Business object processing method, device, computer device, and storage medium

Abstract

The present disclosure relates to the technical field of big data analysis, and particularly relates to a business object processing method and device, computer equipment, a storage medium and a computer program product. The method comprises: in response to a processing request for a business object, obtaining business object data and user risk data; determining a business cycle corresponding to the business object; generating a yield loss parameter corresponding to the business cycle according to the business object data and the user risk data; generating a risk parameter of the business object according to the yield loss parameter; and generating a processing result of the business object in response to a comparison result of the risk parameter and a preset risk threshold. The method can generate a yield loss parameter of a business object by combining data at the business object level and the user level, thereby improving the practicality of the risk parameter, and helping to generate a processing result of the business object based on the risk parameter subsequently, so as to be suitable for various different types of business object processing scenarios, thereby improving the versatility of the business object processing method.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of big data analysis, and in particular, to a business object processing method and device, computer equipment, a storage medium, and a computer program product. BACKGROUND

[0002] When processing a business application submitted by a user, a financial institution often needs to evaluate the return rate of the business based on the application information of the user to maximize the profit of the business as much as possible. For example, when approving a loan application of a user, a bank will evaluate the risk return rate of the loan product applied by the user according to the asset level, recent consumption expenditure record, and information such as whether there is a loan overdue record of the user, and can subsequently perform credit approval processing or risk pricing processing on the loan application based on the risk return rate of the loan product.

[0003] In the traditional technology, the expected income and expected loss of a loan product can be calculated according to the loan application information of a user, the economic capital can be calculated through a VaR model (Value at Risk), and the risk return rate corresponding to the loan product can be generated according to the expected income, expected loss, and economic capital of the loan product. The loan product is subjected to data processing operations according to the risk return rate.

[0004] However, as the user's business needs change, the types of businesses in the market are also becoming more and more diverse. The business object processing method in the traditional technology is difficult to adapt to different types of business scenarios, and therefore, there is an urgent need for a business object processing method with stronger universality. SUMMARY

[0005] Therefore, it is necessary to provide a business object processing method, device, computer equipment, computer readable storage medium, and computer program product with stronger universality to solve the above technical problems.

[0006] In a first aspect, the present disclosure provides a business object processing method. The method comprises:

[0007] In response to a processing request for a business object, obtaining business object data and user risk data;

[0008] Determining a business cycle corresponding to the business object;

[0009] Generating an income and loss parameter corresponding to the business cycle according to the business object data and the user risk data;

[0010] Generating a risk parameter of the business object according to the income and loss parameter;

[0011] In response to a comparison result of the risk parameter and a preset risk threshold, a processing result of the business object is generated.

[0012] In one embodiment provided by the present disclosure, the business cycle includes a plurality of business processing stages.

[0013] The generating of the yield loss parameter corresponding to the business cycle according to the business object data and the user risk data includes:

[0014] The generating of the yield loss parameter corresponding to each of the business processing stages according to the business object data and the user risk data.

[0015] In one embodiment provided by the present disclosure, the generating of the yield loss parameter corresponding to the business cycle according to the business object data and the user risk data includes:

[0016] The determining of an amount parameter corresponding to the business cycle according to the business object data;

[0017] The determining of a default parameter corresponding to the business cycle according to the user risk data;

[0018] The generating of the yield loss parameter according to the amount parameter and the default parameter.

[0019] In one embodiment provided by the present disclosure, the default parameter includes a default rate, the amount parameter includes an interest parameter, and the yield loss parameter includes a yield parameter.

[0020] The generating of the yield loss parameter according to the amount parameter and the default parameter includes:

[0021] The yield parameter is obtained by the following formula:

[0022]

[0023] Wherein, EP is the yield parameter, n is the number of business processing stages in the business cycle of the business object, i is the serial number of the business processing stage, P i is the default rate corresponding to the i th business processing stage of the business object, I i is the interest parameter corresponding to the i th business processing stage of the business object.

[0024] In one embodiment provided by the present disclosure, the default parameter includes a default rate and a default loss rate, the amount parameter includes a remaining principal, and the yield loss parameter includes a loss parameter.

[0025] The generating the income loss parameter according to the amount parameter and the default parameter comprises:

[0026] The loss parameter is obtained by the following formula:

[0027]

[0028] Wherein, EL is the loss parameter, n is the number of business processing stages in the business cycle of the business object, i is the serial number of the business processing stage, P i is the default rate corresponding to the i-th business processing stage of the business object, B i is the residual principal corresponding to the i-th business processing stage of the business object, LGD i is the default loss rate corresponding to the i-th business processing stage of the business object.

[0029] In an embodiment provided by the present disclosure, the method further comprises:

[0030] Obtaining a cost parameter corresponding to the business object;

[0031] The generating the risk parameter of the business object according to the income loss parameter comprises:

[0032] Generating a business cost of the business object according to the cost parameter and the business object data;

[0033] Performing operation processing on the income loss parameter, the business cost and the business object data to generate the risk parameter.

