Exterior complaint processing method and system for consumer finance complex case

Abstract

The invention belongs to the technical field of information processing, and provides a consumer finance complex case foreign complaint processing method and system, and the technical scheme is as follows: judging whether acceptance conditions are met or not according to received customer information submitting foreign complaint cases and foreign complaint case information; distributing the cases meeting the acceptance conditions; client identity information corresponding to the distributed foreign complaint case is identified, a consumer financial record related to the client is searched based on the client identity information, the consumer financial record is associated with the foreign complaint case, the associated data is verified, and a case report is generated after verification is completed; analyzing the case report, and extracting key information in the case; and generating an external complaint processing strategy according to the specific demand of the external complaint case and the key information in the case, and if the external complaint processing strategy does not meet the requirement or is not achieved, performing risk assessment to obtain a risk assessment result. And effective processing of complex consumption amount foreign complaints can be realized.

Description

Technical Field

[0001] The present invention belongs to the technical field of information processing, and particularly relates to a method and system for handling external complaints of complex consumer finance cases. Background Art

[0002] The statements in this part only provide background technical information related to the present invention and do not necessarily constitute prior art.

[0003] In the field of consumer finance, the handling of external complaint cases has always been a complex and cumbersome process. Traditional handling methods often rely on manual operations, which are not only inefficient but also error-prone. With the development of technology, automated and intelligent handling methods have gradually become the trend.

[0004] However, there are still some problems with existing automated handling methods and they cannot comprehensively cover all case types: Due to the diversity and complexity of cases, it is difficult for existing automated handling methods to cover all types of cases. For some special and complex cases, existing methods may not be able to give accurate handling suggestions or results. Limited ability to handle complex cases: For complex cases, such as those involving multiple-party disputes, complex evidence, or legal professional knowledge, existing automated handling methods often have difficulty coping. Summary of the Invention

[0005] In order to solve at least one of the above technical problems in the background art, the present invention provides a method and system for handling external complaints of complex consumer finance cases, which can comprehensively cover various case types and significantly improve the ability to handle complex cases.

[0006] To achieve the above object, the present invention adopts the following technical solutions:

[0007] The first aspect of the present invention provides a method for handling external complaints of complex consumer finance cases, including the following steps:

[0008] Receive customer information and external complaint case information submitted for external complaints;

[0009] Judge whether it meets the acceptance conditions according to the received customer information and external complaint case information of the external complaint case;

[0010] Allocate the cases that meet the acceptance conditions;

[0011] Identify the customer identity information corresponding to the allocated external complaint case, search for consumer finance records related to the customer based on the customer identity information, associate the consumer finance records with the external complaint case, verify the associated data, and generate a case report after the verification is completed;

[0012] Analyze the case report and extract the key information in the case;

[0013] Generate an external litigation handling strategy based on the specific requirements of the external litigation case and the key information in the case, determine whether the external litigation handling strategy meets the requirements. If it meets the requirements, send it to the client and receive the feedback from the client, and determine whether a settlement is reached with the client. If a settlement is reached, close the case; if the external litigation handling strategy does not meet the requirements or no settlement is reached, conduct a risk assessment to obtain the risk assessment result.

[0014] Furthermore, the customer information of the external litigation case includes the customer's name, ID number, and contact information;

[0015] The external litigation case information includes basic information and case details. The basic information includes the case number, case type, and submission time; the case details include the involved amount, relevant evidence, urgency, and handling requirements.

[0016] Furthermore, the allocation of cases that meet the acceptance conditions specifically includes:

[0017] Obtain the case tags of multiple cases that meet the acceptance conditions and the professional skill tags of multiple corresponding handlers, and calculate the matching degree of the handlers corresponding to multiple cases according to the preset first allocation rule;

[0018] Based on the matching degree of the handlers corresponding to multiple cases, determine the balanced allocation plan for cases according to the preset second allocation rule;

[0019] Based on the personnel allocation plan corresponding to the cases that meet the acceptance conditions, determine the priority of the cases and the priority of the handlers according to the preset third allocation rule.

