance mechanism. Through refined problem localization, semantic explanations of violations, and intelligent correction suggestions, it helps users quickly understand the problem and complete accurate modifications, thereby significantly reducing duplicate submissions and improving overall process efficiency and user experience.

[0047] Furthermore, this step can also integrate multiple processing mechanisms such as differentiated processing strategies (based on job level), adaptive rule learning (based on cluster analysis of historical failure data), and intelligent replacement recommendation (combined with individual / group behavioral preferences).

[0048] In one embodiment, after generating a rejection signal, the above method may further include: according to the job level of the user who submitted the expense report, calling a pre-configured set of exception handling rules to perform differentiated processing on the results that failed the verification; the set of exception handling rules includes fault tolerance modes corresponding to different job levels, such as: junior employees trigger direct rejection, intermediate employees allow supervisors to review, and senior employees support special approval filing.

[0049] Preferably, the exception handling rule set can be built based on the role-based access control (RBAC) model in the enterprise's organizational structure and synchronized in real time with the job level data in the human resources system to ensure the accuracy and timeliness of the rule application. After a verification failure is detected, the job level attribute of the submitting user (such as "P5-Intermediate Engineer", "M2-Department Manager" or "VP-Senior Manager") can be automatically identified, and the exception handling strategy matching it can be dynamically loaded to achieve differentiated compliance management for different job levels.

[0050] In one embodiment, the above method may further include an adaptive rule optimization process: collecting historical verification failure records as abnormal event data; performing cluster analysis on the abnormal event data containing historical verification failure records based on a machine learning model to identify high-frequency abnormal types and root causes; and dynamically adjusting the abnormal handling rule set or updating the generation strategy of the selectable range of personnel and the set of allowed reimbursement locations for this business trip based on the identification results.

[0051] Specifically, an exception event database can be built by periodically collecting verification failure logs through background tasks. Each record can include, but is not limited to, the following dimensions: error type (such as personnel going out of bounds, city mismatch), frequency of occurrence, user job level and department involved, degree of time deviation, whether it has been corrected and passed, final handling method, etc.

[0052] Subsequently, unsupervised learning algorithms (such as K-means or DBSCAN) can be used to perform cluster analysis on these abnormal samples to uncover common abnormal patterns. For example, a sales team frequently encounters the error "the city visited by the customer is not in the original itinerary"; most users mistakenly enter "Suzhou" instead of "Hangzhou", indicating a tendency to confuse input; and senior executives often have unapproved business trips before and after holidays.

[0053] Furthermore, based on the identified high-frequency anomaly types and their underlying causes (such as process delays, high naming similarity, and special business scenarios), automatic rule optimization suggestions are triggered, which may include: For situations where "sales field staff frequently change destinations", the location constraint mechanism for this position can be dynamically relaxed, and a "whitelist expansion application" function can be introduced or a larger fault-tolerant city circle can be enabled by default. To address the issue of "easily confused city names," we have optimized the front-end search matching algorithm, enhanced the pinyin / semantic error correction capabilities, and prioritized displaying frequently used historical options in the recommendation list. If a certain type of anomaly is found to be concentrated in a specific job level for a long period of time, the corresponding anomaly handling rule set will be adjusted. For example, an entry point for "one-click to supplement travel nodes" will be added for intermediate employees to improve flexibility.

[0054] The above optimization process supports closed-loop feedback: after the new strategy is launched, its implementation effect is continuously monitored (such as the decrease in the anomaly rate and the correction of the upward trend in the adoption rate), and the improvement effect is evaluated in combination with A / B testing, so as to realize the transformation of the rule system from "static configuration" to "continuous evolution".

[0055] In one embodiment, when returning a prompt message to the client, the above method may further include: generating intelligent replacement recommendation options for each expense detail that fails verification; the intelligent replacement recommendation options are generated based on the user's personal historical correction behavior data, correction preference data of groups with the same job position as the user, and / or contextual information of the current expense report; and providing a one-click adoption interface for the user to select and automatically complete the field correction.

