Task execution method

Abstract

The invention provides a task execution method, which comprises the following steps: in response to a received task request sent by a first client, executing a target task matched with the task request, so as to determine asset factors of a target object of a target service of a financial institution to be executed in a plurality of historical periods according to service data; according to each asset factor, determining a fluctuation factor of the target object in a specified period; determining a risk compensation base point of the target object in a specified period according to the fluctuation factor; based on the risk compensation base point, performing risk pricing on the target object to obtain a risk pricing result of the target object executing the target business; and generating an execution result of the target task according to the risk pricing result, and sending the execution result to the first client for visual display, thereby improving the task execution efficiency and accuracy, improving the accuracy of the risk pricing result, and helping a financial institution to improve the business decision efficiency and the overall risk management level.

Description

Technical Field

[0001] The present disclosure relates to the technical field of risk management, and in particular to a task execution method. Background Art

[0002] With the rapid development of the financial industry, the importance of financial risk management has become increasingly prominent. Implementing accurate risk pricing for target objects of financial services such as loans can not only help financial institutions effectively identify and manage potential credit risks, but also optimize resource allocation, improve capital utilization efficiency, and enhance market competitiveness.

[0003] In the related art, when financial institutions conduct risk pricing for target objects, they perform tasks manually to subjectively judge the risk tolerance of the target objects, and manually perform risk pricing based on the judgment results of risk tolerance, resulting in low task execution efficiency and poor accuracy. Summary of the invention

[0004] The present disclosure provides a task execution method to solve one of the technical problems in the related art at least to a certain extent. The technical solution of the present disclosure is as follows:

[0005] According to a first aspect of an embodiment of the present disclosure, a task execution method is provided, which is applied to a server, and includes: in response to receiving a task request sent by a first client, determining a target task matching the task request, and executing the target task, so as to determine the asset factors of a target object of a target business of a financial institution to be executed in multiple historical periods according to business data in a business data table associated with the task purpose of the target task; determining a volatility factor of the target object within a specified period according to each of the asset factors; determining a risk compensation basis point of the target object within the specified period according to the volatility factor; performing risk pricing on the target object based on the risk compensation basis point to obtain a risk pricing result of the target object executing the target business; generating an execution result of the target task according to the risk pricing result, and sending the execution result to the first client for visual display.

[0006] According to a second aspect of an embodiment of the present disclosure, there is provided a task execution device, which is applied to a server, and includes: an execution module, which is used to determine a target task matching the task request in response to receiving a task request sent by a first client, and execute the target task to determine the asset factors of a target object of a target business of a financial institution to be executed in multiple historical periods according to business data in a business data table associated with the task purpose of the target task; a first determination module, which is used to determine the volatility factor of the target object within a specified period according to each of the asset factors; a second determination module, which is used to determine the risk compensation basis point of the target object within the specified period according to the volatility factor; a pricing module, which is used to perform risk pricing on the target object based on the risk compensation basis point to obtain a risk pricing result of the target object executing the target business; a generation module, which is used to generate the execution result of the target task according to the risk pricing result, and send the execution result to the first client for visual display.

[0007] According to a third aspect of an embodiment of the present disclosure, an electronic device is provided, comprising: a processor; and a memory for storing instructions executable by the processor; wherein the processor is configured to execute the instructions to implement the task execution method as described in the embodiment of the first aspect of the present disclosure.

[0008] According to a fourth aspect of an embodiment of the present disclosure, a computer-readable storage medium is provided. When instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device is enabled to execute the task execution method as described in the embodiment of the first aspect of the present disclosure.

[0009] According to a fifth aspect of an embodiment of the present disclosure, a computer program product is provided, including: a computer program, which, when executed by a processor, implements the task execution method as described in the embodiment of the first aspect of the present disclosure.

[0010] The technical solution provided by the embodiments of the present disclosure brings at least the following beneficial effects:

[0011] In the present technical scheme, by responding to a task request received from a first client, a target task matching the task request is determined, and the target task is executed, so as to determine the asset factors of the target object of the target business of the financial institution to be executed in multiple historical periods according to the business data in the business data table associated with the task purpose of the target task; according to each asset factor, the volatility factor of the target object within a specified period is determined; according to the volatility factor, the risk compensation basis point of the target object within the specified period is determined; based on the risk compensation basis point, the risk pricing of the target object is performed to obtain the risk pricing result of the target object executing the target business; according to the risk pricing result, the execution result of the target task is generated, and the execution result is sent to the first client for visual display, thereby, upon receiving the task request sent by the client, the target task is triggered. The execution of the task is to price the risk of the target object, which reduces the intermediate links and manual intervention, improves the accuracy and timeliness of the risk pricing of the target object, and after generating the execution result of the target task, sends the execution result to the first client for visual display, realizes the intuitive display of complex data and analysis results, and the user can intuitively understand the distribution and trend of the data, quickly discover key information and potential problems, and improves decision-making efficiency; among them, when executing the target task, the asset factor is determined based on the total assets sent by the second client and written into the data table in the corresponding historical period, which ensures the timeliness and accuracy of the data. The server performs subsequent analysis and decision-making based on these accurate data, avoiding the risks caused by data delays or errors, while simplifying the process of data collection and processing and improving work efficiency.