[0034] In a second aspect, the present disclosure further provides a processing device of a business object. The device comprises:

[0035] A data acquisition module configured to acquire business object data and user risk data in response to a processing request for a business object;

[0036] A cycle determination module configured to determine a business cycle corresponding to the business object;

[0037] A loss generation module configured to generate an income loss parameter corresponding to the business cycle according to the business object data and the user risk data;

[0038] A risk generation module configured to generate a risk parameter of the business object according to the income loss parameter, the risk parameter being used to indicate that a corresponding data processing operation is performed on the business object;

[0039] A result generation module configured to generate a processing result of the business object in response to a comparison result of the risk parameter and a preset risk threshold.

[0040] In one embodiment provided by the present disclosure, the business cycle comprises a plurality of business processing stages.

[0041] The loss generation module is further configured to generate the yield loss parameter corresponding to each of the business processing stages according to the business object data and the user risk data.

[0042] In one embodiment provided by the present disclosure, the loss generation module comprises:

[0043] A first parameter determination unit configured to determine an amount parameter corresponding to the business cycle according to the business object data;

[0044] A second parameter determination unit configured to determine a default parameter corresponding to the business cycle according to the user risk data;

[0045] A parameter generation unit configured to generate the yield loss parameter according to the amount parameter and the default parameter.

[0046] In one embodiment provided by the present disclosure, the default parameter comprises a default rate, the amount parameter comprises an interest parameter, and the yield loss parameter comprises a yield parameter.

[0047] The parameter generation unit is further configured to obtain the yield parameter by the following formula:

[0048]

[0049] wherein, EP is the yield parameter, n is the number of business processing stages in the business cycle of the business object, i is the serial number of the business processing stage, P i is the default rate corresponding to the i-th business processing stage of the business object, and I i is the interest parameter corresponding to the i-th business processing stage of the business object.

[0050] In one embodiment provided by the present disclosure, the default parameter comprises a default rate and a default loss rate, the amount parameter comprises a remaining principal, and the yield loss parameter comprises a loss parameter.

[0051] The parameter generation unit is further configured to obtain the loss parameter by the following formula:

[0052]

[0053] wherein, EL is the loss parameter, n is the number of business processing stages in the business cycle of the business object, i is the serial number of the business processing stage, P iB is the default rate corresponding to the i-th business processing stage of the business object i LGD is the residual principal corresponding to the i-th business processing stage of the business object i LGD is the residual principal corresponding to the i-th business processing stage of the business object

[0054] In an embodiment provided by the present disclosure, the apparatus further comprises:

[0055] a parameter acquisition module configured to acquire a cost parameter corresponding to the business object;

[0056] The risk generation module comprises:

[0057] a business cost generation unit configured to generate a business cost of the business object according to the cost parameter and the business object data;

[0058] a risk parameter generation unit configured to perform operation processing on the yield loss parameter, the business cost and the business object data to generate the risk parameter.

[0059] In a third aspect, the present disclosure further provides a computer device. The computer device comprises a memory and a processor, the memory stores a computer program, and the processor implements the processing method of the business object according to any one of the embodiments of the first aspect when executing the computer program.

[0060] In a fourth aspect, the present disclosure further provides a computer readable storage medium. The computer readable storage medium stores a computer program, and the computer program is executed by a processor to implement the processing method of the business object according to any one of the embodiments of the first aspect.

[0061] In a fifth aspect, the present disclosure further provides a computer program product. The computer program product comprises a computer program, and the computer program is executed by a processor to implement the processing method of the business object according to any one of the embodiments of the first aspect.

[0062] The processing method, device, computer device, storage medium and computer program product of the business object can obtain business object data and user risk data in response to a processing request for a business object, determine a business period corresponding to the business object, generate a yield loss parameter corresponding to the business period according to the business object data and the user risk data, generate a risk parameter of the business object according to the yield loss parameter, and generate a processing result of the business object in response to a comparison result of the risk parameter and a preset risk threshold. The yield loss parameter corresponding to the business period of the business object can be generated by combining the business object data and the business period at the business object level and the user risk data at the user level, so that the risk parameter generated based on the yield loss parameter is more practical in a specific business object processing scenario. The processing result of the business object can be generated according to the comparison result of the risk parameter and the preset risk threshold, which is suitable for various types of business object processing scenarios, thereby improving the universality of the processing method of the business object.

[0063] In addition, compared with the technical means of calculating economic capital by a VaR model to generate a risk parameter in the prior art, the processing method of the business object provided by the present disclosure generates a risk parameter of the business object by using business object data, user risk data and a business period corresponding to the business object. The generation difficulty of the risk parameter is simplified, the operability of the processing method of the business object is improved, and the generation efficiency of the risk parameter is improved, thereby further improving the processing efficiency of the business object. BRIEF DESCRIPTION OF DRAWINGS

[0064] Figure 1 A flowchart of a processing method of a business object in an embodiment;

[0065] Figure 2 A flowchart of a yield loss parameter generation step in an embodiment;

[0066] Figure 3 A flowchart of a yield loss parameter generation step in another embodiment;

[0067] Figure 4 A flowchart of a risk parameter generation step in an embodiment;

[0068] Figure 5 A flowchart of a processing method of a business object in another embodiment;

[0069] Figure 6 A block diagram of a processing device of a business object in an embodiment;

[0070] Figure 7 An internal structure diagram of a computer device in an embodiment. DETAILED DESCRIPTION

[0071] In order to make the purposes, technical solutions and advantages of the present disclosure clearer, the present disclosure will be further described in detail below with reference to the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present disclosure and not to limit the present disclosure.