[0056] Specifically, when a certain expense detail is determined to be in violation (e.g., the person "Zhang San" is not the traveler, or the city "Shenzhen" is not included in the itinerary), the process no longer stops at the error reporting level, but rather generates a precise recommendation solution by comprehensively considering information from multiple sources. For example: (1) Based on personal historical correction behavior data: Analyze the user's modification path in similar errors in the past. For example, if the user changes "Shenzhen" to "Guangzhou" in 80% of cases, the system will recommend this option first; (2) Based on group-based preference correction data: Refer to the high-frequency correction choices of other employees with the same job title (such as "Regional Sales Manager") or department in similar scenarios. If 60% of employees with the same job title tend to choose "Shanghai", then include them in the recommended candidates; (3) Based on contextual information: Combine the overall content of the current expense report to make contextual inferences. For example: "Guangzhou" appears most frequently in the itinerary planning; other expense details all occur in "Guangzhou"; the companions are all employees in the "Guangzhou" office area; then the confidence of "recommending to replace it with 'Guangzhou'" is further strengthened.

[0057] Finally, the system sorts the results by overall score and outputs 1-3 of the most likely correct options, providing a "Smart Replace" button for each incorrect option on the client interface. Users can click to adopt the recommended value with one click, and the system automatically fills in the blanks and skips the manual search step. Furthermore, it supports batch intelligent correction. When multiple errors have a unified correction logic (e.g., all cities should be "Guangzhou"), a global "All Apps Recommendation" operation is provided, greatly improving correction efficiency.

[0058] The above mechanism significantly reduces the cognitive burden and operational costs for users, transforming compliance rectification from passive error correction to efficient collaboration, which can effectively improve the first-time approval rate of reimbursement and user experience satisfaction.

[0059] In another embodiment, if all the expense details pass the verification, a "compliance confirmation signal" is generated, and the reimbursement form is pushed to the preset approval process starting point to enter the subsequent multi-level review process.

[0060] This invention provides a method for verifying travel expense reimbursement data based on application form association. The method includes: responding to a user's operation of associating an approved travel application form in the expense reimbursement form filling interface; obtaining the traveler list and itinerary planning information corresponding to the travel application form; generating a selectable range of personnel and a set of allowed reimbursement locations for this business trip; sending front-end control instructions to the client to restrict the input options for personnel and location fields when entering expense details; receiving expense reimbursement form data and verifying the expense details; if the verification fails, generating a rejection signal containing specific error identifiers and violation explanations, returning the expense reimbursement form to the submission node, and simultaneously returning a prompt message to the client to guide the user in correction. This invention solves the technical problem of how to improve the efficiency, accuracy, and compliance of expense reimbursement data verification, achieving the technical effects of improving expense management compliance and accelerating the reimbursement process.

[0061] Based on the same inventive concept, this embodiment of the invention also provides a travel expense reimbursement data verification system based on application form association. This system can be run by a server, which communicates with a client providing the reimbursement form filling interface; see also Figure 2 As shown, the system mainly includes the following structure: The data association and scope extraction module 210 is used to respond to the user's operation of associating the approved business trip application form in the expense report form filling interface, obtain the traveler list and itinerary planning information corresponding to the business trip application form, generate the selectable range of personnel for this business trip based on the traveler list, and extract location information based on the itinerary planning information and generate a set of allowed reimbursement locations. The front-end scope control module 220 is used to send front-end control instructions to the client so that the client can dynamically restrict the input options of the personnel field to only include members within the selectable range of personnel on this business trip, and the input options of the location field to only include locations in the set of allowed reimbursement locations during the expense details entry process. The compliance verification module 230 is used to receive expense report data submitted by the client, traverse each expense detail record, and verify whether the personnel corresponding to the expense details are within the selectable range of personnel for this business trip and whether the location is within the set of allowed reimbursement locations. The rejection signal generation module 240 is used to generate a rejection signal containing specific error identifiers and violation descriptions if any expense detail fails the verification, and return the expense report to the submission node, while also returning prompt information to the client to guide the user to make corrections.

[0062] The system provided in this embodiment of the invention has the same implementation principle and technical effects as the aforementioned method embodiment. For the sake of brevity, any parts not mentioned in the system embodiment can be referred to the corresponding content in the aforementioned method embodiment. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can all be referred to the corresponding processes in the aforementioned method embodiments, and will not be repeated here.