[0020] Furthermore, the calculation of the matching degree of the handlers corresponding to multiple cases according to the preset first allocation rule is:

[0021]

[0022] where P k represents the matching degree between the kth case that meets the acceptance conditions and the handler, k is a natural number between 1 and K, K is the number of cases that meet the acceptance conditions, and λ i represents the weight of the professional skill of the ith handler; p ki represents the matching degree between the professional skill tag of the ith handler and the kth tag of the case that meets the acceptance conditions.

[0023] Furthermore, the determination of the balanced allocation plan for cases according to the preset second allocation rule is:

[0024] fit = W 1 C complexity + W 2 Mcomplaint +W 3 E tendency ,

[0025] Among them, C complexity represents the complexity of the case, M complaint represents whether there are multiple complaints, and E tendency represents the tendency of complaint escalation; W 1 、W 2 and W 3 are the weights of the corresponding factors.

[0026] Furthermore, parsing the case report to extract key information in the case, including:

[0027] Preprocessing the case report text, including removing irrelevant characters, word segmentation, and part-of-speech tagging;

[0028] Analyzing the preprocessed case report text to extract key information in the case text;

[0029] Comparing the extracted key information with a preset database or rules, and if the comparison result is not equal, sending a prompt message and an alarm message.

[0030] Furthermore, if the external complaint handling strategy does not meet the requirements or no settlement is reached, a credit risk assessment is carried out, specifically including:

[0031] Obtaining data related to consumer finance collected from multiple channels;

[0032] Extracting feature variables from the preprocessed data according to the requirements of risk assessment;

[0033] Training a trained credit risk assessment model based on the extracted feature variables and the constructed credit risk assessment model;

[0034] Evaluating the data of the customer to be predicted based on the trained credit risk assessment model to obtain a credit risk assessment result.

[0035] The second aspect of the present invention provides an external complaint handling system for complex consumer finance cases, including:

[0036] An information receiving module, which is used to receive customer information and external complaint case information submitted for external complaints;

[0037] A case allocation module, which is used to judge whether it meets the acceptance conditions according to the received customer information and external complaint case information submitted for external complaints; allocating the cases that meet the acceptance conditions;

[0038] A case report generation module, which is used to identify the customer identity information corresponding to the assigned external lawsuit cases, search for consumer finance records related to the customers based on the customer identity information, associate the consumer finance records with the external lawsuit cases, verify the associated data, and generate a case report after the verification is completed;

[0039] A case report parsing module, which is used to parse the case report and extract the key information in the case;

[0040] A risk assessment module, which is used to generate an external lawsuit handling strategy according to the specific requirements of the external lawsuit cases and the key information in the cases, judge whether the external lawsuit handling strategy meets the requirements, if it meets, send it to the client, and receive the feedback from the client, judge whether a settlement is reached with the customer, if a settlement is reached, close the case; if the external lawsuit handling strategy does not meet the requirements or no settlement is reached, conduct a risk assessment to obtain a risk assessment result.

[0041] The third aspect of the present invention provides a computer-readable storage medium.

[0042] A computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the steps in an external lawsuit handling method for a complex consumer finance case as described above are implemented.

[0043] The fourth aspect of the present invention provides a computer device.

[0044] A computer device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, and when the processor executes the program, the steps in an external lawsuit handling method for a complex consumer finance case as described above are implemented.

[0045] Compared with the prior art, the beneficial effects of the present invention are:

[0046] 1. When the present invention is used for handling external lawsuits in consumer finance, aiming at the problems of the complexity and diversity of cases, by specifically assigning different types and degrees of cases to corresponding handlers, and at the same time generating corresponding external lawsuit handling strategies, and being able to conduct risk assessment on the external lawsuit handling strategies with risks, the ability and efficiency of handling external lawsuits are improved.

[0047] 2. When the present invention assigns cases that meet the acceptance conditions, comprehensively considering the matching degree between the cases and the handlers, the balanced distribution plan of the cases, and the priorities of the cases and the handlers, it can comprehensively cover various case types, especially for complex cases such as cases involving multiple disputes, complex evidence, or cases involving legal professional knowledge, and can handle external lawsuits well, significantly improving the handling ability of complex cases.