[0072] In one embodiment provided by the present disclosure, as shown in Figure 1 A processing method of a business object is provided, and the embodiment is exemplarily described by applying the method to a server. It should be understood that the method can also be applied to a terminal, and can also be applied to a system including a terminal and a server, and is implemented through the interaction of the terminal and the server. The terminal can be, but is not limited to, various personal computers, notebook computers, smart phones, tablet computers, Internet of Things devices, and portable wearable devices. The Internet of Things device can be a smart television, a smart vehicle device, etc. The portable wearable device can be a smart watch, a smart bracelet, a head-mounted device, etc. The server can be implemented by an independent server or a server cluster composed of multiple servers.

[0073] In the embodiment, the method includes the following steps:

[0074] In step S102, in response to a processing request for a business object, business object data and user risk data are acquired.

[0075] The business object data can include, but is not limited to, any one or more of various business data such as the type of the business object, the amount of the business object, the interest rate of the business object, and the processing period of the business object.

[0076] The user risk data can include, but is not limited to, any one or more of various user data such as the age of the user, the survival time of the user, and the business channel of the user.

[0077] Specifically, the server acquires the business object data corresponding to the business object and the user risk data in response to a processing request for the business object. The processing request for the business object can be manually triggered by the user on demand, for example, when the user submits a business application for the business object, the processing request for the business object is triggered. The processing request for the business object can also be automatically triggered by the server, for example, when the server detects the business object, the processing request for the business object is automatically triggered.

[0078] In step S104, a business period corresponding to the business object is determined.

[0079] The business period can be used to represent the processing period of the business object.

[0080] Specifically, the server can determine the business period corresponding to the business object according to the business object data of the business object. In one example, the server can generate the business period corresponding to the business object according to the processing deadline of the business object in the business object data. For example, in the case where the processing deadline of the business object is three months, the obtained business period is three months. In another example, the server can also generate the business period corresponding to the business object according to the type of the business object in the business object data. For example, in the case where the business type of the business object is a installment type, the obtained business period includes each installment period.

[0081] In step S106, the income and loss parameter corresponding to the business period is generated according to the business object data and the user risk data.

[0082] The income and loss parameter can be used to represent the income level and loss level of the business object in the business period.

[0083] Specifically, the server can pre-store a risk assessment model. The user risk data is input into the risk assessment model to determine the risk score corresponding to the user risk data. The risk probability corresponding to the risk score is obtained, and the risk probability is used to operate and process the business object data to generate the income parameter and the loss parameter of the business object in the business period, and the income and loss parameter is determined according to the income parameter and the loss parameter.

[0084] In step S108, the risk parameter of the business object is generated according to the income and loss parameter.

[0085] The risk parameter can be used to represent the risk return level of the business object.

[0086] Specifically, the server pre-stores a risk parameter generation logic. The risk parameter generation logic is used to process the income and loss parameter to generate the risk parameter of the business object. The risk parameter generation logic can be an operation and processing on the business object data and the income and loss parameter, taking the income and loss parameter as the dividend, taking the business object data as the divisor, obtaining the quotient between the business object data and the income and loss parameter, and taking the quotient as the risk parameter of the business object. The income and loss parameter can also be compared with a preset threshold, and according to the comparison result, the risk parameter corresponding to the income and loss parameter is determined.

[0087] In step S110, the processing result of the business object is generated in response to the comparison result of the risk parameter and the preset risk threshold.

[0088] Specifically, a preset risk threshold can be stored in the server. The risk parameter is compared with the preset risk threshold to generate a comparison result of the risk parameter and the preset risk threshold. In response to the comparison result that the risk parameter is greater than the preset risk threshold, a first processing result of the business object is generated. In response to the comparison result that the risk parameter is equal to or less than the preset risk threshold, a second processing result of the business object is generated. In one example, the processing request for the business object can be a credit approval request for the business object. The first processing result generated by the server can be a result of passing the credit approval for the business object, and the second processing result can be a result of failing the credit approval for the business object. In another example, the processing request for the business object can be a risk pricing request for the business object. In the case where the server generates the second processing result in response to the comparison result that the risk parameter is equal to the preset risk threshold, the second processing result can be to obtain the interest of the current business object as the risk pricing parameter of the business object.

[0089] In the above business object processing method, by responding to the processing request for the business object, the business object data and the user risk data are obtained, the business period corresponding to the business object is determined, the yield loss parameter corresponding to the business period is generated according to the business object data and the user risk data, the risk parameter of the business object is generated according to the yield loss parameter, and the processing result of the business object is generated in response to the comparison result of the risk parameter and the preset risk threshold. The yield loss parameter corresponding to the business period of the business object can be generated by combining the business object data and the business period at the business object level and the user risk data at the user level, so that the risk parameter generated based on the yield loss parameter is more practical in the specific business object processing scenario, which helps to generate the processing result of the business object according to the comparison result of the risk parameter and the preset risk threshold, so as to be suitable for various types of business object processing scenarios, thereby improving the universality of the business object processing method. In addition, compared with the technical means of calculating economic capital by using the VaR model to generate the risk parameter in the traditional technology, the business object processing method provided by the present disclosure generates the risk parameter of the business object by using the business object data, the user risk data, and the business period corresponding to the business object. Not only can the generation difficulty of the risk parameter be simplified to improve the operability of the business object processing method, but also the generation efficiency of the risk parameter can be improved, thereby further improving the processing efficiency of the business object.