[0063] Based on the same inventive concept, this invention also provides another method for verifying travel expense reimbursement data based on application form association. This method can be executed by a client that provides an expense reimbursement form filling interface. See [link to relevant documentation]. Figure 3 As shown, the method mainly includes the following steps S302 to S310: S302, Receive configuration data from the server. The configuration data is generated based on the user's associated approved business trip application form, including the selectable range of personnel for this business trip and the set of allowed reimbursement locations; S304, During the expense details entry process, dynamically render the input controls to restrict the input options of the personnel field to only members within the selectable range of personnel for this business trip, and restrict the input options of the location field to only locations within the set of allowed reimbursement locations; S306, in response to the user's search operation in the expense report form filling interface, performs prefix matching filtering locally based on the set of allowed expense report locations and returns the matching results; S308, in response to the submission of the expense report, sends expense report data containing multiple expense details to the server so that the server can perform compliance verification on the personnel and locations in each expense detail according to the configuration data; S310, if it receives a rejection signal from the server, displays a prompt interface containing specific error information and provides one-click correction recommendations for the error to guide the user to adjust the input.

[0064] The above method can be executed by a client that provides the expense report form filling interface. After the user associates an approved business trip application, the client receives configuration data from the server, including the selectable range of personnel for this business trip and the set of allowed reimbursement locations generated based on the application. Subsequently, during the expense details entry process, the client dynamically renders the personnel and location input controls, displaying only the compliant options to achieve proactive constraints on front-end input. When the user performs a city search, the client performs prefix matching filtering on the set of allowed reimbursement locations locally and returns the results that meet the conditions in real time. When the user submits the expense report, the client sends data containing all expense details to the server, triggering back-end compliance verification. If a rejection signal is received from the server, a prompt interface containing specific error information is displayed, and intelligent replacement recommendation options based on personal historical behavior, group preferences, and contextual information are provided for each error, supporting one-click adoption for quick content correction.

[0065] The client-side method described in this embodiment is not only a passive execution of server-side rules, but also a key vehicle for optimizing user experience. Through localized data processing, intelligent interactive control, and closed-loop feedback guidance, this method achieves a complete closed loop from front-end data loading, input control, local interaction to submission verification and intelligent feedback, thereby improving the compliance of reimbursement operations and the user experience.

[0066] To facilitate understanding, this invention also provides an application example of a travel expense reimbursement data verification method based on application form association. This invention constructs a dynamic range control and compliance verification engine integrated into the core of the travel expense reimbursement system. This engine uses the "travel application form" as a trusted data source and implements system-level mandatory constraints on the "personnel" and "city" dimensions at two key stages: the completion (front-end) and submission (back-end). This ensures that reimbursement activities always occur within the approved scope, forming a dual-protection closed loop of "front-end prevention and back-end verification." Its core implementation process is as follows: 1) Data binding and initialization phase: When a user selects an approved business trip application form through the "Associate Application Form" control on the expense report form, the data binding operation is triggered.

[0067] The engine retrieves the "List of Travelers (Multiple Selections)" and "Itinerary Plan (An Ordered List Containing Multiple City Nodes)" for the application form from the database using the application form ID.

[0068] Automatically populate the "Travelers List" into the "Personnel on This Business Trip" field (a multi-select dropdown) of the expense report, and set this list as the only selectable range for the "Personnel" field in subsequent expense details.

[0069] Extract all unique city names from the "Itinerary Planning" data, generate a "Set of Cities Allowed for Reimbursement", and associate it with the reimbursement form instance to control the display of the front-end city selection component.

[0070] 2) Front-end real-time range control stage: Personnel control: When a user fills in the "Personnel" field in the expense details, the pop-up selector only displays the "Personnel on this business trip" list brought out from the application form. Other personnel are automatically filtered out and cannot be selected from the interface at all.

[0071] City Control: When a user enters the "City" field, whether through a dropdown selection or a search, the city selection component will only display and return cities from the "Set of Cities Allowed for Reimbursement". Its search algorithm is client-side filtering, matching only within this set.

[0072] 3) Backend integration and verification phase: After the expense report is submitted, the "compliance verification" node in the system workflow is triggered, sending an outbound message to a dedicated integrated verification service (such as FVC), with the expense report ID in the message body.

[0073] After receiving the message, the verification service queries all data based on the expense report ID and executes the core verification algorithm. This algorithm iterates through each expense detail in the expense report and performs two key checks.

[0074] 4) Status adjudication and process advancement phase: Verification passed: If all the personnel and cities in the expense details are within the allowable range of the application, the verification service returns an "pass" signal, and the expense report will proceed normally to the subsequent approval process.

[0075] Verification Rejection: If any person or city in any expense detail is outside the allowed range, the verification service will return a "Rejection" signal with a specific error comment (e.g., "Person 'Zhang San' in line X of the expense detail is not within the scope of travelers in the business trip application" or "City 'Shenzhen' in line Y of the expense detail is not within the itinerary of the business trip application"). The system will automatically reject the expense report back to the submitter's node and display the error message, requiring them to make corrections.