[0048] Advantages of additional aspects of the present invention will be given in part in the following description, become apparent in part from the following description, or be learned by practice of the present invention. Brief Description of the Drawings

[0049] The accompanying drawings forming a part of this specification are used to provide a further understanding of the present invention. The schematic embodiments and descriptions thereof of the present invention are used to explain the present invention and do not constitute an improper limitation to the present invention.

[0050] Figure 1 It is a flowchart of a method for handling external complaints of complex consumer finance cases provided by an embodiment of the present invention. Detailed Embodiments

[0051] The present invention will be further described below in conjunction with the drawings and embodiments.

[0052] It should be noted that the following detailed description is illustrative and is intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which the present invention belongs.

[0053] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular forms are also intended to include the plural forms. In addition, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they specify the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0054] Embodiment 1

[0055] As Figure 1 shown, this embodiment provides a method for handling external complaints of complex consumer finance cases, including the following steps:

[0056] Step 1: Receive customer information and external complaint case information of the submitted external complaint case;

[0057] In this embodiment, the customer information of the external complaint case includes customer name, ID number, and contact information;

[0058] Customer name: Record the full name of the customer for easy identification of the customer and subsequent communication.

[0059] ID number: Used to verify the authenticity and accuracy of the customer's identity.

[0060] The external complaint case includes basic information and case details;

[0061] The basic information includes the case number, case type, and submission time;

[0062] Among them, case number: A unique number is assigned to each case for subsequent tracking and management;

[0063] Case type: Classify cases according to the nature of the case and the business areas involved, such as loan disputes, credit card overdue, etc.;

[0064] Submission time: Record the specific time when the customer submits the case for evaluating the processing time limit.

[0065] Contact information: Include the customer's contact phone number, address, etc. for maintaining contact with the customer.

[0066] Case details include case description, involved amount, urgency, and handling requirements;

[0067] Case description: The customer's detailed description of the case, including points of dispute, demands, etc.

[0068] Involved amount: Record the size of the amount involved in the case for evaluating the importance and risk of the case.

[0069] Relevant evidence: Evidence materials provided by the customer related to the case, such as contracts, transaction records, communication records, etc.

[0070] Urgency: The customer's description of the urgency of the case for giving priority to handling urgent cases.

[0071] Handling requirements: The customer's specific requirements or expectations for case handling, such as hoping to resolve it as soon as possible, hoping to communicate with specific personnel, etc.

[0072] During the case registration process, it is necessary to ensure the accuracy and completeness of all information for the smooth progress of subsequent steps. At the same time, it is also necessary to keep the registered information confidential to ensure the safety of customer privacy.

[0073] Step 2: Judge whether it meets the acceptance conditions according to the customer information and the external complaint case information of the received external complaint case;

[0074] In this embodiment, a preliminary review is conducted on the registered case to judge whether the case meets the acceptance conditions. If it meets, proceed to the next step; if not, feedback to the customer and explain the reasons.

[0075] The specific review principles are as follows:

[0076] First, classify the cases into different categories (such as contract disputes, fraud complaints, service problems, etc.) according to the nature and type of the cases;

[0077] Then judge and check whether the case is within the statute of limitations, whether it falls within the company's jurisdiction, whether it has been processed before, etc.

[0078] Check the integrity and compliance of case information, including checking whether the case contains necessary documents (such as contracts, transaction records, complaint letters, etc.), and whether these documents meet the format and requirements stipulated by laws or internal company regulations;

[0079] If the case does not meet the acceptance conditions, send a notice of rejection of acceptance to the customer and explain the reasons.

[0080] Number the cases that meet the acceptance conditions and record the basic information of the cases (such as customer name, contact information, case type, acceptance date, etc.). This information will be used for tracking and recording in the subsequent processing.