[0090] In one embodiment provided by the present disclosure, the business period includes a plurality of business processing stages. As shown in Figure 2 Step S106, according to the business object data and the user risk data, the yield loss parameter corresponding to the business period is generated, including:

[0091] Step S202, each business processing stage in the business period is determined.

[0092] In step S204, the income and loss parameters corresponding to each business processing stage are generated according to the business object data and the user risk data.

[0093] Specifically, the server can determine the business cycle of the business object according to the business object data. In the case where the business cycle includes a plurality of business processing stages, each business processing stage in the business cycle is determined. The business object data and the user risk data are processed to generate the income and loss parameters of the business object in each business processing stage. The income and loss parameters in each business processing stage are processed to generate the income and loss parameters of the business object in the entire business cycle.

[0094] In one example, in the case where the type of the business object is a installment type, the server can divide the processing period of the business object according to the installment number of the business object to obtain each business processing stage in the business cycle. For example, the business object A is a installment type product with a installment number of twelve times, and the processing period of the business object A is one year. The server divides the processing period according to the installment number to determine that the business cycle of the business object A is one year, and each business processing stage in the business cycle is one month. The business object data and the user risk data are processed to determine the income and loss parameters of the business object A in each month. The income and loss parameters of the business object A in each month are accumulated to obtain the sum of the income and loss parameters as the income and loss parameters of the business object A in the business cycle.

[0095] In this embodiment, by determining each business processing stage in the business cycle and generating the income and loss parameters corresponding to each business processing stage, the business characteristics of confirming the income and loss of the installment business object are combined, the income and loss parameters in each business processing stage are determined respectively, thereby improving the accuracy of the income and loss parameters, and further facilitating the processing of the installment type business object, thereby improving the universality of the business object processing method.

[0096] In one embodiment provided by the present disclosure, as shown in Figure 3 Step S106, the income and loss parameters corresponding to the business cycle are generated according to the business object data and the user risk data, including:

[0097] In step S302, the amount parameter corresponding to the business cycle is determined according to the business object data.

[0098] The amount parameter can include, but is not limited to, any one or more of the following parameters: principal of the business object, interest of the business object, and remaining principal of the business object.

[0099] Specifically, the server stores an amount parameter generation logic. The amount parameter generation logic is used to process the business object data to generate the amount parameter corresponding to the business period. The amount parameter generation logic can be configured to determine the principal, interest rate and processing period of the business object according to the business object data, perform operation processing on the principal, interest rate and processing period of the business object, and generate the amount parameter corresponding to the business period; or compare the business object data with a preset amount threshold to determine the amount range corresponding to the business object data, and generate the amount parameter corresponding to the business period according to the corresponding amount range.

[0100] In step S304, the default parameter corresponding to the business period is determined according to the user risk data.

[0101] The default parameter can include, but is not limited to, any one or more of the following parameters: user default probability, default loss of the business object, and default loss rate of the business object.

[0102] Specifically, the server can store a risk assessment model and a default parameter generation logic. The user risk data is input into the risk assessment model to determine the risk score corresponding to the user risk data. The risk probability corresponding to the risk score is obtained, and the default parameter generation logic is used to judge the risk probability to generate the default parameter corresponding to the business period. The default parameter generation logic can be configured to compare the risk probability with a probability threshold to generate the default parameter corresponding to the risk probability according to the comparison result, or input the risk probability of the business object into a Markov chain model to determine the exponential distribution of the risk probability, and generate the default parameter corresponding to the risk probability according to the exponential distribution of the risk probability.

[0103] In step S306, the yield loss parameter is generated according to the amount parameter and the default parameter.

[0104] Specifically, the server can perform operation processing on the amount parameter and the default parameter to generate the yield loss parameter. The specific method for generating the yield loss parameter can be implemented by referring to the yield loss parameter generation operation provided in the above embodiments, and will not be described in detail here.

[0105] In this embodiment, the business object data is processed to generate the amount parameter corresponding to the business period, the user risk data is processed to generate the default parameter corresponding to the business period, and the yield loss parameter is generated according to the amount parameter and the default parameter, which can improve the accuracy of the yield loss parameter and thus improve the accuracy of the risk parameter generated by using the yield loss parameter.

[0106] In one embodiment provided in the present disclosure, the default parameter includes a default rate, the amount parameter includes an interest parameter, and the yield loss parameter includes a yield parameter.

[0107] In step S106, the yield loss parameter is generated according to the amount parameter and the default parameter, including:

[0108] The yield parameter is obtained by the following formula:

[0109]

[0110] Wherein, EP is the yield parameter, which can be used to represent the mathematical expectation of the total interest of the business object under the premise that the user does not default in each business processing stage. n is the number of business processing stages in the business cycle of the business object, i is the serial number of the business processing stage, P i is the default rate corresponding to the i th business processing stage of the business object, I i is the interest parameter corresponding to the i th business processing stage of the business object.