[0076] As a concrete example, the key technical means in each step of a travel expense reimbursement data verification method based on application form association will be described in detail below. Preferably, a specific implementation scheme is as follows (including the implementation of the following five major module functions): I. Data Association and Range Set Generation Module; the core method is a three-dimensional range extraction algorithm.

[0077] This method automatically extracts three dimensions—personnel, city, and time—from the application form ID to establish a three-dimensional boundary constraint for reimbursement data.

[0078] The algorithm process includes: (A1) Application Form Data Analysis: Input: Unique identifier for the application form; Processing: Obtain complete application information through the data access layer, including basic information, traveler list, itinerary planning, and business trip duration; Output: Structured application form data object.

[0079] (A2) Personnel Scope Extraction: Parse the list of multiple-select personnel from the "Traveler" field of the application form; verify the validity and availability of the personnel information; generate a set of unique identifiers for the personnel.

[0080] (A3) City Scope Extraction: The city node data of the itinerary planning component is analyzed; a deduplication algorithm is used to generate a set of unique cities; and a standardized mapping of city names is established.

[0081] (A4) Time range extraction: Extract the start and end dates of the business trip from the application form; Construct a valid time interval [start_date, end_date]; Set up a time tolerance mechanism (such as extending by 1 day before or after to adapt to actual traffic demand).

[0082] Case Description: An application form includes: Traveler: [A, B, C], Itinerary: [Beijing → Shanghai → Beijing → Guangzhou], Business Trip Dates: January 10, 2025 to January 15, 2025.

[0083] The system extracts and generates the following data: Personnel range: {A, B, C}, City range: {Beijing, Shanghai, Guangzhou}, Time range: [2025-01-10, 2025-01-15] (including fault tolerance mechanism from 2025-01-09 to 2025-01-16).

[0084] II. Front-end range control module; The core method is the range constraint rendering method, which implements real-time range constraints in the front-end interface to prevent out-of-bounds operations from the interaction level.

[0085] Implementation strategies include: Personnel selector constraint method: The selector data source is bound to the extracted personnel range set; a whitelist filtering mechanism is used to display only personnel within the range; real-time search filtering is implemented, and the search range is limited to the constraint set; The intelligent filtering method for the city selector is as follows: the set of allowed cities is loaded during the initialization of the city component; a prefix matching search algorithm is implemented to perform the search within the constraint set; and an empty status prompt is provided to clearly inform the user of the reason for the lack of data.

[0086] Example: When a user enters "state" in the city selector: the system performs a search within the set {Beijing, Shanghai, Guangzhou}; the returned match result is Guangzhou; other cities such as "Zhengzhou" and "Hangzhou" will not appear in the results.

[0087] III. Compliance Verification Engine Module; The core method is a two-dimensional cross-validation algorithm, which performs a final compliance verification on the reimbursement data upon submission to ensure that business rules are strictly enforced.

[0088] Algorithm Design: (C1) Data preparation stage: Obtain complete data instance of expense report; load the associated application form range constraint set; prepare the verification result data structure.

[0089] (C2) Verification stage: Traverse each expense detail record; Verify the affiliation of the executor: Check that the detailed personnel ∈ the application form personnel set; Verify the inclusion relationship of the execution city: Check that the detailed city ∈ the application form city set.

[0090] (C3) Result aggregation stage: Collect all verification failure records; generate detailed error reports; and provide user-friendly prompts.

[0091] Case Description: The expense report includes the following details: <1> Person A, City: Beijing; <2> Personnel B, City Shanghai; <3> Person C, city Shenzhen; (Shenzhen is not among {Beijing, Shanghai, Guangzhou}); <4> Person D, city Beijing; (D is not in {A,B,C}); The system returned a verification failure message: "The city of Shenzhen in line 3 is outside the application scope; Person D in line 4 is not within the scope of travelers."

[0092] IV. Anomaly and Boundary Condition Handling Module; Core approach: Intelligent hierarchical fault tolerance and adaptive optimization strategy. This module provides differentiated anomaly handling solutions based on employee rank, historical behavior, and enterprise rules, and achieves continuous process optimization through blockchain notarization and data analysis.

[0093] It mainly includes the following four parts (4.1-4.4): (4.1) Hierarchical authorization exception handling mechanism; Implementation method: dynamic rule engine based on RBAC model; Job level permission mapping algorithm: Establish a mapping relationship between employee job levels and exception handling permissions; define fault tolerance thresholds and processing scopes for different job levels; and implement real-time permission verification and access control.