[0012] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The drawings herein are incorporated into and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the description are used to explain the principles of the present disclosure, and do not constitute improper limitations on the present disclosure.

[0014] Figure 1 is a flowchart of a task execution method shown in the first embodiment of the present disclosure;

[0015] Figure 2 is a flowchart of a task execution method shown in the second embodiment of the present disclosure;

[0016] Figure 3 is a flowchart of a task execution method shown in the third embodiment of the present disclosure;

[0017] Figure 4 is a flowchart of a task execution method shown in the fourth embodiment of the present disclosure;

[0018] Figure 5 is a structural diagram of a task execution device shown in the fifth embodiment of the present disclosure;

[0019] Figure 6 It is a schematic structural diagram of an electronic device shown in an exemplary embodiment of the present disclosure. DETAILED DESCRIPTION

[0020] In order to enable ordinary persons in the art to better understand the technical solutions of the present disclosure, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the accompanying drawings.

[0021] It should be noted that the terms "first", "second", etc. in the specification and claims of the present disclosure and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present disclosure described herein can be implemented in an order other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0022] It should be noted that in the technical solution of the present disclosure, the collection, storage, use, processing, transmission, provision and disclosure of user personal information are all carried out with the user's consent, and are in compliance with the relevant laws and regulations and do not violate public order and good morals.

[0023] It is important to understand that enterprise risk pricing is a complex process that requires comprehensive consideration of various factors. Different financial institutions may adopt different risk pricing strategies to adapt to their own business characteristics and market environment, not only considering cost factors, but also risks, market competition conditions, target profits and other factors. The risk pricing methods commonly used by general financial institutions include the following three: cost-plus pricing, risk-plus pricing and customer segmentation pricing.

[0024] However, the above risk pricing methods each have their own advantages and limitations. For example, the cost-plus pricing method is too simplistic and ignores market dynamics and competition factors, resulting in a lack of competitiveness in risk pricing. It does not fully consider the differences in credit risks among different financing companies and ignores the relationship between market demand and supply, resulting in insufficient attractiveness of loan products. The risk-plus pricing method is a challenge for accurately assessing the risk level of each financing company, which may result in a risk premium that is too high or too low, and is not sensitive enough to changes in market interest rates, resulting in pricing lagging behind market changes. The customer segmentation pricing method requires a lot of data analysis and technical support, which may be difficult to implement and may not treat all customers fairly.

[0025] Therefore, in view of the above problems, the present disclosure proposes a task execution method.

[0026] The task execution method of the embodiment of the present disclosure is described below with reference to the accompanying drawings.

[0027] Figure 1 It is a flowchart of the task execution method shown in the first embodiment of the present disclosure.

[0028] like Figure 1 As shown, the task execution method includes the following steps:

[0029] Step 101, in response to receiving a task request sent by the first client, determining a target task that matches the task request, and executing the target task to determine the asset factors of the target object of the target business of the financial institution to be executed in multiple historical periods based on the business data in the business data table associated with the task purpose of the target task.

[0030] In order to improve the efficiency and accuracy of risk pricing, as a possible implementation method, by executing the target task, the asset factors of multiple historical periods can be automatically collected, so as to fully understand the historical asset situation of the target object and more accurately assess the risk situation of the target object.

[0031] In the disclosed embodiment, upon receiving a task request sent by a first client, the task request is parsed to obtain key information in the task request, wherein the key information includes: task type, target object, historical period, etc. According to the key information, a target task matching the task request is determined, and the target task is executed to select business data in a business data table associated with the task purpose of the target task, and based on the business data, the asset factor of the target object in multiple historical periods is determined. Among them, the target object is an object (such as an enterprise) that handles a target business in a financial institution, and the target business is, for example, a loan business, an investment business, etc. The task purpose of the target task includes: approving the business application of the target object or performing risk pricing on the target object, etc. The business data may include: the asset value, long-term liabilities and short-term liabilities of the target object, etc.; the asset factor includes: asset yield rate.

[0032] Step 102: Determine the volatility factor of the target object within a specified period based on each asset factor.

[0033] In order to improve the accuracy of risk pricing, as a possible implementation method, risk pricing is performed based on the asset changes and potential risks of the target object within a specified period.

[0034] In the disclosed embodiment, based on the asset factors of multiple historical periods, the volatility factor of the target object in a specified period is calculated. The volatility factor can accurately reflect the asset changes and potential risks of the target object in the specified period. For example, the volatility factor includes: asset volatility.

[0035] Step 103: Determine the risk compensation base point of the target object within a specified period according to the volatility factor.

[0036] It is important to understand that the risk compensation basis point reflects the actual risk level of the target object. Financial institutions can reasonably adjust business interest rates (such as loan interest rates) or other financial parameters based on the risk compensation basis point to ensure a balance between risk and return.