[0111] Specifically, the server can process the user risk data to determine the default rate corresponding to each business processing stage of the business object. The business object data is processed to determine the number of business processing stages in the business cycle of the business object, the principal of the business object, the interest rate of the business object. The principal of the business object and the interest rate of the business object are operated and processed to generate the interest parameter corresponding to each business processing stage of the business object. The default rate and the interest parameter corresponding to each business processing stage of the business object are operated and processed to generate the yield parameter of the business object.

[0112] In one example, when the business processing stage of the business object is 1, that is, in the case of a one-period product, the server can obtain the yield parameter by the following formula:

[0113] EP = (1 - P) I

[0114] Wherein, EP is the yield parameter, P is the default rate, and I is the interest parameter.

[0115] In the traditional method, the yield expectation of the business object generated by the operation and processing of the customer default probability and the interest of the business object is used as the yield parameter. Compared with the traditional method, the yield loss parameter generation method provided in the embodiment can obtain the default rate and the interest parameter under each business processing stage to generate the yield parameter, which can not only be applied to the application scenarios of the equal principal and interest or equal principal and capital type of business object, but also be applied to the application scenarios of the interest first and principal later or one-time principal and interest type of business object, thereby improving the universality of the business object processing method.

[0116] In one embodiment provided in the disclosure, the default parameter includes the default rate and the default loss rate, the amount parameter includes the remaining principal, and the yield loss parameter includes the loss parameter.

[0117] In step S106, the yield loss parameter is generated according to the amount parameter and the default parameter, including:

[0118] The loss parameter is obtained by the following formula:

[0119]

[0120] Wherein, EL is the loss parameter, which can be used to represent the mathematical expectation of the principal loss of the business object under the premise of user default. n is the number of business processing stages in the business cycle of the business object, i is the serial number of the business processing stage, P i is the default rate corresponding to the i th business processing stage of the business object, B i is the remaining principal corresponding to the i th business processing stage of the business object, LGD i is the default loss rate corresponding to the i th business processing stage of the business object.

[0121] Specifically, the server can process the user risk data to determine the default rate and historical collection efficiency corresponding to the user risk data. The historical collection efficiency is input into the machine learning model to generate the default loss rate corresponding to the historical collection efficiency. The business object data is processed to determine the remaining principal corresponding to each business processing stage of the business object. The default rate, remaining principal and default loss rate corresponding to each business processing stage of the business object are calculated and processed to generate the loss parameter of the business object.

[0122] In one example, when the business processing stage of the business object is 1, i.e. in the case of a one-period product, the server can obtain the loss parameter by the following formula:

[0123] EL = P * A

[0124] Wherein, EL is the loss parameter, P is the default rate, and A is the principal of the business object.

[0125] In the traditional method, the loss parameter is generated by calculating the client default probability and the remaining principal of the business object. The loss expectation of the generated business object is used as the loss parameter. Compared with the traditional method, the yield loss parameter generation method provided in the embodiment can obtain the default rate, remaining principal and default loss rate under each business processing stage to generate the loss parameter, which can not only be applied to the application scenarios of the equal principal and interest or equal principal type of business object, but also be applied to the application scenarios of the interest first and principal later or one-time principal and interest type of business object, thereby improving the universality of the business object processing method.

[0126] In one embodiment provided in the present disclosure, as Figure 4As shown, in step S108, the risk parameter of the business object is generated according to the yield loss parameter, including:

[0127] In step S402, the cost parameter corresponding to the business object is obtained.

[0128] In step S404, the business cost of the business object is generated according to the cost parameter and the business object data.

[0129] In step S406, the yield loss parameter, the business cost and the business object data are processed to generate the risk parameter.

[0130] The cost parameter can be used to represent the data relationship between the principal and the business cost of the business object.

[0131] The business cost can include, but is not limited to, any one or more of the operation cost, the customer acquisition cost, the fund cost and the value-added tax.

[0132] Specifically, the server obtains the cost parameter corresponding to the business object, processes the business object data using the cost parameter to generate the business cost of the business object. The yield loss parameter, the business cost and the business object data are processed to obtain the difference between the yield loss parameter and the business cost, and the risk parameter is generated by processing the difference between the yield loss parameter and the business cost and the business object data.

[0133] In one example, the server can obtain a first cost parameter corresponding to the operation cost, process the principal of the business object using the first cost parameter to generate the operation cost of the business object. A second cost parameter corresponding to the customer acquisition cost is obtained, and the principal of the business object is processed using the second cost parameter to generate the customer acquisition cost of the business object. A third cost parameter corresponding to the fund cost is obtained, and the remaining principal of the business object at each business processing stage is processed using the third cost parameter to generate the fund cost of the business object. A fourth cost parameter corresponding to the value-added tax is obtained, and the interest parameter of the business object at each business processing stage is processed using the fourth cost parameter to generate the value-added tax of the business object.