[0094] Example of job title processing rules: Junior staff: Strict mode, the system will force the association of unrelated applications; there is no tolerance period for the time range, and the application cycle will be strictly matched; any application that exceeds the range will be rejected directly.

[0095] Intermediate staff: Standard mode, temporary creation and automatic filing are allowed when there are no associated application forms; a standard error tolerance period of 1 day is provided within the time range; supervisor approval can be triggered if a single dimension is slightly exceeded.

[0096] Senior staff / managers: Flexible mode, supporting special reimbursement scenarios without application forms; configurable time tolerance period, supporting multi-dimensional special approvals; emergency handling process can be initiated for major anomalies.

[0097] (4.2) Blockchain-based evidence storage and audit trail; Implementation method: Distributed ledger evidence storage mechanism; (4.2.1) Abnormal event on-chain process: When the system detects an abnormal scenario, it automatically generates an abnormal event summary; writes the abnormal information, processing process and approval records into the blockchain through smart contracts; and generates an immutable timestamp and digital fingerprint. Evidence storage data structure: json { "event_id": "Unique event identifier", "employee_id": "employee number", "exception_type": "Exception type", "original_data": "Original data snapshot", "handling_process": "Process log", "approval_chain": "Approval chain information", "timestamp": "Blockchain timestamp", "transaction_hash": "Transaction hash value" } (4.2.2) Audit trail method: Provides complete exception handling and tracing capabilities; Support regulatory review and internal audit; Ensure transparency and compliance in the processing procedures.

[0098] (4.3) Adaptive rule optimization engine; Implementation method: rule iterative optimization based on machine learning; (4.3.1) Abnormal data collection and analysis: Real-time collection of the frequency of occurrence and processing results of various abnormal scenarios; Establish an anomaly pattern recognition model to identify high-frequency anomaly types; Analyze the root causes of anomalies and identify defects in system rules.

[0099] Data metrics dimensions: anomaly type distribution statistics, job level anomaly pattern analysis, time period anomaly trend identification, processing success rate and user satisfaction.

[0100] (4.3.2) Automatic rule optimization process: The optimized algorithm framework includes: data acquisition stage, pattern recognition stage, rule evaluation stage, and rule iteration stage.

[0101] (4.3.3) Specific optimization case: Scenario 1: Frequent occurrences of unrelated application form anomalies; Problem identification: Statistics show that 30% of junior employees encounter this anomaly at least once a week; Root cause analysis: The system's mandatory association requirements are too strict, and the application form creation process is complex; Optimization measures include: adding a "Quick Re-entry Application" function for junior employees; simplifying the application form creation process and providing preset commonly used templates; and adding application form creation guidelines and training tips.

[0102] Results verification: After optimization, the occurrence rate of this anomaly was reduced to 8%.

[0103] Scenario 2: Insufficient time tolerance; Problem identification: Among the time-related anomalies among mid-level employees, 65% were due to objective reasons such as flight delays; Root cause analysis: The fixed 1-day tolerance period cannot meet the actual business needs; Optimization solution: Introduce a dynamic fault tolerance mechanism to automatically adjust according to the mode of transportation; provide a 3-hour buffer for flight delays and a 1-hour buffer for high-speed rail delays; integrate third-party delay certificates for automatic verification.

[0104] Results verification: Time dimension anomalies decreased by 42%, and user satisfaction increased by 35%.

[0105] (4.4) Intelligent early warning and proactive intervention; Implementation method: predictive anomaly management; (4.4.1) Anomaly Risk Prediction: Establish anomaly prediction models based on historical data; Identify high-risk employees and unusual scenarios; Early warning and preventative measures should be triggered in advance.

[0106] (4.4.2) Proactive intervention strategy: Provide personalized training for users with high frequency of abnormal behavior; Provide operational guidance before an anomaly occurs; Automatically optimize interface prompts and process guidance.

[0107] Through the three mechanisms of hierarchical authorization, blockchain notarization, and adaptive optimization, this system has achieved a shift from passive processing to proactive prevention, and has built a continuously evolving intelligent anomaly management system.

[0108] V. Status Synchronization and Message Notification Module; Core methodology: Intelligent corrective recommendation and predictive guidance mechanism. By analyzing users' historical behavior data, an intelligent recommendation model is built to provide users with accurate corrective suggestions and convenient one-click processing functions.