[0037] Therefore, in order to improve risk management capabilities, in the embodiment of the present disclosure, the risk compensation basis points of the target object within a specified period are calculated based on the volatility factor, and risk pricing is performed based on the risk compensation basis points.

[0038] Step 104, based on the risk compensation basis point, risk pricing is performed on the target object to obtain a risk pricing result of the target object executing the target business.

[0039] In order to further improve the accuracy of risk pricing, as a possible implementation method, factors such as the capital cost and operating cost of financial institutions, market interest rate levels, and the risks of target objects should be fully considered to conduct risk pricing for the target objects.

[0040] In the disclosed embodiment, the base interest rate of the financial institution and the risk-free interest rate in a specified period are obtained; and the risk pricing result of the target object executing the target business is determined based on the sum of the base interest rate, the risk-free interest rate and the risk compensation basis point.

[0041] That is to say, the base interest rate may vary depending on the type of financial institution, market positioning, business strategy and other factors. In a specified period, the risk-free interest rate may change due to market changes, policy adjustments and other factors. Therefore, it is necessary to obtain and update the risk-free interest rate data regularly. The risk compensation basis point refers to the additional amount or percentage added to the price or interest rate in order to compensate for the possible losses caused by taking risks. By adding the base interest rate, risk-free interest rate and risk compensation basis points, the risk pricing result of the target object executing the target business can be obtained.

[0042] Step 105: Generate the execution result of the target task according to the risk pricing result, and send the execution result to the first client for visual display.

[0043] In order for financial institutions to effectively execute target businesses, as a possible implementation method, the risk pricing results are converted into specific business execution or output results. In order to intuitively display the execution results of the target tasks to improve decision-making efficiency, in the disclosed embodiment, the execution results are sent to the first client for visual display.

[0044] As an example, when the purpose of the target task is to calculate the risk pricing of the target object, the risk pricing result is directly used as the execution result of the target task.

[0045] As another example, when the purpose of the target task is to approve the business application of the target object, the execution result of the target task is determined based on the difference between the risk pricing result and the set risk pricing threshold.

[0046] For example, if the risk pricing result is within an acceptable set threshold range, the financial institution may decide to approve the target object's business application and determine the corresponding interest rate, fees or conditions based on the risk pricing result. For another example, if the risk pricing result is not within the set threshold range, the financial institution may reject the business application, require additional risk mitigation measures or re-evaluate the target object's risk status.

[0047] In summary, when the task request sent by the first client is received, the execution of the target task is triggered to perform risk pricing on the target object, which reduces intermediate links and manual intervention and improves the accuracy and timeliness of the risk pricing of the target object. When performing risk pricing on the target object, the asset factor is determined based on the total assets sent by the second client and written into the data table within the corresponding historical period, ensuring the timeliness and accuracy of the data. The server calculates the volatility factor based on the asset factor, and accurately reflects the asset changes and potential risks of the target object within the specified period; the target object is risk priced according to the risk compensation basis point determined by the volatility factor, and the execution result of the automatic target task is generated according to the risk pricing result, which reduces manual intervention and decision-making time, improves the efficiency and accuracy of task execution, and thus improves the accuracy of the risk pricing result. The execution result is sent to the first client for visual display, which realizes the intuitive display of complex data and analysis results. Users can intuitively understand the distribution and trends of the data, quickly discover key information and potential problems, and improve decision-making efficiency.

[0048] In order to clearly illustrate how to determine the risk compensation base point of the target object within a specified period according to the fluctuation factor in the above embodiment, the present disclosure proposes another task execution method.

[0049] Figure 2 It is a flowchart of a task execution method shown in the second embodiment of the present disclosure.

[0050] like Figure 2 As shown, the task execution method includes the following steps:

[0051] Step 201, in response to receiving a task request sent by the first client, determining a target task that matches the task request, and executing the target task to determine the asset factors of the target object of the target business of the financial institution to be executed in multiple historical periods based on the business data in the business data table associated with the task purpose of the target task.

[0052] Step 202, determining the volatility factor of the target object within a specified period based on each asset factor.

[0053] Step 203: Determine multiple risk adjustment factors of the target object within the specified period according to the volatility factor and the specified period.

[0054] In order to improve the accuracy of risk pricing, as a possible implementation method, when calculating the risk compensation basis point, the multiple risk characteristics of the target object are combined, that is, multiple risk adjustment factors of the target object within a specified period are considered for calculation.

[0055] In the embodiment of the present disclosure, multiple risk adjustment factors include a first risk adjustment factor and a second risk adjustment factor. The asset-liability factor of the target object within a specified period is determined based on the asset mean and the liability mean; the asset volatility intensity of the total assets of the target object in each historical period within the specified period is determined based on the volatility factor and the specified period; the first risk adjustment factor is calculated based on the asset-liability factor and the asset volatility intensity; the risk adjustment amount is determined based on the volatility factor and the specified period; and the second risk adjustment factor is determined based on the first risk adjustment factor and the risk adjustment amount.