[0134] In the traditional method, economic cost is generated by the VaR model, and the expected income, expected loss, cost and economic cost of the business object are calculated and processed to generate the risk parameter of the business object. However, when the risk parameter generation method in the traditional method is used, the business operation department may lack data on market risk and operational risk, and thus cannot establish a VaR model, thereby reducing the operability of the risk parameter generation method. The risk parameter generation method provided in the embodiment can generate business cost through cost parameters, unify the data dimensions of business cost and business object data, facilitate subsequent generation of risk parameters, replace economic cost with business object data to generate risk parameters, simplify the generation of risk parameters, improve the operability of the risk parameter generation step, and make the risk parameter more intuitive in reflecting the return on investment of the business object after risk adjustment in mathematical definition.

[0135] In one embodiment provided in the present disclosure, as shown in Figure 5 A processing method of a business object is provided, including:

[0136] In step S502, in response to a processing request for a business object, business object data and user risk data are obtained.

[0137] In step S504, an amount parameter and a default parameter corresponding to each business processing stage are determined, and an income and loss parameter is generated according to the amount parameter and the default parameter.

[0138] Specifically, the server can obtain business object data and user risk data in response to a processing request for a business object. Each business processing stage in the business cycle of the business object is determined according to the business object data. The user risk data is processed to generate a default rate and a default loss rate corresponding to each business processing stage. The business object data is processed to generate an interest parameter and a remaining principal corresponding to each business processing stage. The default rate and the remaining principal corresponding to each business processing stage are calculated and processed to generate an income parameter of the business object. The default rate, the default loss rate and the remaining principal corresponding to each business processing stage are calculated and processed to generate a loss parameter of the business object. The difference between the income parameter and the loss parameter is obtained, and the difference between the income parameter and the loss parameter is taken as the income and loss parameter of the business object. The specific generation of the income and loss parameter can be realized by the income and loss parameter generation method provided in the above embodiment, and details are not repeated here.

[0139] In step S506, a business cost of the business object is generated according to the cost parameter and the business object data.

[0140] In step S508, the income and loss parameter, the business cost and the business object data are calculated and processed to generate a risk parameter.

[0141] Step S510, in response to the comparison result of the risk parameter and the preset risk threshold, a processing result of the business object is generated.

[0142] Specifically, the server can obtain a plurality of cost parameters, and perform operation processing on the business object data by using each cost parameter respectively to generate a business cost corresponding to each cost parameter. The profit loss parameter, the business cost and the business object data are operated and processed to generate a risk parameter. The risk parameter is compared with the preset risk threshold to generate a comparison result of the risk parameter and the preset risk threshold. In response to the comparison result of the risk parameter and the preset risk threshold, a processing result of the business object is generated. The specific processing result generation operation can be realized by referring to the processing result generation method provided in the above embodiments, and will not be specifically described here.

[0143] In one example, the server can generate the risk parameter by using the following formula:

[0144]

[0145] wherein RAROC (Risk Adjusted Return on Capital) is the risk parameter, n is the number of business processing stages in the business cycle of the business object, i is the serial number of the business processing stage, P i is the default rate corresponding to the i-th business processing stage of the business object, I i is the interest parameter corresponding to the i-th business processing stage of the business object, B i is the remaining principal corresponding to the i-th business processing stage of the business object, LGD i is the default loss rate corresponding to the i-th business processing stage of the business object, C is the principal of the business object, c1 is the first cost parameter corresponding to the operating cost, c2 is the second cost parameter corresponding to the customer acquisition cost, c3 is the third cost parameter corresponding to the fund cost, and c4 is the fourth cost parameter corresponding to the value-added tax.

[0146] In the embodiment, by determining each business processing stage in the business cycle, generating the income parameter and the loss parameter corresponding to each business processing stage, and determining the income and loss parameters of the business object according to the income parameter and the loss parameter, the business characteristics of the income and loss of the installment business object can be combined, and the income and loss parameters in each business processing stage are determined respectively, so as to improve the accuracy of the income and loss parameters, and then facilitate the processing of the installment type business object, so as to improve the universality of the business object processing method. By using the principal of the business object to replace the economic capital to generate the risk parameter, the generation operation of the risk parameter can be simplified, the operability of the risk parameter generation step is improved, and the risk parameter is more intuitive in mathematical definition to reflect the risk-adjusted return rate of the business object. By generating the processing result of the business object in response to the comparison result of the risk parameter and the preset risk threshold, the processing efficiency of the business object can be improved.

[0147] It should be understood that, although each step in the flowchart involved in each embodiment as described above is displayed in sequence according to the arrow, these steps are not necessarily executed in sequence according to the order of the arrow. Unless otherwise specified herein, the execution of these steps is not strictly limited in sequence, and these steps can be executed in other orders. Moreover, at least part of the steps in the flowchart involved in each embodiment as described above can include multiple steps or stages, which are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily sequential, but can be executed alternately or alternately with at least part of other steps or steps or stages in other steps.

[0148] Based on the same inventive concept, the disclosure embodiments also provide a business object processing apparatus for implementing the above-mentioned business object processing method. The problem-solving implementation scheme provided by the apparatus is similar to the implementation scheme described in the above method, so the specific limitations in one or more business object processing apparatus embodiments provided below can refer to the limitations of the business object processing method in the above text, which will not be repeated here.

[0149] In one embodiment provided by the disclosure, as shown in Figure 6 A business object processing apparatus 600 is provided, which comprises a data acquisition module 602, a cycle determination module 604, a loss generation module 606, a risk generation module 608 and a result generation module 610, wherein:

[0150] The data acquisition module 602 is configured to acquire business object data and user risk data in response to a processing request for a business object.