[0109] It mainly includes the following five parts (5.1-5.5): (5.1) Intelligent correction recommendation engine; Implementation method: recommendation algorithm based on collaborative filtering and behavior analysis.

[0110] (5.1.1) User behavior profile construction: collect users' historical correction records and selection preferences; analyze users' commonly used correction patterns and habit paths; establish a knowledge base of correction behaviors for individuals and groups.

[0111] Data collection dimensions: selection of historical error types and correction methods; frequently used cities and personnel association preferences; time scheduling habits; approval rate and correction efficiency indicators.

[0112] (5.1.2) Intelligent replacement recommendation algorithm; The recommendation engine workflow includes: recommendations based on individual historical behavior, recommendations based on collective intelligence, recommendations based on contextual association, and the fusion and ranking of recommendation results.

[0113] (5.2) One-click intelligent replacement function; implementation method: context-aware automatic correction technology.

[0114] (5.2.1) Intelligent Replacement Button Mechanism: Provide an "Intelligent Replacement" operation button for each verification error; the system automatically recommends 1-3 most likely correct options; and supports users to accept the recommended results with one click.

[0115] Replacement strategy example: Example: The city field "Shenzhen" is not within the allowed range {Beijing, Shanghai, Guangzhou}; The system analyzes the user's historical behavior: this user will choose "Guangzhou" 80% of the time; Group data analysis: 60% of employees in similar positions chose "Guangzhou", and 30% chose "Shanghai"; Contextual analysis: "Guangzhou" appears most frequently in the itinerary planning; Recommendation result: Guangzhou is recommended first, followed by Shanghai.

[0116] (5.2.2) Batch intelligent processing function: Provides a global "Batch Intelligent Correction" button; the system automatically identifies error types that can be processed in batches; supports previewing correction results and confirming execution.

[0117] (5.3) Predictive recommendation optimization mechanism; Implementation method: dynamic recommendation optimization based on machine learning.

[0118] (5.3.1) Recommendation effect feedback learning: record users' adoption of recommendation results; analyze the pattern characteristics of successful and unsuccessful recommendations; continuously optimize recommendation algorithm parameters and weights; The learning feedback process includes: collecting feedback data; adjusting model parameters; and updating user profiles.

[0119] (5.3.2) Context-aware recommendation enhancement: Adjust recommendation strategies based on business seasonality and special events; consider organizational structure changes and project cycle factors; adapt to corporate policy adjustments and rule updates.

[0120] (5.4) Intelligent guidance and interaction optimization; Implementation method: multi-dimensional user guidance strategy.

[0121] (5.4.1) Hierarchical prompting information system: Level 1 prompt: Simple error, directly display the replace button; Level 2 hint: Medium complexity error, multiple options recommended; Level 3 warning: Complex exception, providing detailed guidance process.

[0122] (5.4.2) Case Study: Intelligent Handling of Multiple Error Scenarios; When the check finds 3 errors: (1) Personnel error: Personnel "D" is not within the range of {A,B,C}; System recommendation: Based on historical data, we recommend replacing it with "B" (confidence level 85%). User action: Click "Replace with B".

[0123] (2) City error: The city "Shenzhen" is not in {Beijing, Shanghai, Guangzhou}; The system recommends offering three options: "Guangzhou" (70%), "Shanghai" (25%), and "Beijing" (5%). User action: Select "Guangzhou" and confirm.

[0124] (3) Time error: The date "2025-01-08" is not within the valid range; System recommendation: Automatically identify the most recent valid date "2025-01-09"; User action: Click "Correct to most recent valid date".

[0125] Processing effect: Traditional method: Users need to manually search and correct one by one, which takes an average of 5-10 minutes; Intelligent method: system recommendation + one-click processing, with an average processing time of less than 30 seconds; Corrected accuracy: improved from 75% to 92%; User satisfaction: Significantly improved, with a 60% decrease in the rate of repeated errors.

[0126] (5.5) Continuous optimization and personalized adaptation; Implementation method: closed-loop optimization based on user feedback.

[0127] (5.5.1) Recommendation quality monitoring: Real-time tracking of recommendation adoption rate and user satisfaction; identification of scenarios and patterns with poor recommendation performance; automatic triggering of recommendation strategy adjustments.

[0128] (5.5.2) Personalized learning evolution: As users use the service more frequently, the accuracy of recommendations continues to improve; it adapts to changes in personal work habits and preferences; and it forms a personalized assistance experience that becomes smarter the more it is used.