[0081] Step 3: Allocate the cases that meet the acceptance conditions;

[0082] In this embodiment, the cases are allocated according to the preset allocation rules, specifically including the matching degree between the cases and the processing personnel, the balanced allocation plan of the cases, and the priorities of the cases and the processing personnel;

[0083] Specifically, it includes the following steps:

[0084] Step 301: Obtain the case tags of multiple cases that meet the acceptance conditions and the professional skill tags corresponding to multiple processing personnel, and calculate the matching degree between the processing personnel corresponding to the multiple cases according to the preset first allocation rule;

[0085] Among them, when calculating the matching degree between the case and the processing personnel, first obtain the tag of each processing personnel, and then determine the matching degree between the case and the processing personnel based on the tag of each processing personnel and the tag that meets the acceptance conditions;

[0086] In this embodiment, when obtaining the tag of each processing personnel, set multiple customer service seat skill groups, and divide each skill group into 4 levels according to the professional skill weight, namely primary, intermediate, advanced, and expert levels. Use the skill group to distinguish the professional skill matching degree, and use the level to distinguish the professional skill weight. According to the number of customer service cases processed, distinguish the experience weight and experience matching degree of the processing personnel. The matching degree calculation formula between the case and the processing personnel is:

[0087]

[0088] Among them, P k represents the matching degree between the kth case that meets the acceptance conditions and the processing personnel, k takes natural numbers between 1 and K, K is the number of cases that meet the acceptance conditions, λ i represents the weight of the professional skill of the ith processing personnel; p ki represents the matching degree between the professional skill tag of the ith processing personnel and the kth tag of the case that meets the acceptance conditions;

[0089] The calculation method for the matching degree between the k-th label of a case meeting the acceptance conditions and the labels of the i-th handler is as follows: Calculate the matching degrees between the i-th label of the case meeting the acceptance conditions and all the labels of the k-th handler respectively; Screen out the highest matching degree; Take the highest matching degree as the matching degree between the k-th label of the case meeting the acceptance conditions and the labels of the i-th handler.

[0090] Through the matching degree calculation formula for cases and handlers, ensure that cases are assigned to handlers who are good at handling such cases; During the assignment process, the professional background and work experience of the handlers will be considered. For example, for cases involving complex legal issues, they may be preferentially assigned to personnel with relevant legal backgrounds or rich handling experience.

[0091] Step 302: Based on the matching degrees of the handlers corresponding to multiple cases, determine the balanced assignment plan for the cases according to the preset second assignment rule;

[0092] In this embodiment, the second assignment rule is the case balanced assignment rule, which is a method designed to ensure that cases can be fairly and effectively assigned to each handler. This rule considers multiple factors, including the complexity of the case, whether there are multiple complaints, and whether there is a tendency for complaint escalation, etc., to ensure that each handler can receive cases that match their capabilities. The case balanced assignment fitness calculation formula is:

[0093] fit = W 1 C complexity + W 2 M complaint + W 3 E tendency ,

[0094] Among them, C complexity represents the complexity of the case, M complaint represents whether there are multiple complaints, E tendency represents the existence of a tendency for complaint escalation; W 1 、W 2 and W 3 are the weights of the corresponding factors.

[0095] For example, if a certain handler is particularly good at handling complex cases, then the weight of the complexity can be appropriately increased. By this method, it can be ensured that cases can be evenly assigned to each handler while considering the characteristics of the cases and the capabilities of the handlers.

[0096] At the same time, consider the quantity balance of case assignment in the case balanced assignment determination mechanism to ensure that the number of cases among handlers remains relatively balanced and avoid overloading individual personnel.

[0097] Step 303: Based on the personnel allocation plan corresponding to the cases that meet the acceptance conditions, determine the priority of the cases and the priority of the processing personnel according to the preset third allocation rule;

[0098] In this embodiment, the preset third allocation rule is: determine the case priority and the priority of the processing personnel corresponding to the cases that meet the acceptance conditions according to the case tags of the multiple cases;

[0099] For example, the case priority tags corresponding to the cases that meet the acceptance conditions are formulated according to the time of submitting the case, the type of the submitted case, the urgency of the case, and the difficulty of handling;

[0100] The priority of the processing personnel is based on the type of professional skills of the processing personnel, the idle situation of the processing personnel, etc.

[0101] Step 4: Identify the customer identity information corresponding to the allocated external complaint cases, search for the consumer finance records related to the customers based on the customer identity information, associate the consumer finance records with the external complaint cases, and perform verification on the associated data. After the verification is completed, generate a case report;

[0102] Specifically, it includes the following steps:

[0103] Step 401: First, perform a preliminary identity identification through the basic information (such as name, ID number, contact phone number, etc.) provided in the external complaint cases submitted by the customers.

