A non-performing asset disposal strategy method and related device

Abstract

This application discloses a method and related apparatus for non-performing asset (NPA) disposal, relating to the field of NPA disposal technology. It uses the due diligence results of NPAs as input and a standardized strategy generation model to determine the collection and disposal strategy for NPAs. The collection and disposal strategy refers to the method of collecting and disposing of NPAs. The target collection and disposal strategy selected by the user from the NPA collection and disposal strategies is broken down into multiple tasks. For each task, the execution status is monitored and recorded in real time until the task is completed. This application can utilize a standardized strategy generation model to conduct in-depth data analysis of the due diligence results of NPAs, intelligently recommending the best collection and disposal strategy, eliminating reliance on manual judgment. The disposal is data-supported, has a clear strategic plan guidance, improves collection efficiency, and enables effective risk control.

Description

Technical Field

[0001] This application relates to the field of non-performing asset disposal technology, and in particular to a non-performing asset disposal strategy, method and related apparatus. Background Technology

[0002] Non-performing assets (NPAs) mainly refer to assets that financial institutions are unable to recover principal and interest on schedule due to debtor default or other reasons, or assets that credit companies cannot effectively dispose of in the financial lending sector, such as overdue loans or situations where the value of collateral is lower than the loan balance. The disposal of NPAs aims to reduce non-performing loans and other non-performing assets on the balance sheet, thereby improving financial condition and reducing risk.

[0003] Traditional non-performing asset disposal systems mainly employ the following approaches: (1) utilizing big data to collect and manage basic debtor data; (2) implementing process-oriented management of non-performing asset disposal operations and establishing an online non-performing asset business processing platform; and (3) connecting with the bank's credit system and core system to synchronize data in real time and track overdue data. While these approaches provide basic data collection and business management functions through online processes, they lack in-depth data analysis capabilities. The disposal of diversified non-performing assets still relies on manual judgment, lacks data support, and is not guided by clear strategic solutions. This results in low efficiency, insufficient risk control, and a lack of intelligent recommendation of the best strategy. Consequently, the value of the data is not truly realized. Summary of the Invention

[0004] The purpose of this application is to provide a non-performing asset disposal strategy method and related apparatus, which can intelligently recommend the best collection and disposal strategy, improve collection efficiency, and enable effective risk control.

[0005] To achieve the above objectives, this application provides the following solution:

[0006] Firstly, this application provides a method for disposing of non-performing assets, the method comprising:

[0007] Using the due diligence results of non-performing assets as input, a standardized strategy generation model is used to determine the collection and disposal strategy for non-performing assets; the collection and disposal strategy refers to the collection and disposal method of non-performing assets.

[0008] The target collection and disposal strategy selected by the user from the collection and disposal strategies for non-performing assets is broken down into multiple tasks based on the user's needs;

[0009] For each of the tasks, the execution status of the task is monitored and recorded in real time until the task is completed.

[0010] Optionally, when the non-performing assets belong to a company, the due diligence results include information on the non-performing assets' claims, principal debtor information, guarantor information, and collateral information; the claim information includes basic claim information and collection litigation status, with basic claim information including the type of claim, debtor attributes, amount owed, completeness of claim documentation, and contractual dispute clauses; collection litigation status includes whether litigation conditions are met, whether the case has progressed to the litigation process, the litigation stage, and the litigation status; principal debtor information includes repayment willingness, repayment ability, and equity information, with equity information including whether it is a one-person limited liability company and whether the shareholder's capital contribution has not been fully paid up; guarantor information includes the type of guarantor, the legal nature of the guarantee, repayment willingness, and repayment ability; collateral information includes the type of collateral and the validity of the collateral.

[0011] When non-performing assets belong to individuals, the due diligence results include information on the debtor, principal debtor, guarantor, and collateral. Debt information includes the completeness of debt documentation, contractual dispute clauses, number of overdue days, whether litigation has commenced, the litigation stage, and the litigation status. Principal debtor information includes the willingness and ability to repay. Guarantor information includes the willingness and ability to repay. Collateral information includes whether there is collateral, the type of collateral, mortgage details, and collateral registration.

[0012] Optionally, before determining the collection and disposal strategy for non-performing assets using a standardized strategy generation model with the due diligence results as input, the non-performing asset disposal strategy method further includes:

[0013] Acquire historical data; the historical data includes historical due diligence results and historical collection and disposal strategies for non-performing assets.

[0014] The initial policy generation model is trained using the historical data to obtain a standardized policy generation model.

[0015] Optionally, the standardized strategy generation model uses weighted calculation or similarity calculation to determine the collection and disposal strategy for non-performing assets.