[0129] With its intelligent recommendations and one-click processing capabilities, this system not only provides clear modification guidance but also significantly improves the efficiency and accuracy of corrections, achieving an upgraded experience from "informing you of the problem" to "helping you solve it."

[0130] In summary, the travel expense reimbursement data verification method and system based on application form association provided by the embodiments of the present invention ensure that the reimbursement content is strictly controlled within the application scope through automatic verification, reducing errors in manual review and improving reimbursement compliance; automatic data import and scope restriction reduce employee errors and repeated modifications, speeding up the reimbursement process and improving its efficiency; data linkage and status synchronization between application forms and reimbursement forms are realized, forming a closed-loop management system and enhancing system synergy; and scope restriction is supported on both PC and mobile terminals, ensuring process consistency and user experience.

[0131] The system provided in this embodiment of the invention can be specific hardware on a device or software or firmware installed on the device. The implementation principle and technical effects of the system / device provided in this embodiment of the invention are the same as those in the foregoing method embodiments. For the sake of brevity, any parts not mentioned in the system / device embodiments can be referred to the corresponding content in the foregoing method embodiments. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can all be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0132] Based on the same inventive concept, embodiments of the present invention also provide an electronic device, specifically, the electronic device includes a processor and a storage device; the storage device stores a computer program, and the computer program, when run by the processor, executes the method described in any of the above embodiments.

[0133] Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. The electronic device 400 includes: a processor 410, a memory 420, a communication interface 430, and a bus 440. The memory 420 stores machine-readable instructions that can be executed by the processor 410. When the electronic device is running, the processor 410 communicates with the memory 420 through the bus 440. The processor 410 executes the machine-readable instructions to perform the steps of the method described above.

[0134] Specifically, the memory 420 and processor 410 can be general-purpose memory and processor, without any specific limitations. When the processor 410 runs the computer program stored in the memory 420, it can execute the above method.

[0135] Processor 410 may be an integrated circuit chip with signal processing capabilities. In implementation, each step of the above method can be completed by the integrated logic circuitry in the hardware of processor 410 or by instructions in software form. The processor 410 may be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this invention. The general-purpose processor may be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this invention can be directly manifested as execution by a hardware decoding processor, or execution by a combination of hardware and software modules in the decoding processor. The software module can reside in a mature storage medium in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, or registers. This storage medium is located in memory 420, and processor 410 reads the information from memory 420 and, in conjunction with its hardware, completes the steps of the above method.

[0136] Corresponding to the above method, this embodiment of the invention also provides a computer-readable storage medium storing machine-executable instructions. When the machine-executable instructions are called and run by a processor, the machine-executable instructions cause the processor to perform the steps of the above method.

[0137] In the embodiments provided by this invention, it should be understood that the disclosed apparatus and method can be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. Furthermore, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Additionally, the displayed or discussed mutual couplings, direct couplings, or communication connections may be through some communication interfaces; indirect couplings or communication connections between devices or units may be electrical, mechanical, or other forms.

[0138] Furthermore, the units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0139] Furthermore, the functional modules in the various embodiments of the present invention can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0140] It should be noted that if the functionality is implemented as a software module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0141] In this document, relational terms such as first and second are used only to distinguish one entity or operation from another entity or operation, without necessarily requiring or implying any such actual relationship or order between these entities or operations.

[0142] The above description is merely an embodiment of the present invention and is not intended to limit the scope of protection of the present invention. For those skilled in the art, the present invention can have various modifications and variations. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for verifying travel expense reimbursement data based on application form association, characterized in that, The method is executed by a server, which communicates with a client that provides an expense reimbursement form filling interface; the method includes: In response to the user's operation of associating an approved business trip application form in the expense reimbursement form filling interface, the system obtains the traveler list and itinerary planning information corresponding to the business trip application form, generates the selectable range of personnel for this business trip based on the traveler list, and extracts location information based on the itinerary planning information to generate a set of allowed reimbursement locations. Send a front-end control instruction to the client so that the client dynamically restricts the input options of the personnel field to only include members within the selectable range of the personnel on this business trip, and the input options of the location field to only include locations in the set of allowed reimbursement locations during the expense detail entry process; Receive expense report data submitted by the client, iterate through each expense detail record, and verify whether the personnel corresponding to the expense details are within the selectable range of personnel for this business trip, and whether the location is within the set of allowed reimbursement locations; If any of the aforementioned expense details fails the verification, a rejection signal containing the specific error identifier and violation explanation is generated, and the expense report is returned to the submission node. At the same time, a prompt message is returned to the client to guide the user to make corrections.