[0104] For customers with existing consumer finance records, the identity information can be quickly matched through database query.

[0105] For new customers or cases with incomplete information, a more detailed verification process will be adopted, including technical means such as verification code verification and face recognition.

[0106] Step 402: Once the identity information is confirmed to be correct, the system will automatically search for all the consumer finance records of this customer in the background database, including but not limited to borrowing records, repayment records, overdue records, etc. Step 403: Associate the consumer finance records with the external complaint cases;

[0107] Specifically, it includes: judge whether there is a case number in the description of the consumer finance record. If so, ensure the unique correspondence between each case number and the customer record to avoid duplicate association or omission. If not, perform comparison from multiple dimensions of the consumer finance record description to obtain the association result;

[0108] In this embodiment, the multiple dimensions include comparison and analysis of multiple dimensions such as case description, involved amount, timestamp, etc. Conflict resolution mechanism:

[0109] When the system encounters unrecognized customer information or data conflicts, it will issue a prompt message and require the operator to make manual corrections. The corrected data will be synchronously updated to the case status and information to ensure data accuracy and integrity.

[0110] Step 404: Verify the associated data and generate a case report after verification;

[0111] Comprehensively verify the associated data to ensure data accuracy, integrity, and consistency.

[0112] After the data integration is completed, the system will automatically generate a detailed case report, including basic case information, customer credit status, dispute focus, etc.

[0113] Step 5: Analyze the case report and extract the key information in the case;

[0114] Specifically, it includes the following steps:

[0115] Step 501: Preprocess the case report text, including steps such as removing irrelevant characters, word segmentation, and part-of-speech tagging;

[0116] Step 502: Analyze the preprocessed case report text and extract the key information in the case text;

[0117] In this embodiment, when analyzing the case report text, it is sufficient to use existing machine learning or deep learning algorithm models. Such as convolutional neural network (CNN), recurrent neural network (RNN), etc., which are used to process complex text data and extract deep-level features and information.

[0118] In this embodiment, the key information in the text, such as the name of the party, ID number, contact information, loan amount, loan term, repayment status, etc. These information are usually identified by specific keywords or phrases, such as "borrower", "loan amount", "repayment date", etc.

[0119] Step 503: Compare the extracted key information with a preset database or rules. If the comparison result is not equal, a prompt message and an alarm message will be issued.

[0120] Step 6: Generate an external lawsuit handling strategy according to the specific requirements of the external lawsuit case and the key information in the case, judge whether the external lawsuit handling strategy meets the requirements. If it meets, send it to the client and receive the feedback from the client, and judge whether a settlement is reached with the customer. If a settlement is reached, close the case; if the external lawsuit handling strategy does not meet the requirements or no settlement is reached, conduct a risk assessment to obtain a risk assessment result;

[0121] Specifically, it includes:

[0122] Step 601: Generate an external lawsuit handling strategy based on the specific requirements of the external lawsuit case and the key information in the case. Specifically, it includes: parsing the case report, extracting the key information in the case, such as the name of the parties, ID number, loan amount, loan term, repayment status, etc. Based on this key information and the specific requirements of the external lawsuit case (such as the customer hopes to resolve it as soon as possible, hopes to communicate with specific personnel, etc.), the system will comprehensively evaluate and generate the corresponding external lawsuit handling strategy. Finally, the system will verify and evaluate the generated external lawsuit handling strategy to ensure that it meets the requirements and standards of case handling.

[0123] Step 602: If the external lawsuit handling strategy does not meet the requirements or no settlement is reached, conduct a credit risk assessment, specifically including:

[0124] Step 6021: Obtain data related to consumer finance collected from multiple channels, including but not limited to the customer's credit record, repayment history, consumption behavior, social network data, etc. Perform preprocessing tasks such as cleaning, deduplication, and missing value handling on the collected data to improve data quality.

[0125] Step 6022: Extract feature variables from the preprocessed data according to the requirements of risk assessment. For example, when evaluating the feature variables of borrowers, extract age, gender, occupation, income status, historical default records, etc.