[0056] In the embodiment of the present disclosure, the first risk adjustment factor is d1, the second risk adjustment factor is d2,

[0057]

[0058]

[0059] in, represents the mean value of assets, D represents the mean value of liabilities, Indicates the asset-liability factor of the target object in the specified period, δ a represents the volatility factor (asset volatility), Indicates the volatility of assets. represents the risk adjustment amount and T represents the specified period.

[0060] Step 204, calculating the risk compensation base points of the target object within a specified period according to the multiple risk adjustment factors.

[0061] In order to improve the accuracy of the risk compensation basis point calculation, as a possible implementation method, the risk compensation basis points of the target object within a specified period are calculated by combining multiple indicators.

[0062] In the disclosed embodiment, the average asset and average liability of the target object in each historical period are obtained; the risk-free interest rate of the financial institution in a specified period is obtained; based on the average asset, average liability, risk-free interest rate and multiple risk adjustment factors, the risk compensation basis point of the target object in the specified period is calculated.

[0063] The calculation of risk compensation basis points is as follows:

[0064]

[0065] Where N(x) represents the standard normal distribution, represents the mean value of assets, D represents the mean value of liabilities, r represents the risk-free rate, T represents the specified period, d1 represents the first risk adjustment factor, and d2 represents the second risk adjustment factor. It should be noted that the mean value of assets of the target object in each historical period is determined by the following steps:

[0066] 1. For any historical period, obtain the total assets in any historical period from the business data table;

[0067] 2. Determine the average asset value for each historical period based on the ratio of the sum of the total assets to the quantity of each historical period.

[0068] In the disclosed embodiment, the asset mean The expression formula is as follows:

[0069]

[0070] Among them, V1, V2…V n It represents the total assets in each historical period, and n represents the number of historical periods.

[0071] In addition, the average value of the target object's liabilities in each historical period is determined using the following steps:

[0072] 1. For any historical period, obtain the short-term liabilities and long-term liabilities for any historical period from the business data table;

[0073] 2. Based on the short-term liabilities in each historical period, determine the average short-term liabilities in each historical period;

[0074] 3. Based on the long-term liabilities in each historical period, determine the average long-term liabilities in each historical period;

[0075] 4. Determine the average debt of the target object in each historical period based on the sum of the average short-term debt and the average long-term debt.

[0076] In the embodiment of the present disclosure, the debt mean D is expressed as the following formula:

[0077]

[0078] in, It represents the average short-term debt of the target object in each historical period. Represents the average value of the target object’s long-term liabilities in each historical period, where:

[0079]

[0080] D s1 , D s2 …D sn represents the short-term liabilities of the target object in each historical period, D l1 , D l2 …D ln It represents the long-term liabilities of the target object in each historical period, and n represents the number of historical periods.

[0081] Step 205, based on the risk compensation basis point, risk pricing is performed on the target object to obtain a risk pricing result of the target object executing the target business.

[0082] Step 206: Generate the execution result of the target task according to the risk pricing result, and send the execution result to the first client for visual display.

[0083] It should be noted that the execution process of steps 201 to 202 and steps 205 to 206 can be implemented in any way in the embodiments of the present disclosure, and the embodiments of the present disclosure do not limit this and will not be repeated.

[0084] In summary, by determining multiple risk adjustment factors of the target object within the specified period based on the volatility factor and the specified period; calculating the risk compensation basis points of the target object within the specified period based on the multiple risk adjustment factors, thereby calculating the risk compensation basis points based on multiple risk adjustment factors, the risk compensation basis points reflect the multiple risk characteristics of the target object, and performing risk pricing based on the risk compensation basis points improves the accuracy of risk pricing, which can better reflect the actual risk differences of different customers and improve the risk management capabilities of financial institutions.

[0085] In order to clearly illustrate how the volatility factor of the target object within a specified period is calculated based on each asset factor in the above embodiment, the present disclosure proposes another task execution method.

[0086] Figure 3It is a flowchart of a task execution method shown in the third embodiment of the present disclosure.

[0087] like Figure 3 As shown, the task execution method includes the following steps:

[0088] Step 301, in response to receiving a task request sent by the first client, determining a target task that matches the task request, and executing the target task to determine the asset factors of the target object of the target business of the financial institution to be executed in multiple historical periods based on the business data in the business data table associated with the task purpose of the target task.

[0089] Step 302: Determine a second value based on each asset factor and the first value of each asset factor.

[0090] Among them, the first value is used to indicate the changing trend of each asset factor, and the second value is used to indicate the degree of dispersion of each asset factor.

[0091] In the embodiment of the present disclosure, the first value

[0092] Second value

[0093] Among them, x1, x2, … x n Represents each asset factor (asset return rate); n represents the number of historical periods.

[0094] Step 303: Determine the fluctuation factor of the target object within the specified period according to the specified period and the second value.

[0095] In the disclosed embodiment,

[0096] It should be noted that δ a Represents the asset volatility of one year. When the period corresponding to δ is one day, T=360; when the period corresponding to δ is one week, T=52; when the period corresponding to δ is one month, T=12; when the period corresponding to δ is one quarter, T=4.