[0016] Optionally, when the non-performing assets belong to the company, the collection and disposal strategies include at least one of the following: self-collection, loss of contact repair, civil litigation, mediation, arbitration, application for enforcement of notarized debt instruments, application for realization of security rights, application for enforcement, debt restructuring, guarantor release strategy, holding shareholders accountable, project company management, partial debt reduction, installment repayment, coordinated transfer of disposal rights, debt transfer, guidance on repairing defects in private sales, guidance on repairing defects in malicious leasing, and recommendation of debt assets;

[0017] When non-performing assets belong to individuals with collateral or pledges, the collection and disposal strategies include at least one of the following: self-collection, restoration of lost contact, civil litigation, mediation, arbitration, application for enforcement of notarized debt instruments, application for realization of security rights, application for enforcement, debt restructuring, guarantor release strategy, partial debt reduction, installment repayment, coordinated transfer of disposal rights, debt transfer, guidelines for repairing lease defects, guidelines for repairing occupancy defects, and recommendation of debt assets;

[0018] When non-performing assets belong to individuals without collateral, the collection and disposal strategies include at least one of the following: regular telephone collection, civil litigation, partial debt relief, installment repayment, loss of contact restoration, seizure, participation in distribution, collection negotiation, deduction, and exercise of subrogation rights.

[0019] Optionally, the task information of the task includes the task indicators for completing the task, the task personnel, and the task time nodes. The non-performing asset disposal strategy method further includes: responding to user input information and adjusting the multiple tasks and the task information of each task.

[0020] Optionally, the task time node corresponds to a sub-task in the task. When monitoring and recording the execution status of the task in real time, the non-performing asset disposal strategy method further includes: when the task time node is reached, determining whether the sub-task corresponding to the task time node has been completed; if not, issuing an early warning.

[0021] Secondly, this application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the non-performing asset disposal strategy method described in any one of the above.

[0022] Thirdly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the non-performing asset disposal strategy method described in any one of the above.

[0023] Fourthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the non-performing asset disposal strategy method described above.

[0024] According to the specific embodiments provided in this application, the following technical effects are disclosed:

[0025] This application provides a method and related apparatus for non-performing asset disposal strategies. Using the due diligence results of non-performing assets as input, a standardized strategy generation model is used to determine the collection and disposal strategy for the non-performing assets. The collection and disposal strategy refers to the method of collecting and disposing of the non-performing assets. The target collection and disposal strategy selected by the user from the collection and disposal strategies for non-performing assets is broken down into multiple tasks. For each task, the execution status is monitored and recorded in real time until the task is completed. This application can utilize the standardized strategy generation model to conduct in-depth data analysis of the due diligence results of non-performing assets, intelligently recommending the best collection and disposal strategy, eliminating reliance on manual judgment. The disposal is data-supported, has a clear strategic plan guidance, improves collection efficiency, and enables effective risk control. Attached Figure Description

[0026] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0027] Figure 1 This is an application environment diagram for a non-performing asset disposal strategy method provided in Embodiment 1 of this application.

[0028] Figure 2 This is a flowchart illustrating a non-performing asset disposal strategy method provided in Embodiment 1 of this application.

[0029] Figure 3 This is a schematic diagram of the structure of a computer device provided in Embodiment 2 of this application. Detailed Implementation

[0030] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0031] Example 1

[0032] The non-performing asset disposal strategy and method provided in this application embodiment can be applied to, for example... Figure 1The application environment shown depicts a scenario where the terminal communicates with the server via a network. A data storage system stores the data the server needs to process. This system can be set up independently, integrated into the server, or located in the cloud or on another server. The terminal can send the due diligence results of the non-performing assets to the server. Upon receiving these results, the server uses them as input and employs a standardized strategy generation model to determine the collection and disposal strategy for the non-performing assets. This strategy represents the method of collecting and disposing of the assets. The server then breaks down the target collection and disposal strategy selected by the user from the available strategies into multiple tasks. For each task, the execution status is monitored and recorded in real time until the task is completed.

[0033] In addition, in some embodiments, the non-performing asset disposal strategy method can also be implemented by the server or the terminal alone. For example, the terminal can directly process the due diligence results of the non-performing assets to be processed, or the server can obtain the due diligence results of the non-performing assets to be processed from the data storage system and process the due diligence results of the non-performing assets to be processed.

[0034] The terminals can be, but are not limited to, various desktop computers, laptops, smartphones, tablets, IoT devices, and portable wearable devices. IoT devices can include smart speakers, smart TVs, smart air conditioners, and smart in-vehicle devices, while portable wearable devices can include smartwatches, smart bracelets, and head-mounted devices. Servers can be implemented using independent servers, server clusters composed of multiple servers, or cloud servers.

[0035] like Figure 2 As shown, a method for non-performing asset disposal is provided. This method is executed by computer equipment, specifically by a terminal or server alone, or by both a terminal and a server. In this embodiment, the method is applied to... Figure 1 Taking the server in the example, the following steps are included:

[0036] Step S1: Using the due diligence results of non-performing assets as input, a standardized strategy generation model is used to determine the collection and disposal strategy for non-performing assets; the collection and disposal strategy refers to the collection and disposal method of non-performing assets.