[0151] The period determination module 604 is configured to determine a service period corresponding to the service object.

[0152] The loss generation module 606 is configured to generate a yield loss parameter corresponding to the service period according to the service object data and the user risk data.

[0153] The risk generation module 608 is configured to generate a risk parameter of the service object according to the yield loss parameter.

[0154] The result generation module 610 is configured to generate a processing result of the service object in response to a comparison result of the risk parameter and a preset risk threshold.

[0155] In an embodiment provided by the present disclosure, the service period includes a plurality of service processing stages. The loss generation module 606 is further configured to generate a yield loss parameter corresponding to each service processing stage according to the service object data and the user risk data.

[0156] In an embodiment provided by the present disclosure, the loss generation module 606 includes: a first parameter determination unit configured to determine an amount parameter corresponding to the service period according to the service object data; a second parameter determination unit configured to determine a default parameter corresponding to the service period according to the user risk data; and a parameter generation unit configured to generate the yield loss parameter according to the amount parameter and the default parameter.

[0157] In an embodiment provided by the present disclosure, the default parameter includes a default rate, the amount parameter includes an interest parameter, and the yield loss parameter includes a yield parameter.

[0158] The parameter generation unit is further configured to obtain the yield parameter by the following formula:

[0159]

[0160] wherein EP is the yield parameter, n is a number of service processing stages in the service period of the service object, i is a serial number of the service processing stage, P i is the default rate corresponding to the i th service processing stage of the service object, and I i is the interest parameter corresponding to the i th service processing stage of the service object.

[0161] In an embodiment provided by the present disclosure, the default parameter includes a default rate and a default loss rate, the amount parameter includes a remaining principal, and the yield loss parameter includes a loss parameter.

[0162] The parameter generation unit is further configured to obtain the loss parameter by the following formula:

[0163]

[0164] wherein, EL is a loss parameter, n is a number of business processing stages in a business cycle of the business object, i is a serial number of the business processing stage, P i is a default rate corresponding to the i-th business processing stage of the business object, B i is a remaining principal corresponding to the i-th business processing stage of the business object, LGD i is a default loss rate corresponding to the i-th business processing stage of the business object.

[0165] In an embodiment provided by the present disclosure, the processing apparatus 600 of the business object further comprises a parameter acquisition module configured to acquire a cost parameter corresponding to the business object. The risk generation module 608 comprises a business cost generation unit configured to generate a business cost of the business object according to the cost parameter and the business object data, and a risk parameter generation unit configured to perform operation processing on the yield loss parameter, the business cost and the business object data to generate a risk parameter.

[0166] The modules in the processing apparatus of the business object described above can be implemented by software, hardware and combinations thereof in whole or in part. The modules described above can be embedded in or independent of a processor in a computer device in hardware form, or stored in a memory in a computer device in software form, so as to be called and executed by a processor to perform operations corresponding to the modules.

[0167] In an embodiment provided by the present disclosure, a computer device is provided, which can be a server, and an internal structure diagram of the computer device can be as shown in Figure 7 The computer device comprises a processor, a memory and a network interface connected through a system bus. The processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for running of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is configured to store preset risk threshold data. The network interface of the computer device is configured to communicate with an external terminal through a network connection. The computer program is executed by the processor to implement a processing method of a business object.

[0168] Those skilled in the art can understand that Figure 7 the structure shown in the figure is only a block diagram of part of the structure related to the scheme of the present disclosure, and does not constitute a limitation on the computer device to which the scheme of the present disclosure is applied. A specific computer device can comprise more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0169] In an embodiment provided by the present disclosure, a computer device is also provided, including a memory and a processor, the memory storing a computer program, and the processor implementing the steps in the above method embodiments when executing the computer program.

[0170] In an embodiment provided by the present disclosure, a computer readable storage medium is also provided, storing a computer program, and the computer program implementing the steps in the above method embodiments when executed by a processor.

[0171] In an embodiment provided by the present disclosure, a computer program product is provided, including a computer program, and the computer program implementing the steps in the above method embodiments when executed by a processor.

[0172] 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 for analysis, stored data, displayed data, etc.) involved in the present disclosure are all information and data authorized by the user or authorized by all parties.

[0173] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer readable storage medium, and when the computer program is executed, the processes of the above-mentioned embodiments of the methods can be included. Any reference to memory, database or other medium used in the embodiments provided by the present disclosure can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical storage, high-density embedded non-volatile memory, resistive memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration but not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The database involved in the embodiments provided by the present disclosure can include at least one of a relational database and a non-relational database. The non-relational database can include a distributed database based on a block chain, etc., without being limited thereto. The processor involved in the embodiments provided by the present disclosure can be a general-purpose processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., without being limited thereto.

[0174] Any combination of the technical features of the above embodiments can be made. In order to make the description simple, all possible combinations of the technical features in the above embodiments are not described, however, as long as the combination of the technical features does not exist, it should be considered as the scope of the present disclosure.