[0097] Step 304: Determine the risk compensation base point of the target object within a specified period according to the volatility factor.

[0098] Step 305: Based on the risk compensation basis point, risk pricing is performed on the target object to obtain a risk pricing result of the target object executing the target business.

[0099] Step 306: Generate the execution result of the target task according to the risk pricing result, and send the execution result to the first client for visual display.

[0100] It should be noted that the execution process of step 301 and steps 304 to 306 can be implemented in any manner in the embodiments of the present disclosure, and the embodiments of the present disclosure do not limit this and will not be described in detail.

[0101] In summary, the second value is determined based on each asset factor and the first value of each asset factor; the volatility factor of the target object within the specified period is determined based on the specified period and the second value. Therefore, by determining the second value based on the asset factor and its first value, and combining it with the specified period, the volatility factor of the target object within a specific time can be effectively calculated.

[0102] In order to clearly illustrate how the above embodiment determines the asset factors of the target object of the target business of the financial institution to be executed in multiple historical periods based on the business data in the business data table associated with the task purpose of the target task, the present disclosure proposes another task execution method.

[0103] Figure 4 It is a flowchart of a task execution method shown in the fourth embodiment of the present disclosure.

[0104] like Figure 4 As shown, the task execution method includes the following steps:

[0105] Step 401, obtaining the total assets of the target object in multiple historical periods from the business data table.

[0106] Among them, the total assets are sent by the second client and written into the business data table within the corresponding historical period.

[0107] In the embodiment of the present disclosure, the business data table includes the total assets, short-term liabilities and long-term liabilities of the target object in multiple historical periods. Therefore, the total assets of the target object in multiple historical periods are obtained from the business data table.

[0108] For example, obtain the total assets in 2021, 2022 and 2023 from the business data table respectively.

[0109] Among them, it should be noted that the total assets of each historical period refer to the total value of all assets owned by the target object in the corresponding historical period. The total assets of each historical period are when the second client obtains the total assets of the target object in the corresponding historical period, the total assets are sent to the server, and the server writes the total assets into the business data table.

[0110] Step 402, for any historical period, obtain the total assets of any historical period and the total assets of the previous historical period from the total assets.

[0111] For example, the total assets of multiple historical periods include the total assets in 2021, the total assets in 2022 and the total assets in 2023. For 2022, the total assets in 2021 and the total assets in 2022 are obtained from the total assets in multiple historical periods; for 2023, the total assets in 2022 and the total assets in 2023 are obtained from the total assets in multiple historical periods.

[0112] Step 403, determining the asset factor of any historical period according to the ratio of the total assets of any historical period to the total assets of the previous historical period.

[0113] In the embodiment of the present disclosure, the asset factor is the asset return rate, and the asset return rate is expressed as the following formula:

[0114]

[0115] Among them, S t Represents the total assets in any historical period, S t-1 It represents the total assets in the previous historical period, and i represents the number of asset returns.

[0116] Step 404, determining the volatility factor of the target object within a specified period based on each asset factor.

[0117] Step 405: Determine the risk compensation base point of the target object within a specified period according to the volatility factor.

[0118] Step 406, based on the risk compensation basis point, risk pricing is performed on the target object to obtain a risk pricing result of the target object executing the target business.

[0119] Step 407: Generate the execution result of the target task according to the risk pricing result, and send the execution result to the first client for visual display.

[0120] It should be noted that the execution process of steps 404 to 406 can be implemented in any manner in the embodiments of the present disclosure, and the embodiments of the present disclosure do not limit this and will not be described in detail.

[0121] In summary, the total assets of the target object in multiple historical periods are obtained from the business data table; wherein, the total assets are sent by the second client and written into the business data table in the corresponding historical period. For any historical period, the total assets of any historical period and the total assets of the previous historical period are obtained from the total assets. The asset factor of any historical period is determined according to the total assets of any historical period and the total assets of the previous historical period. Thus, the asset factor is determined based on the total assets sent by the second client and written into the data table in the corresponding historical period, thereby ensuring the timeliness and accuracy of the data. The server performs subsequent analysis and decision-making based on these accurate data, avoiding the risks caused by data delays or errors, while simplifying the process of data collection and processing and improving work efficiency.

[0122] On the basis of any of the above embodiments, taking the task purpose of calculating the risk pricing of the target object as an example, the task execution method of the embodiment of the present disclosure is implemented based on the following steps.

[0123] Step 1. Collect and organize financial data tables (business data tables), as shown in Table 1, which includes total assets, short-term liabilities and long-term liabilities for 2021, 2022 and 2023.