[0037] Step S2 involves breaking down the target collection and disposal strategy selected by the user from the non-performing asset collection and disposal strategies according to their needs, resulting in multiple tasks.

[0038] Step S3: For each task, monitor and record the execution status of the task in real time until the task is completed.

[0039] By implementing steps S1 to S3 above, this embodiment first conducts due diligence on non-performing assets during the recovery process. Due diligence involves investigating non-performing assets during acquisition, management, and disposal to obtain the due diligence results. Then, using the due diligence results as input, a standardized strategy generation model is used to determine the recovery and disposal strategy for non-performing assets. The recovery and disposal strategy refers to the method of recovering and disposing of non-performing assets. This allows the standardized strategy generation model to conduct in-depth data analysis on the due diligence results of non-performing assets, intelligently recommending the best recovery and disposal strategy. It no longer relies on manual judgment, and the disposal is supported by data, with a clear strategic plan orientation, improving recovery efficiency and enabling good risk control.

[0040] This embodiment introduces advanced data analysis technology to achieve in-depth analysis of the due diligence results of non-performing assets and automatically matches the optimal collection and disposal strategy accordingly. Specifically, based on the due diligence results, several collection and disposal strategies are obtained, which the user (who may be business personnel) can select. Based on the user's selected target collection and disposal strategy, the system automatically breaks down the task, assisting the user in quickly formulating an efficient collection and disposal plan. Specifically, this embodiment uses the due diligence results of non-performing assets as input and utilizes a standardized strategy generation model to determine the collection and disposal strategy for non-performing assets. The collection and disposal strategy refers to the method of collecting and disposing of non-performing assets.

[0041] The due diligence results are obtained based on the different types of non-performing assets, categorized as corporate and personal. For corporate non-performing assets (i.e., those belonging to companies), a tailored strategy model is used. This means that different collection and disposal strategies are developed for different corporate non-performing assets. It's understood that each corporate non-performing asset has significant differences in its debt, equity, and collateral information; the standardized strategy generation model will generate different collection and disposal strategies based on these differences. For personal non-performing assets (i.e., individual loans), a category-specific strategy model is used. This means that different personal non-performing assets are categorized based on debt information, repayment willingness, and whether there are collateral. It's understood that personal non-performing assets are numerous and share many commonalities; the standardized strategy generation model will generate different collection and disposal strategies based on different categories of non-performing assets. The standardized strategy generation model for non-performing asset disposal provided in this embodiment includes a strategy model for corporate clients with a tailored approach and a strategy model for individual clients with a tailored approach. The corresponding strategy model can be configured according to corporate or retail clients.

[0042] The standardized strategy generation model analyzes various related indicators (i.e., due diligence results) of specific non-performing assets according to established rules to obtain the most suitable and effective collection and disposal strategy. It is understandable that the various related indicators of specific non-performing assets are prerequisites for the collection and disposal strategy.

[0043] When non-performing assets belong to a company, the due diligence results include information on the debts, principal debtors, guarantors, and collateral. Debt information includes basic debt information and collection litigation status. Basic debt information includes the type of debt, debtor attributes, amount owed, completeness of debt documentation, and disputed clauses in the contract. Collection litigation status includes whether litigation conditions are met, whether the case has progressed to the litigation process, the litigation stage, and the litigation status. Principal debtor information includes repayment willingness, repayment ability, and equity structure. Equity structure includes whether it is a one-person limited liability company and whether the shareholder's capital contribution is not fully paid up. Guarantor information includes the type of guarantor, the legal nature of the guarantee, repayment willingness, and repayment ability. Collateral information includes the type of collateral and the validity of the collateral.

[0044] When non-performing assets belong to individuals, the due diligence results include information on the debtor, principal debtor, guarantor, and collateral. Debt information includes the completeness of debt documentation, contractual dispute clauses, number of overdue days, whether litigation has commenced, the litigation stage, and the litigation status. Principal debtor information includes their willingness and ability to repay. Guarantor information includes their willingness and ability to repay. Collateral information includes whether there is collateral, the type of collateral, mortgage details, and collateral registration information.

[0045] "One policy per client" refers to the collection and disposal strategy for corporate clients. When non-performing assets belong to a company, the collection and disposal strategy for non-performing assets includes, but is not limited to, self-collection, loss of contact repair, civil litigation, mediation, arbitration, application for enforcement of notarized debt instruments, application for realization of security rights, application for enforcement, debt restructuring, guarantor release strategy, holding shareholders accountable, project company management, partial debt reduction, installment repayment, coordinated transfer of disposal rights, debt transfer, guidance on repairing defects in private sales (passive), guidance on repairing defects in malicious leasing (passive), and recommendation of debt assets.