2. The method according to claim 1, characterized in that, Based on the trip planning information, location information is extracted and a set of locations eligible for reimbursement is generated, including: Obtain the itinerary plan consisting of multiple city nodes from the business trip application form; The city nodes in the itinerary plan are deduplicated to generate a set of unique city names. The set of non-repeating city names is determined as the set of allowed reimbursement locations.

3. The method according to claim 1, characterized in that, In response to the user's operation of associating an approved business trip application form in the expense reimbursement form filling interface, the method further includes: extracting the start date and end date of the business trip from the business trip application form, and constructing a valid time interval as the business trip time range; Verify that the occurrence time of each expense detail in the expense report falls within the business trip time range; Send a time constraint instruction to the client so that the client restricts or prompts the input of the time field during the expense details entry process, and only allows input within the business trip time range or the preset error tolerance period.

4. The method according to claim 1, characterized in that, After generating the rejection signal, the method further includes: Based on the job level of the user who submitted the expense report, a pre-configured set of exception handling rules is invoked to perform differentiated processing on the results that fail the verification; the set of exception handling rules includes fault tolerance modes corresponding to different job levels.

5. The method according to claim 4, characterized in that, The method also includes an adaptive rule optimization process: Collect historical verification failure records as exception event data; Cluster analysis is performed on abnormal event data containing historical verification failure records based on machine learning models to identify high-frequency anomaly types and root causes. The anomaly handling rule set is dynamically adjusted or the generation strategy for the selectable range of personnel and the set of allowed reimbursement locations for this business trip is updated based on the identification results.

6. The method according to claim 1, characterized in that, When returning a prompt message to the client, the method further includes: For each expense detail that fails verification, a smart replacement recommendation option is generated; the smart replacement recommendation option is generated based on the user's personal historical correction behavior data, correction preference data of groups with the same job position as the user, and / or the contextual association information of the current expense report; Provides a one-click adoption interface for users to select and automatically complete field corrections.

7. A method for verifying travel expense reimbursement data based on application form association, characterized in that, The method, executed by a client that provides an interface for filling out expense reports, includes: Receive configuration data from the server, which is generated based on the user's associated approved business trip application form, including the selectable range of personnel for this business trip and the set of allowed reimbursement locations; During the expense details entry process, the input controls are dynamically rendered to restrict the input options of the personnel field to only members within the selectable range of personnel on this business trip, and to restrict the input options of the location field to only locations within the set of allowed reimbursement locations; In response to the user's search operation in the expense reimbursement form filling interface, perform prefix matching filtering locally based on the set of allowed reimbursement locations and return the matching results; In response to the submission of the expense report, expense report data containing multiple expense details is sent to the server so that the server can perform compliance verification on the personnel and locations in each expense detail according to the configuration data. If a rejection signal is received from the server, a prompt interface containing specific error information is displayed, and one-click correction recommendations for the error are provided to guide the user to adjust the input.

8. A travel expense reimbursement data verification system based on application form association, characterized in that, The system is run by a server that communicates with a client that provides an expense reimbursement form filling interface; the system includes: The data association and scope extraction module is used to respond to the user's operation of associating the approved business trip application form in the expense reimbursement form filling interface, obtain the traveler list and itinerary planning information corresponding to the business trip application form, generate the selectable range of personnel for this business trip based on the traveler list, and extract location information based on the itinerary planning information and generate a set of allowed reimbursement locations. The front-end scope control module is used to send front-end control instructions to the client so that the client can dynamically restrict the input options of the personnel field to only include members within the selectable range of the personnel on this business trip, and the input options of the location field to only include locations in the set of allowed reimbursement locations during the expense details entry process. The compliance verification module is used to receive expense report data submitted by the client, traverse each expense detail record, and verify whether the personnel corresponding to the expense details are within the selectable range of personnel for this business trip, and whether the location is within the set of allowed reimbursement locations. The rejection signal generation module is used to generate a rejection signal containing a specific error identifier and a violation description if any of the aforementioned expense details fails the verification, and to return the expense report to the submission node, while simultaneously returning a prompt message to the client to guide the user in making corrections.

9. An electronic device comprising a memory and a processor, wherein the memory stores a computer program executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions that, when invoked and executed by a processor, cause the processor to perform the method according to any one of claims 1 to 7.

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