[0124] Table 1 Financial data table

[0125] year Total assets (V) <![CDATA[Short-term liabilities (D s )]]> <![CDATA[Long-term liabilities (D l )]]> 2021 410843.00 458123.00 102617.00 2022 416998.00 448881.00 102930.00 2023 437965.00 441762.00 17012.00

[0126] Average asset value

[0127] Mean short-term liabilities

[0128] Mean long-term debt

[0129] Step 2: Calculate the return on assets x i (Asset Factor);

[0130] Return on assets in 2022

[0131] Return on assets in 2023

[0132] Step 3: Calculate the first value The second value δ and asset volatility δ a (Volatility Factor);

[0133]

[0134] Step 4: Calculate multiple risk adjustment factors d1 and d2

[0135]

[0136] Step 5: Calculate the risk compensation basis point R p and risk pricing result R c ;

[0137]

[0138] R c =R b +R f +R p =2%+1.45%+3.63%=7.08%

[0139] Corresponding to the task execution method provided in the above-mentioned embodiment, the present disclosure also provides a task execution device. Since the task execution device provided in the embodiment of the present disclosure corresponds to the task execution method provided in the above-mentioned embodiment, the implementation method of the task execution method is also applicable to the task execution device provided in the embodiment of the present disclosure, and will not be described in detail in the embodiment of the present disclosure.

[0140] Figure 5 It is a structural diagram of a task execution device shown in the fifth embodiment of the present disclosure.

[0141] like Figure 5 As shown, the task execution device 500 includes: an execution module 510, a first determination module 520, a second determination module 530, a pricing module 540 and a generation module 550.

[0142] Among them, the execution module 510 is used to determine the target task matching the task request in response to receiving the task request sent by the first client, and execute the target task to determine the asset factors of the target object of the target business of the financial institution to be executed in multiple historical time periods based on the business data in the business data table associated with the task purpose of the target task; the first determination module 520 is used to determine the volatility factor of the target object within a specified period based on each asset factor; wherein the length of the historical period is the same as the length of the specified period; the second determination module 530 is used to determine the risk compensation basis point of the target object within the specified period based on the volatility factor; the pricing module 540 is used to perform risk pricing on the target object based on the risk compensation basis point to obtain the risk pricing result of the target object executing the target business; the generation module 550 is used to generate the execution result of the target task based on the risk pricing result, and send the execution result to the first client for visual display.

[0143] As a possible implementation method of the embodiment of the present disclosure, the execution module 510 is used to query the total assets of the target object in multiple historical periods from the business data table; wherein the total assets are sent by the second client and written into the business data table within the corresponding historical period; for any historical period, the total assets of any historical period and the total assets of the previous historical period are obtained from the total assets; the asset factor of any historical period is determined based on the ratio of the total assets of any historical period to the total assets of the previous historical period.

[0144] As a possible implementation method of the embodiment of the present disclosure, generation module 550 is used to, in response to the task purpose being to calculate risk pricing, use the risk pricing result as the execution result of the target task; in response to the task purpose being to approve business applications, determine the difference between the risk pricing result and a set risk pricing threshold; in response to the difference being within the set threshold range, generate an execution result indicating that the target business has passed the approval; in response to the difference not being within the set threshold range, generate an execution result indicating that the target business has not passed the approval.

[0145] As a possible implementation method of the embodiment of the present disclosure, the second determination module 530 is used to determine multiple risk adjustment factors of the target object within the specified period according to the volatility factor and the specified period; and calculate the risk compensation base point of the target object within the specified period according to the multiple risk adjustment factors.

[0146] As a possible implementation method of the embodiment of the present disclosure, the second determination module 530 is used to obtain the average asset value and the average liability value of the target object in each historical period; obtain the risk-free interest rate of the financial institution in a specified period; and calculate the risk compensation basis point of the target object in the specified period based on the asset average, liability average, risk-free interest rate and multiple risk adjustment factors.

[0147] As a possible implementation method of the embodiment of the present disclosure, multiple risk adjustment factors include a first risk adjustment factor and a second risk adjustment factor, and the second determination module 530 is used to determine the asset-liability factor of the target object within a specified period based on the asset mean and the liability mean; determine the asset volatility intensity of the total assets of the target object in each historical period within the specified period based on the volatility factor and the specified period; calculate the first risk adjustment factor based on the asset-liability factor and the asset volatility intensity; determine the risk adjustment amount based on the volatility factor and the specified period; determine the second risk adjustment factor based on the first risk adjustment factor and the risk adjustment amount.

[0148] As a possible implementation method of the embodiment of the present disclosure, the second determination module 530 is used to obtain short-term liabilities and long-term liabilities in any historical period from the business data table for any historical period; determine the average short-term liabilities in each historical period based on the short-term liabilities in each historical period; determine the average long-term liabilities in each historical period based on the long-term liabilities in each historical period; determine the average liabilities of the target object in each historical period based on the sum of the average short-term liabilities and the average long-term liabilities.

[0149] As a possible implementation method of the embodiment of the present disclosure, the second determination module 530 is used to obtain the total assets in any historical period from the business data table for any historical period; and determine the average asset value of each historical period based on the ratio of the sum of the total assets to the number of each historical period.

[0150] As a possible implementation method of the embodiment of the present disclosure, the first determination module 520 is used to determine the second value based on each asset factor and the first value of each asset factor; wherein the first value is used to indicate the change trend of each asset factor, and the second value is used to indicate the discrete degree of each asset factor; based on the specified period and the second value, determine the volatility factor of the target object within the specified period.