[0046] The "one-size-fits-one" approach refers to the collection and disposal strategy for individual loan customers. Different collection and disposal strategies are provided for different types of individual loan customers, categorized as either individuals with collateral or without collateral, as detailed below:

[0047] When non-performing assets belong to individuals with collateral (i.e., personal mortgage loans), the strategies for the collection and disposal of non-performing assets include, but are not limited to, self-collection, loss of contact restoration, civil litigation, mediation, arbitration, application for enforcement of notarized debt instruments, application for realization of security rights, application for enforcement, debt restructuring, guarantor release strategy, partial debt reduction, installment repayment, coordinated transfer of disposal rights, debt transfer, guidelines for repairing lease defects, guidelines for repairing occupancy defects, and promotion of debt assets.

[0048] When non-performing assets belong to individuals without collateral (i.e., personal loans and credit loans), the collection and disposal strategies for non-performing assets include, but are not limited to, at least one of the following: regular telephone collection, civil litigation, partial debt reduction, installment repayment, loss of contact restoration, seizure, participation in distribution, collection negotiation, deduction, and exercise of subrogation rights.

[0049] For non-performing corporate assets, based on structured due diligence results stored in the storage medium, the data is read into memory. A computer program (standardized strategy generation model) is then executed by the processor to match the optimal strategy, intelligently recommending a tailored collection and disposal strategy for each individual loan, thereby maximizing and maintaining asset value. For non-performing personal assets, based on structured due diligence results stored in the storage medium, the data is read into memory. A computer program is then executed by the processor to match the optimal strategy, intelligently recommending a tailored collection and disposal strategy for each type of loan, achieving more effective management and recovery of individual non-performing loans and improving asset recovery efficiency.

[0050] This embodiment provides three different standardized strategy generation models for corporate clients, personal mortgage loans, and personal credit loans. For corporate clients, strategy recommendations are made based on due diligence results such as the debtor's repayment ability, repayment willingness, contractual dispute clauses, type of collateral, validity of collateral, and litigation stage. For personal mortgage loans, strategy recommendations are made based on due diligence results such as the debtor's repayment ability, repayment willingness, contractual dispute clauses, type of collateral, and litigation stage. For personal credit loans, strategy recommendations are made based on due diligence results such as the debtor's repayment willingness and repayment ability.

[0051] Before using the due diligence results of non-performing assets as input and employing a standardized strategy generation model to determine the collection and disposal strategy for non-performing assets, the non-performing asset disposal strategy method in this embodiment further includes: acquiring historical data, which includes historical due diligence results and historical collection and disposal strategies for non-performing assets; and using the historical data to train the initial strategy generation model to obtain a standardized strategy generation model.

[0052] This embodiment also incorporates a strategy accumulation mechanism. By systematically collecting and organizing the disposal methods and results in historical cases, it forms case data (i.e., historical due diligence results) and tags (i.e., historical collection and disposal strategies). The case data and tags are then accumulated and continuously fed back into the standardized strategy generation model to achieve precise strategy recommendations. This allows the standardized strategy generation model to continuously enrich and improve its own strategy library, providing valuable reference for subsequent non-performing asset disposal.

[0053] This embodiment features an autonomous optimization and iteration function. Leveraging a historical data analysis feedback mechanism, it continuously iterates and optimizes the standardized strategy generation model. Specifically, based on a large amount of historical data related to non-performing asset disposal, advanced algorithms such as deep learning are used to identify key features (e.g., the nature of the debt, due diligence results, debtor profiles, and the adopted collection and disposal strategies). An initial strategy generation model is constructed based on these extracted key features and trained using machine learning algorithms. This enables the model to predict the output result (i.e., the collection and disposal strategy) based on the input conditions (i.e., due diligence results), resulting in a standardized strategy generation model. During the operation of the standardized strategy generation model, new data is continuously collected and compared with previous prediction results. Based on this, the model parameters are automatically adjusted to achieve self-optimization. Through in-depth mining and analysis of massive amounts of historical data, the model can continuously identify and correct its shortcomings, thereby gradually improving the accuracy and efficiency of non-performing asset disposal.

[0054] The due diligence results for non-performing assets provided above are comprehensive. However, in practical applications, partial due diligence results can be input into the standardized strategy generation model. In this case, a partial due diligence result corresponds to a real-world scenario. When this partial due diligence result is input into the standardized strategy generation model, multiple output results may be generated. Different non-performing assets, after being calculated by the standardized strategy generation model, may produce multiple different recovery and disposal strategies. Simple real-world scenarios can use a weighted standard value method for strategy recommendation. Complex real-world scenarios, due to their higher complexity, can be recommended by analyzing a large number of historical cases and calculating similarity. Therefore, in this embodiment, the standardized strategy generation model uses a weighted calculation or similarity calculation method to determine the recovery and disposal strategy for non-performing assets.