[0126] Step 6023: Based on the extracted feature variables, train a credit risk assessment model using machine learning algorithms such as logistic regression, decision tree, random forest, etc. to obtain a trained credit risk assessment model;

[0127] Step 6024: Evaluate the data of the customer to be predicted based on the trained credit risk assessment model to obtain a credit risk assessment result;

[0128] In this embodiment, the credit risk assessment result is calculated using the probability of default;

[0129] The calculation formula for the probability of default is:

[0130]

[0131] where Y is the default event (Y = 1 indicates default, Y = 0 indicates non - default), X is the feature variable of the borrower (such as age, income, etc.), and β is the prediction model parameter;

[0132] Step 6025: Automatically optimize the risk management strategy according to the assessment result;

[0133] For example, when it is found that the default risk of a certain type of customer is relatively high, the large model can automatically adjust the credit policy for this type of customer, such as reducing the loan amount or increasing the interest rate, etc.

[0134] Embodiment 2

[0135] This embodiment provides an external lawsuit processing system for complex consumer finance cases, including:

[0136] An information receiving module, which is used to receive customer information and external lawsuit case information for submitting external lawsuit cases;

[0137] A case allocation module, which is used to judge whether it meets the acceptance conditions according to the received customer information and external lawsuit case information for submitting external lawsuit cases; allocate the cases that meet the acceptance conditions;

[0138] A case report generation module, which is used to identify the customer identity information corresponding to the allocated external lawsuit case, search for consumer finance records related to the customer based on the customer identity information, associate the consumer finance records with the external lawsuit case, verify the associated data, and generate a case report after the verification is completed;

[0139] A case report parsing module, which is used to parse the case report and extract the key information in the case;

[0140] A risk assessment module, which is used to generate an external lawsuit processing strategy according to the specific requirements of the external lawsuit case and the key information in the case, judge whether the external lawsuit processing strategy meets the requirements. If it meets the requirements, send it to the client and receive the feedback from the client, and judge whether a settlement is reached with the customer. If a settlement is reached, close the case; if the external lawsuit processing strategy does not meet the requirements or no settlement is reached, conduct a risk assessment to obtain a risk assessment result.

[0141] Embodiment 3

[0142] This embodiment provides a computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, the steps in an external lawsuit processing method for complex consumer finance cases as described above are implemented.

[0143] Embodiment 4

[0144] This embodiment provides a computer device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, the steps in an external lawsuit processing method for complex consumer finance cases as described above are implemented.

[0145] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a hardware embodiment, a software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage and optical storage, etc.) containing computer-usable program code.

[0146] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the present invention. It should be understood that each flow and / or block in the flowchart and / or block diagram, and the combination of flows 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 the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices produce means for implementing the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or multiple blocks.

[0147] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory produce a manufactured article including instruction means that implement the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or multiple blocks.

[0148] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operating steps are performed on the computer or other programmable device to generate a computer-implemented process, so that the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or multiple blocks.

[0149] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above methods. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM), etc.

[0150] The above are only the preferred embodiments of the present invention and are not used to limit the present invention. For those skilled in the art, the present invention can have various changes and modifications. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for handling external litigation of complex consumer finance cases, characterized in that: The steps include: Receive information about clients who submit external litigation cases and information about external litigation cases; Determine whether the acceptance conditions are met based on the client information and case information of the received external litigation cases; Allocate cases that meet the acceptance criteria; Identify the customer identity information corresponding to the assigned external litigation case, search for the consumer finance records related to the customer based on the customer identity information, associate the consumer finance records with the external litigation case, verify the associated data, and generate a case report after the verification is completed; Parse case reports and extract key information from the case; Generate an external litigation handling strategy based on the specific needs of the external litigation case and the key information in the case, determine whether the external litigation handling strategy meets the requirements, and if so, send it to the client and receive feedback from the client to determine whether a settlement is reached with the client. If a settlement is reached, close the case; If the external litigation handling strategy does not meet the requirements or no settlement is reached, a risk assessment is conducted to obtain the risk assessment results.