[0151] As a possible implementation method of the embodiment of the present disclosure, the pricing module 540 is used to obtain the base interest rate of the financial institution and the risk-free interest rate within a specified period; and determine the risk pricing result of the target object executing the target business based on the sum of the base interest rate, the risk-free interest rate and the risk compensation basis point.

[0152] The task execution device of the disclosed embodiment determines the target task matching the task request in response to receiving the task request sent by the first client, and executes the target task, so as to determine the asset factors of the target object of the target business of the financial institution to be executed in multiple historical periods according to the business data in the business data table associated with the task purpose of the target task; determines the volatility factor of the target object within a specified period according to each asset factor; determines the risk compensation basis point of the target object within the specified period according to the volatility factor; performs risk pricing on the target object based on the risk compensation basis point to obtain the risk pricing result of the target object executing the target business; generates the execution result of the target task according to the risk pricing result, and sends the execution result to the first client for visual display, thereby triggering the execution of the target task when the task request sent by the first client is received, so as to perform risk pricing on the target object, thereby reducing intermediate links and manual intervention. The accuracy and timeliness of risk pricing of the target object are improved. When the risk pricing of the target object is performed, the asset factor is determined based on the total assets sent by the second client and written into the data table in the corresponding historical period, thereby ensuring the timeliness and accuracy of the data. The server calculates the volatility factor based on the asset factor, thereby accurately reflecting the asset changes and potential risks of the target object in the specified period. The risk compensation basis point determined by the volatility factor is used to perform risk pricing on the target object, and the execution result of the automatic target task is generated according to the risk pricing result, thereby reducing manual intervention and decision-making time, improving the efficiency and accuracy of task execution, and thus improving the accuracy of the risk pricing result. The execution result is sent to the first client for visual display, thereby realizing the intuitive display of complex data and analysis results. Users can intuitively understand the distribution and trend of the data, quickly discover key information and potential problems, and improve decision-making efficiency.

[0153] In an exemplary embodiment, an electronic device is also provided.

[0154] Among them, electronic equipment includes:

[0155] processor;

[0156] a memory for storing processor-executable instructions;

[0157] The processor is configured to execute instructions to implement the task execution method proposed in any of the aforementioned embodiments.

[0158] As an example, Figure 6 is a schematic diagram of the structure of an electronic device 600 shown in an exemplary embodiment of the present disclosure, such as Figure 6 As shown, the electronic device 600 may further include:

[0159] The memory 610 and the processor 620, a bus 630 connecting different components (including the memory 610 and the processor 620), the memory 610 stores a computer program, and when the processor 620 executes the program, the task execution method described in the embodiment of the present disclosure is implemented.

[0160] Bus 630 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor or a local bus using any of a variety of bus architectures. By way of example, these architectures include, but are not limited to, an Industry Standard Architecture (ISA) bus, a Micro Channel Architecture (MAC) bus, an Enhanced ISA bus, a Video Electronics Standards Association (VESA) local bus, and a Peripheral Component Interconnect (PCI) bus.

[0161] The electronic device 600 typically includes a variety of electronic device readable media. These media can be any available media that can be accessed by the electronic device 600, including volatile and non-volatile media, removable and non-removable media.

[0162] The memory 610 may also include computer system readable media in the form of volatile memory, such as random access memory (RAM) 640 and / or cache memory 650. The server 600 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the storage system 660 may be used to read and write non-removable, non-volatile magnetic media ( Figure 6 not shown, usually called a "hard drive"). Although Figure 6 Not shown, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk"), and an optical disk drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, a DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to the bus 630 via one or more data medium interfaces. The memory 610 may include at least one program product having a set (e.g., at least one) of program modules that are configured to perform the functions of the various embodiments of the present disclosure.

[0163] A program / utility 680 having a set (at least one) of program modules 670 may be stored, for example, in the memory 610, such program modules 670 including but not limited to an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment. The program modules 670 generally perform the functions and / or methods of the embodiments described in the present disclosure.

[0164] The electronic device 600 may also communicate with one or more external devices 690 (e.g., keyboard, pointing device, display 691, etc.), may also communicate with one or more devices that enable a user to interact with the electronic device 600, and / or communicate with any device that enables the electronic device 600 to communicate with one or more other computing devices (e.g., network card, modem, etc.). Such communication may be performed via an input / output (I / O) interface 692. Furthermore, the electronic device 600 may also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN) and / or public network, such as the Internet) via a network adapter 693. As shown, the network adapter 693 communicates with other modules of the electronic device 600 via a bus 630. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 600, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0165] The processor 620 executes various functional applications and data processing by running the programs stored in the memory 610 .

[0166] It should be noted that the implementation process and technical principles of the electronic device of this embodiment refer to the aforementioned explanation of the task execution method of the embodiment of the present disclosure, and will not be repeated here.