[0055] For example, the model input condition is the litigation situation, which includes whether there is a contractual dispute clause, whether the conditions for litigation are met, whether the litigation process has been initiated for a specific asset, the litigation stage, and the litigation status. If the conditions for litigation are met, the model recommends advancing the litigation process to exert pressure. If the litigation stage has already begun, the model analyzes and determines the current litigation stage and status. Litigation stages include first instance, second instance, retrial, and enforcement; litigation status includes filing, hearing, judgment, effective, suspension of litigation, dismissal of litigation, enforcement in progress, enforcement settlement, objection to enforcement, enforcement review, termination of this enforcement, resumption of enforcement, and completion of enforcement. Based on different litigation stages and statuses, the model recommends corresponding strategies.

[0056] For example, the model input conditions include debt information, guarantor information, and collateral information. The model determines whether the debt has defects. Defects can be understood as follows: if the litigation status is pending and no judgment has been reached, the following conditions can be considered as defects: the litigation status associated with the debt has expired; the guarantor has valid guarantee; the collateral has not been registered; the validity of the collateral is defective, etc. If the above conditions are met, the model determines that the debt has defects and recommends actively negotiating and mediating with the debtor to rectify the defects. If it is a corporate debt, the model recommends actively negotiating and restructuring with the debtor to rectify the defects.

[0057] Below is an example of weighted calculation and similarity calculation:

[0058] (1) Weighted calculation

[0059] The model's input conditions are the principal debtor's willingness and ability to repay. These input conditions are obtained from the principal debtor information in the preconditions. C1 represents repayment willingness, with C1=1 indicating willingness and C1=0 indicating no willingness. C2 represents repayment ability, with C2=1 indicating ability and C2=0 indicating inability. For a specific real-world scenario where C1=1 and C2=0, the corresponding main output strategy is a debt reduction strategy, potentially including three collection and disposal strategies: debt reduction, interest reduction, and adding an installment repayment agreement. Understandably, different users will have different preferences for these three collection and disposal strategies. Therefore, customizable weight parameters are set for these three strategies: W1 for debt reduction, W2 for interest reduction, and W3 for adding an installment repayment agreement. These weight parameters can provide a slight bias in the selection of the collection and disposal strategy. The standardized strategy generation model reads the debt information from the preconditions, with the following parameters: P is the outstanding principal, and I is the outstanding interest. The priority can then be adjusted based on the ratio of outstanding principal to outstanding interest, with the outstanding principal representing the proportion of the total debt. The percentage of interest owed to total debt Further deduction leads to the standard value of debt relief: S1 = W1 × R PThe standard value for interest reduction is S2 = W2 × R I Increase the standard value of the installment repayment agreement S3 = W3 × (1 - R) P -R I Understandably, when the proportions of outstanding principal and outstanding interest are not significant, it is more appropriate to use the standard value of S3 for additional installment payments. Therefore, the final strategy is as follows:

[0060]

[0061] The formulas for the above debt reduction schemes can be understood as follows: Debt reduction is more suitable when the outstanding principal accounts for a higher proportion of the total debt, because reducing this portion has a greater impact on the total debt. Interest reduction is more suitable when the outstanding interest accounts for a higher proportion of the total debt, because reducing this portion can significantly reduce the burden. When neither proportion is prominent, installment payments may be a more flexible option. Based on the "one household, one policy" and "one category, one policy" approaches, the priority among the three is determined by adjusting the weighting ratios. It should be noted that the standardized strategy generation model's priority judgments for the three debt reduction strategies are only recommendations to provide more ideas for choosing a debt reduction scheme.

[0062] (2) Similarity calculation

[0063] Similarity calculation requires the integration of historical cases. By analyzing these cases, the scenarios within them are parameterized. This parameterization can be understood as the creditor scoring each condition. For example, conditions such as debtor attributes, outstanding amount, repayment ability, and willingness to repay can all be parameterized. For debtor attributes, 1 represents a company, and 2 represents an individual. The outstanding amount can be parameterized by combining attributes from different dimensions: the proportional dimension is the proportion of the outstanding amount to the total loan amount, and the numerical dimension is the range of values ​​for the outstanding amount. For repayment ability, 1 indicates the ability to repay, and 0 indicates the inability to repay. For willingness to repay, 1 indicates the willingness to repay, and 0 indicates the unwillingness to repay, and so on. It's important to understand that the parameterization of any condition does not require consideration of the resulting parameterization; simply generating the corresponding parameters according to a unified rule is sufficient to serve as the evaluation standard.

[0064] The strategy recommendation criteria are set as follows: C1 is repayment willingness, C2 is repayment ability, C3 is debtor attributes, and C4 is the proportion of the outstanding amount. The condition set is I = {C1, C2, C3, C4}. If the score item Ru of the existing historical successfully recovered debt u is [1, 1, 1, 0.5], and the score item Rv of the debt v to be recommended is [1, 0, 1, 0.2], the similarity between debt u and debt v is calculated according to the cosine similarity formula, as follows:

[0065]

[0066] Where sim(u,v) represents the similarity between claim u and claim v; R u,i Let R be the value of the i-th condition of the claim u; v,i Let be the value of the i-th condition of claim v.

[0067] The calculation process for the dot product (numerator) is as follows:

[0068] ∑ i∈I R u,i ·R v,i =1×1+1×0+1×1+0.5×0.2=2.1.