2. A method for handling external litigation of complex consumer finance cases as claimed in claim 1, characterized in that: The customer information of the external litigation case includes the customer's name, ID number and contact information; The external litigation case information includes basic information and case details. The basic information includes the case number, case type and submission time; the case details include the amount involved, relevant evidence, urgency and handling requirements.

3. A method for handling external litigation of complex consumer finance cases as claimed in claim 1, characterized in that: The cases that meet the acceptance conditions will be allocated, including: Obtain case labels of multiple cases that meet acceptance conditions and professional skill labels corresponding to multiple processing personnel, and calculate matching degrees of processing personnel corresponding to the multiple cases according to a preset first allocation rule; Based on the matching degree of the processing personnel corresponding to the multiple cases, a balanced allocation plan of the cases is determined according to a preset second allocation rule; Based on the personnel allocation plan corresponding to the cases that meet the acceptance conditions, the priority of the cases and the priority of the processing personnel are determined according to the preset third allocation rule.

4. A method for handling external litigation of complex consumer finance cases as claimed in claim 3, characterized in that: According to the preset first allocation rule, the matching degree of the processing personnel corresponding to multiple cases is calculated as follows: Among them, P k represents the matching degree between the kth case that meets the acceptance conditions and the processing personnel, k is a natural number between 1 and K, K is the number of cases that meet the acceptance conditions, λ i represents the weight of the professional skills of the i-th processing personnel; p ki It represents the matching degree between the professional skill label of the i-th processing personnel and the k-th label of the case that meets the acceptance conditions.

5. A method for handling external litigation of complex consumer finance cases as claimed in claim 3, characterized in that: The balanced allocation scheme of the cases determined according to the preset second allocation rule is: fit=W1C complexity +W2M complaint +W3E tendency , Among them, C complexity Indicates the complexity of the case, M complaint Indicates whether there are multiple complaints, E tendency Indicates that there is a tendency for complaints to escalate; W1, W2 and W3 are the weights of the corresponding factors.

6. A method for handling external litigation of complex consumer finance cases as claimed in claim 1, characterized in that: The case report is parsed to extract key information from the case, including: Preprocess the case report text, including removing irrelevant characters, word segmentation, and part-of-speech tagging; Analyze the pre-processed case report text and extract key information from the case text; The extracted key information is compared with the preset database or rules. If the comparison results are not equal, prompt information and alarm information are issued.

7. A method for handling external litigation of complex consumer finance cases as claimed in claim 1, characterized in that: If the external litigation handling strategy does not meet the requirements or no settlement is reached, a credit risk assessment will be conducted, including: Obtain data related to consumer finance from multiple channels; Extract characteristic variables from preprocessed data according to the needs of risk assessment; Training is performed based on the extracted characteristic variables and the constructed credit risk assessment model to obtain a trained credit risk assessment model; The data of the customer to be predicted is evaluated based on the trained credit risk assessment model to obtain the credit risk assessment result.

8. A system for handling external complaints of complex consumer finance cases, characterized by: include: An information receiving module, which is used to receive information about the client who submitted the external litigation case and information about the external litigation case; A case allocation module is used to determine whether the received client information and case information of the external litigation case meet the acceptance conditions; and allocate the cases that meet the acceptance conditions; A case report generation module, which is used to identify the customer identity information corresponding to the assigned external litigation case, search for the consumer finance records related to the customer based on the customer identity information, associate the consumer finance records with the external litigation case, verify the associated data, and generate a case report after the verification is completed; A case report parsing module, which is used to parse case reports and extract key information from the case; The risk assessment module is used to generate an external litigation handling strategy based on the specific needs of the external litigation case and the key information in the case, determine whether the external litigation handling strategy meets the requirements, and if so, send it to the client and receive feedback from the client to determine whether a settlement is reached with the client. If a settlement is reached, the case is closed; If the external litigation handling strategy does not meet the requirements or no settlement is reached, a risk assessment is conducted to obtain the risk assessment results.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps in a method for handling external litigation of a complex consumer finance case as described in any one of claims 1-7 are implemented.

10. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the steps in the method for handling external litigation of complex consumer finance cases as described in any one of claims 1-7 are implemented.

Images