[0167] In an exemplary embodiment, a computer-readable storage medium including instructions is also provided, such as a memory including instructions, and the above instructions can be executed by a processor of an electronic device to complete the task execution method proposed in any of the above embodiments. Optionally, the computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0168] In an exemplary embodiment, a computer program product is also provided, including a computer program / instruction, wherein the computer program / instruction, when executed by a processor, implements the task execution method proposed in any of the above embodiments.

[0169] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the invention disclosed herein. The present disclosure is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The description and examples are to be considered exemplary only, and the true scope and spirit of the present disclosure are indicated by the following claims.

[0170] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A task execution method, characterized in that: Applied to the server, including: In response to receiving a task request sent by the first client, determining a target task matching the task request, and executing the target task to determine the asset factors of a target object of a target business of a financial institution to be executed in multiple historical periods according to business data in a business data table associated with a task purpose of the target task; Determining the volatility factor of the target object within a specified period according to each of the asset factors; Determining the risk compensation base point of the target object within the specified period according to the volatility factor; Based on the risk compensation basis point, risk pricing is performed on the target object to obtain a risk pricing result of the target object executing the target business; According to the risk pricing result, the execution result of the target task is generated, and the execution result is sent to the first client for visual display.

2. The method according to claim 1, characterized in that: The determining of the asset factors of the target object of the target business of the financial institution to be executed in multiple historical periods according to the business data in the business data table associated with the task purpose of the target task includes: Querying the total assets of the target object in the multiple historical periods from the business data table; wherein the total assets are sent by the second client and written into the business data table in the corresponding historical period; For any historical period, from each of the total assets, obtain the total assets of the any historical period and the total assets of the previous historical period; The asset factor of any historical period is determined based on the ratio of the total assets of any historical period to the total assets of the previous historical period.

3. The method according to claim 1, characterized in that Generating the execution result of the target task according to the risk pricing result includes: In response to the task purpose being to calculate risk pricing, using the risk pricing result as the execution result of the target task; In response to the task purpose being to approve a business application, determining a difference between the risk pricing result and a set risk pricing threshold; In response to the difference being within a set threshold range, generating an execution result indicating that the target business has passed approval; In response to the difference not being within the set threshold range, an execution result indicating that the target business has not passed the approval is generated.

4. The method according to claim 1, characterized in that Determining the risk compensation base point of the target object within the specified period according to the volatility factor includes: Determining, based on the volatility factor and the specified period, a plurality of risk adjustment factors for the target object within the specified period; The risk compensation base points of the target object in the specified period are calculated according to the multiple risk adjustment factors.

5. The method according to claim 4, characterized in that The step of calculating the risk compensation base point of the target object within the specified period according to the multiple risk adjustment factors includes: Obtaining the average value of assets and the average value of liabilities of the target object in each of the historical periods; Obtain the risk-free interest rate of the financial institution during the specified period; The risk compensation basis points of the target object in the specified period are calculated based on the asset mean, the liability mean, the risk-free interest rate and the multiple risk adjustment factors.

6. The method according to claim 5, characterized in that The multiple risk adjustment factors include a first risk adjustment factor and a second risk adjustment factor, and determining the multiple risk adjustment factors of the target object within the specified period according to the volatility factor and the specified period includes: Determining the asset-liability factor of the target object within the specified period according to the asset mean and the liability mean; Determine the asset volatility intensity of the total assets of the target object in each of the historical time periods within the specified period according to the volatility factor and the specified period; Calculating the first risk adjustment factor based on the asset-liability factor and the asset volatility intensity; determining a risk adjustment amount based on the volatility factor and the specified period; The second risk adjustment factor is determined based on the first risk adjustment factor and the risk adjustment amount.

7. The method according to claim 5, characterized in that Obtaining the average value of the target object's liabilities in each of the historical periods, including: For any historical period, obtaining short-term liabilities and long-term liabilities in the historical period from the business data table; Determine the average value of short-term liabilities for each of the above historical periods based on the short-term liabilities for each of the above historical periods; Determine the average value of long-term liabilities for each of the historical periods based on the long-term liabilities for each of the historical periods; The average debt of the target object in each of the historical periods is determined based on the sum of the average short-term debt and the average long-term debt.

8. The method according to claim 5, characterized in that Obtaining the average asset value of the target object in each of the historical periods, including: For any historical period, obtaining the total assets in the historical period from the business data table; The average asset value of each historical period is determined based on the ratio of the sum of the total assets to the number of each historical period.

9. The method according to claim 1, characterized in that: The step of calculating the volatility factor of the target object within a specified period according to each of the asset factors includes: Determine a second value according to each of the asset factors and the first value of each of the asset factors; wherein the first value is used to indicate the change trend of each of the asset factors, and the second value is used to indicate the degree of dispersion of each of the asset factors; A fluctuation factor of the target object within the specified period is determined according to the specified period and the second value.

10. The method according to claim 1, characterized in that The step of performing risk pricing on the target object based on the risk compensation base point to obtain a risk pricing result of the target object executing the target business includes: Obtain the base interest rate of the financial institution and the risk-free interest rate in the specified period; The risk pricing result of the target object executing the target business is determined according to the sum of the base interest rate, the risk-free interest rate and the risk compensation basis point.

Images