[0069] The calculation process for the norm (first part of the denominator) of the score vector of claim u is as follows:

[0070]

[0071] The calculation process for the norm of the score vector of claim v (the second part of the denominator) is as follows:

[0072]

[0073] The cosine similarity results of claims v and u are as follows:

[0074]

[0075] Calculate the similarity between claim v and all historical claims u, select the historical claims u with the highest similarity ranking (sorted from high to low) as the result set, and sort the different output results in the result set to achieve the effect of recommending collection and disposal strategies.

[0076] This embodiment allows for the configuration of standardized strategy generation models, supports configuration based on customer type, allows the saving of multiple standardized strategy generation models, and enables the activation of adapted standardized strategy generation models according to different business scenarios and customer types.

[0077] Below are recommended examples of strategies for recovering and disposing of non-performing assets, both for public and private entities:

[0078] For non-performing assets of corporate clients, for example: Client A conducts due diligence and obtains information on collection and litigation, with the constraints being that no lawsuit has been filed and there are no contractual dispute clauses. The computer system reads the rules and settings of the standardized strategy generation model and concludes that the conditions for filing a lawsuit are met. Therefore, the collection and disposal strategy recommended to the corporate account manager or handler is civil litigation.

[0079] For non-performing assets held by private individuals, for example, Client B, through due diligence, has a large number of private assets due to its retail business, and these assets often share common characteristics. The standardized strategy generation model analyzes different classifications to generate corresponding collection and disposal strategies. At this point, the computer system identifies the due diligence results for Client B and recognizes repairable defects in the borrower's assets. Taking defects in private sales as an example, the standardized strategy generation model provides guidance on repairing these defects, breaking down the task into rejecting third-party objections to enforcement and rejecting lawsuits against third-party objections to enforcement. Correspondingly, rejecting a third-party objection to enforcement requires obtaining a court ruling on the objection review as the enforcement indicator; rejecting a lawsuit against a third-party objection to enforcement requires obtaining a legally effective judgment in the court's enforcement objection lawsuit.

[0080] The standardized strategy generation model in this embodiment can simultaneously provide multiple collection and disposal strategies. The computer system obtains the scoring and valuation results from the storage medium by calling the interface, and intelligently analyzes the priority of different collection and disposal strategies for different businesses through predetermined rules, and provides semi-automated recommendation guidance during the strategy execution process.

[0081] Based on the obtained collection and disposal strategy, the recommended target collection and disposal strategy is further refined into a series of structured task nodes. Each task node corresponds to a collection process, and each task node provides task indicators to guide frontline personnel in completing the relevant tasks. A rigorous tracking mechanism is established to ensure that the execution status of each task node is monitored and recorded in real time. That is, in this embodiment, after obtaining the collection and disposal strategy, it is further broken down into multiple tasks. For each task, the execution status is monitored and recorded in real time until the task is completed. When all tasks are completed, the non-performing asset collection process ends.

[0082] This embodiment supports users in flexibly adjusting collection and disposal strategies. After calculation, the model generates collection and disposal strategies that suit the debtor's situation. Faced with a complex and ever-changing market environment, users can modify and optimize the initially recommended collection and disposal strategies as necessary based on actual conditions to adapt to new market conditions and further improve disposal effectiveness. It supports the management of strategy details, including disposal tasks, disposal time nodes, and disposal personnel configuration, enabling precise management of collection and disposal strategies. For example, management can customize collection task indicators, rationally allocate collection resources, and promote the management of key clients. In this embodiment, task information includes task indicators, personnel, and time nodes. The non-performing asset disposal strategy method in this embodiment also includes: responding to user input information and adjusting the multiple tasks and the task information of each task.

[0083] This embodiment supports dynamic adjustment of collection and disposal strategies. As the external environment changes or new information is acquired, the collection and disposal strategies can be updated accordingly to achieve continuous optimization of the strategies and maintain the accuracy of matching collection and disposal strategies.

[0084] To ensure the smooth progress of the disposal process, this embodiment designs an early warning mechanism to monitor and remind users of key time points. Specifically, it identifies and categorizes key time points that may occur during the collection process. These key time points may include legal proceedings deadlines, debt restructuring negotiation periods, and asset auction preparation time. When a key time point is reached, but the actual execution of the task node deviates from the preset standard, a warning signal will be automatically triggered, reminding relevant personnel to intervene in a timely manner and take corrective measures, thereby effectively avoiding potential risks caused by execution deviations. In addition, if changes in asset value occur during continuous monitoring that affect the collection task, relevant early warning reminders will be generated to help improve the timeliness of asset disposal. That is, in this embodiment, a task time node corresponds to a sub-task in the task. While monitoring and recording the execution status of the task in real time, the non-performing asset disposal strategy method of this embodiment also includes: when a task time node is reached, determining whether the sub-task corresponding to the task time node has been completed; if not, issuing an early warning.