[0175] The above embodiments only express several implementation manners of the present disclosure, and the description is more specific and detailed, but it should not be understood as a limitation on the scope of the patent of the present disclosure. It should be pointed out that for ordinary skilled in the art, without departing from the concept of the present disclosure, a number of modifications and improvements can be made, which are within the protection scope of the present disclosure. Therefore, the protection scope of the present disclosure should be subject to the appended claims.

Claims

1. A method for processing business objects, characterized in that, The method includes: In response to processing requests for business objects, obtain business object data and user risk data; Determine the business cycle corresponding to the business object, wherein the business cycle is used to characterize the processing cycle of the business object, and the business cycle includes one or more business processing stages; Based on the business object data, determine the amount parameter corresponding to each business processing stage; based on the user risk data, determine the default parameter corresponding to each business processing stage; and based on the amount parameter and the default parameter, generate the revenue loss parameter corresponding to each business processing stage. Based on the revenue loss parameters, generate the risk parameters for the business object; In response to the comparison result between the risk parameter and the preset risk threshold, a processing result for the business object is generated; The default parameters include the default rate and the default loss rate; the amount parameters include the interest parameter and the remaining principal; and the profit loss parameters include the profit parameter and the loss parameter. The step of generating the revenue loss parameter based on the amount parameter and the default parameter includes: The revenue parameters are obtained using the following formula: Wherein, EP is the revenue parameter, n is the number of business processing stages in the business cycle of the business object, and i is the sequence number of the business processing stage. The default rate is the rate corresponding to the i-th business processing stage of the business object. The interest parameter corresponding to the i-th business processing stage of the business object; The loss parameter is obtained using the following formula: Wherein, EL is the loss parameter, n is the number of business processing stages in the business cycle of the business object, and i is the sequence number of the business processing stage. The default rate is the rate corresponding to the i-th business processing stage of the business object. The remaining principal corresponding to the i-th business processing stage of the business object. The default loss rate is the rate corresponding to the i-th business processing stage of the business object.

2. The method according to claim 1, characterized in that, The method further includes: Obtain the cost parameters corresponding to the business object; The step of generating risk parameters for the business object based on the revenue loss parameters includes: Based on the cost parameters and the business object data, generate the business cost of the business object; The risk parameters are generated by performing calculations on the revenue loss parameters, the business costs, and the business object data.

3. The method according to claim 1, characterized in that, The method further includes: Based on the processing period of the business object in the business object data, generate the business cycle corresponding to the business object; or, Based on the type of the business object in the business object data, generate the business cycle corresponding to the business object.

4. The method according to claim 1, characterized in that, The process of generating the processing result of the business object in response to the comparison result of the risk parameter and the preset risk threshold includes: In response to a comparison result where the risk parameter is greater than the preset risk threshold, a first processing result for the business object is generated; or, In response to a comparison result where the risk parameter is equal to or less than the preset risk threshold, a second processing result for the business object is generated.

5. The method according to claim 1, characterized in that, The method further includes: When the type of the business object is installment type, the processing period of the business object is divided according to the number of installments of the business object to obtain each business processing stage in the business cycle.

6. A processing apparatus for a business object, characterized in that, The device includes: The data acquisition module is used to respond to processing requests for business objects and acquire business object data and user risk data. A cycle determination module is used to determine the business cycle corresponding to the business object. The business cycle is used to characterize the processing cycle of the business object, and the business cycle includes one or more business processing stages. The loss generation module is used to generate revenue loss parameters corresponding to each of the business processing stages based on the business object data and the user risk data. The risk generation module is used to generate risk parameters for the business object based on the revenue loss parameters. The result generation module is used to generate the processing result of the business object in response to the comparison result between the risk parameter and the preset risk threshold; The loss generation module includes: The first parameter determination unit is used to determine the amount parameter corresponding to each of the business processing stages based on the business object data. The second parameter determination unit is used to determine the default parameter corresponding to each of the business processing stages based on the user risk data. The parameter generation unit is used to generate the revenue loss parameter based on the amount parameter and the default parameter; The default parameters include the default rate and the default loss rate; the amount parameters include the interest parameter and the remaining principal; and the profit loss parameters include the profit parameter and the loss parameter. The parameter generation unit is further configured to obtain the revenue parameter using the following formula: Wherein, EP is the revenue parameter, n is the number of business processing stages in the business cycle of the business object, and i is the sequence number of the business processing stage. The default rate is the rate corresponding to the i-th business processing stage of the business object. The interest parameter corresponding to the i-th business processing stage of the business object; The parameter generation unit is further configured to obtain the loss parameter using the following formula: Wherein, EL is the loss parameter, n is the number of business processing stages in the business cycle of the business object, and i is the sequence number of the business processing stage. The default rate is the rate corresponding to the i-th business processing stage of the business object. The remaining principal corresponding to the i-th business processing stage of the business object. The default loss rate is the rate corresponding to the i-th business processing stage of the business object.

7. The apparatus according to claim 6, characterized in that, The device further includes: The parameter acquisition module is used to acquire the cost parameters corresponding to the business object; The risk generation module includes: A business cost generation unit is used to generate the business cost of the business object based on the cost parameters and the business object data. The risk parameter generation unit is used to perform calculations on the revenue loss parameter, the business cost, and the business object data to generate the risk parameter.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 5.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 5.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 5.

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