[0085] The non-performing asset disposal strategy and method provided in this embodiment includes functions such as standardized strategy generation, task planning, execution monitoring, early warning prompts, strategy adjustment, strategy experience accumulation, and data feedback for continuous optimization. It supports automatic matching of suitable strategies based on due diligence results, assists business personnel in disposal decisions, reduces human strategy inappropriateness or omissions, and can accumulate historical strategy selection data for further scientific recommendations, so as to comprehensively improve the decision-making efficiency and execution capabilities of financial institutions in the field of non-performing asset management.

[0086] This embodiment further constructs a data security strategy for the standardized strategy generation model. It is understood that data is extremely sensitive during the data collection process. In order to ensure the security and compliance of data collection during the preliminary conditions collection process, the following solutions are adopted, including but not limited to:

[0087] (1) Anonymization and desensitization: When collecting pre-debt data, ensure that the data is anonymized or desensitized to protect privacy data. For example, remove or replace parts of the information that can directly obtain sensitive information.

[0088] (2) Data storage encryption: Sensitive data is encrypted and stored using national cryptographic algorithms to ensure data security in the storage medium. For example, asymmetric encryption SM2 is used to encrypt and store data. It is an elliptic curve cryptography (ECC) based cipher. The public key is used to encrypt and store the data in the storage medium. When the data is needed, the private key is used to decrypt it, and no trace is left in the intermediate process.

[0089] (3) Strictly control access permissions during access to prevent horizontal and vertical unauthorized data access and ensure that only authorized personnel can access the data.

[0090] (4) Network environment isolation: The construction of the standardized strategy generation model is carried out entirely in the local area network, and the data in the model only provides output items without sensitive information. The calculation process does not throw out any access path.

[0091] (5) Data communication security protocol: HTTPS (Hypertext Transfer Protocol Secure) is used for data transmission to ensure confidentiality and integrity during data transmission.

[0092] This embodiment provides a standardized strategy generation model for non-performing asset disposal recommendations, including a corporate client-specific strategy model and a private client-category-specific strategy model. The corporate client-specific strategy model supports combined recommendations and multi-method collection through different intelligent recommendation strategies for different types of non-performing assets. The private client-category-specific strategy model formulates the same strategy for the same type of business by recommending different types of intelligent recommendation strategies to improve collection efficiency. Based on the recommended strategies, disposal plans are arranged, plans are automatically generated, and plan adjustments are supported. The disposal process is automatically monitored and warned, realizing full-chain automated management from strategy recommendation to task execution. Utilizing due diligence results, collection and disposal strategies that are highly matched with the debt situation are intelligently pushed to promote the management of key clients. By introducing innovative mechanisms such as early warning, adjustment, data retention, and optimization, the collection process is promoted to be standardized, digitalized, and intelligent. Through appropriate collection and disposal strategy recommendations, the goal of maximizing and maintaining asset value can be achieved. This can effectively solve the problems of existing non-performing asset disposal systems lacking clear strategy guidance, resulting in low efficiency and insufficient risk control. The asset disposal solutions generated by the standardized strategy model connect upstream and downstream information in asset disposal, establish an asset management ecosystem, link due diligence information with asset disposal, track and optimize disposal solutions in real time, rationally plan and allocate collection resources, and maximize the advantages of various personnel / organizations. Users can rationally prioritize asset disposal based on the model analysis results, manage and promote key clients, maximize the utilization rate of collection resources, and reduce collection costs.

[0093] Compared to traditional non-performing asset (NPA) disposal systems, the NPA disposal strategy method provided in this embodiment supports automatic matching of suitable strategies based on due diligence results, assisting business personnel in making disposal decisions, reducing human error or omissions in strategy selection, and accumulating historical strategy selection data for further scientific recommendations. By recommending appropriate collection and disposal strategies, the goal of maximizing and maintaining asset value is achieved, solving the problems of existing NPA disposal systems lacking clear strategic guidance, resulting in low efficiency and insufficient risk control.

[0094] Example 2

[0095] In one exemplary embodiment, a computer device is provided, which may be a server or a terminal, and its internal structure diagram may be as follows. Figure 3 As shown, this computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database stores data to be processed. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communicating with external terminals via a network connection. When executed by the processor, the computer program implements a non-performing asset disposal strategy method.

[0096] Those skilled in the art will understand that Figure 3 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0097] In one exemplary embodiment, a computer device is also provided, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, the processor executing the computer program to implement the non-performing asset disposal strategy method described in Embodiment 1.

[0098] Example 3

[0099] This application provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the non-performing asset disposal strategy and method described in Embodiment 1.

[0100] Example 4

[0101] This application provides a computer program product, including a computer program that, when executed by a processor, implements the non-performing asset disposal strategy and method described in Embodiment 1.

[0102] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0103] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0104] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A strategy and method for disposing of non-performing assets, characterized in that, The strategies and methods for disposing of non-performing assets include: Using the due diligence results of non-performing assets as input, a standardized strategy generation model is used to determine the collection and disposal strategy for these assets. This standardized strategy generation model includes a "one-policy-per-corporation" model for corporate clients and a "one-policy-per-category" model for individual clients. "Corporate clients" refers to non-performing assets belonging to companies, and "individual clients" refers to non-performing assets belonging to individuals. The appropriate standardized strategy generation model is activated based on different client types. During the operation of the standardized strategy generation model, the model parameters are automatically adjusted based on newly collected historical due diligence results and historical collection and disposal strategies to optimize the standardized strategy generation model. The collection and disposal strategy refers to the method of collecting and disposing of non-performing assets. The target collection and disposal strategy selected by the user from the collection and disposal strategies for non-performing assets is broken down according to the user's needs, and a collection and disposal plan is formulated to obtain multiple tasks; each task corresponds to a collection process. For each of the tasks, the execution status of the task is monitored and recorded in real time until the task is completed; When the non-performing assets belong to a company, the due diligence results include information on the non-performing assets' claims, principal debtor information, guarantor information, and collateral information. Claim information includes basic claim information and collection litigation status. Basic claim information includes the type of claim, debtor attributes, amount owed, completeness of claim documentation, and contractual dispute clauses. Collection litigation status includes whether litigation conditions are met, whether litigation has commenced, the litigation stage, and the litigation status. Principal debtor information includes repayment willingness, repayment ability, and equity structure. Equity structure includes whether it is a one-person limited liability company and whether the shareholder's capital contribution is not fully paid up. Guarantor information includes the type of guarantor, the legal nature of the guarantee, repayment willingness, and repayment ability. Collateral information includes the type of collateral and the validity of the collateral. When non-performing assets belong to individuals, the due diligence results include information on the debtor's claims, the principal debtor's information, the guarantor's information, and the collateral information. The debtor's claims information includes the completeness of the debt documentation, the terms of any disputed contracts, the number of overdue days, whether litigation has commenced, the stage of litigation, and the status of the litigation. The principal debtor's information includes their willingness and ability to repay. The guarantor's information includes their willingness and ability to repay. The collateral information includes whether there is collateral, the type of collateral, the details of the mortgage, and the registration status of the collateral. When non-performing assets belong to the company, the collection and disposal strategies include at least one of the following: self-collection, restoration of lost contact, civil litigation, mediation, arbitration, application for enforcement of notarized debt instruments, application for realization of security rights, application for enforcement, debt restructuring, guarantor release strategy, holding shareholders accountable, project company management, partial debt reduction, installment repayment, coordinated transfer of disposal rights, debt transfer, guidance on repairing defects in private sales, guidance on repairing defects in malicious leasing, and promotion of debt assets; When non-performing assets belong to individuals with collateral or pledges, the collection and disposal strategies include at least one of the following: self-collection, restoration of lost contact, civil litigation, mediation, arbitration, application for enforcement of notarized debt instruments, application for realization of security rights, application for enforcement, debt restructuring, guarantor release strategy, partial debt reduction, installment repayment, coordinated transfer of disposal rights, debt transfer, guidelines for repairing lease defects, guidelines for repairing occupancy defects, and recommendation of debt assets; When non-performing assets belong to individuals without collateral or pledges, the collection and disposal strategies include at least one of the following: regular telephone collection, civil litigation, partial debt relief, installment repayment, loss of contact restoration, seizure, participation in distribution, collection negotiation, deduction, and exercise of subrogation rights; The task information of the task includes the task indicators for completing the task, the task personnel and the task time node. The task time node corresponds to a sub-task in the task. When the execution status of the task is monitored and recorded in real time, the non-performing asset disposal strategy method further includes: when the task time node is reached, determining whether the sub-task corresponding to the task time node has been completed. If not, an early warning is issued. As the external environment changes or new information becomes available, the collection and disposal strategies are updated accordingly.

2. The non-performing asset disposal strategy and method according to claim 1, characterized in that, Before using the due diligence results of non-performing assets as input and employing a standardized strategy generation model to determine the collection and disposal strategy for non-performing assets, the non-performing asset disposal strategy method further includes: Acquire historical data; the historical data includes historical due diligence results and historical collection and disposal strategies for non-performing assets. The initial policy generation model is trained using the historical data to obtain a standardized policy generation model.

3. The non-performing asset disposal strategy and method according to claim 1, characterized in that, The standardized strategy generation model uses weighted calculation or similarity calculation to determine the collection and disposal strategy for non-performing assets.

4. The non-performing asset disposal strategy and method according to claim 1, characterized in that, The non-performing asset disposal strategy method further includes: responding to user input information and adjusting the multiple tasks and the task information of each task.

5. A computer device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the non-performing asset disposal strategy method according to any one of claims 1-4.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the non-performing asset disposal strategy method as described in any one of claims 1-4.

7. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the non-performing asset disposal strategy method as described in any one of claims 1-4.

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