CN113298398A - Client viscosity evaluation method and device, readable medium and equipment - Google Patents
Client viscosity evaluation method and device, readable medium and equipment Download PDFInfo
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- CN113298398A CN113298398A CN202110603802.1A CN202110603802A CN113298398A CN 113298398 A CN113298398 A CN 113298398A CN 202110603802 A CN202110603802 A CN 202110603802A CN 113298398 A CN113298398 A CN 113298398A
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Abstract
The application discloses a method, a device, a readable medium and equipment for evaluating customer viscosity, wherein the method outputs a bank viscosity index interface; a bank viscosity index interface comprising: a plurality of viscosity indexes under the bank liability category, the bank asset category, the bank transaction category and the bank viscosity product category; setting a weight value of each viscosity index; calculating to obtain the value of the target bank customer under the viscosity index by using the historical customer data associated with the viscosity index and the standard value assignment rule corresponding to the viscosity index; calculating the viscosity of the target bank client under the viscosity index by utilizing the assignment of the target bank client under the viscosity index and the weight value of the viscosity index; and summing the viscosities under each viscosity index, calculating to obtain the viscosity between the target bank client and the bank, and realizing quantitative evaluation of the viscosity between the target bank client and the bank.
Description
Technical Field
The present application relates to the field of information processing technologies, and in particular, to a method and an apparatus for evaluating client viscosity, a readable medium, and a device.
Background
In the prior art, many banks can increase the viscosity of bank customers by promoting preferential activities, increasing loan amounts, promoting new bank products, and the like. The viscosity of a bank customer refers to the degree of closeness between the bank and the bank customer. The higher the viscosity of the bank customer, the more sustainable revenue the bank will bring.
However, due to the lack of a method for quantitatively evaluating the viscosity of a bank client in the prior art, many banks have difficulty in judging whether the implementation of a series of measures for improving the viscosity of the client effectively improves the viscosity of the bank client after the series of measures for improving the viscosity of the client are taken. In addition, many banks do not consider the current viscosity of the bank client in the process of planning a series of measures such as issuing a discount, increasing the credit limit, issuing a new bank product, and the like. For example, individual offers may be more suitable for pushing to customers with higher viscosities, individual products may be more suitable for pushing to customers with lower viscosities, and so on. Therefore, in order to effectively improve the viscosity between the bank customer and the bank, quantitative evaluation of the viscosity of the bank customer needs to be realized.
Disclosure of Invention
Based on the defects of the prior art, the application provides a method, a device, a readable medium and equipment for evaluating client viscosity, so as to improve the construction efficiency of a network scheme.
The application discloses in a first aspect a method for evaluating client viscosity, comprising:
outputting a bank viscosity index interface to a user; wherein, the bank viscosity index interface includes: a plurality of viscosity indicators under a plurality of banking categories; the plurality of banking categories, including: a bank liability category, a bank asset category, a bank transaction category, and a bank viscosity product category; the bank viscosity product category is a business category formed by a plurality of bank products with the highest historical viscosity with a bank client;
responding to weight setting operation executed by a user on the bank viscosity index interface, and setting a weight value of each viscosity index in the bank viscosity index interface; the higher the weight value of the viscosity index is, the higher the importance degree of the viscosity index in evaluating the viscosity between the target bank customer and the bank is;
for each viscosity index, calculating to obtain the value of the target bank customer under the viscosity index by using the historical customer data associated with the viscosity index in the historical customer data of the target bank customer and the standard value assignment rule corresponding to the viscosity index; calculating the viscosity of the target bank customer under the viscosity index by utilizing the assignment of the target bank customer under the viscosity index and the weight value of the viscosity index; the value of the target bank customer under the viscosity index is used for explaining the viscosity reflected by the target bank customer under the viscosity index;
summing the viscosity of the target bank customer under each viscosity index, and calculating to obtain the viscosity between the target bank customer and the bank; and the viscosity between the target bank customer and the bank is used for reflecting the intimacy degree between the target bank customer and the bank.
Optionally, in the method for evaluating client viscosity, the viscosity index is set according to a time influence factor and/or a client data volatility influence factor; the time influence factor is an influence factor caused by the time of generating customer data related to the banking business category on the viscosity; the influence factor of the fluctuation of the customer data is the influence factor of the fluctuation condition of the customer data associated with the banking classes in two adjacent time periods on the viscosity.
Optionally, in the method for evaluating customer viscosity, the viscosity indexes under the banking categories are divided into a plurality of levels;
wherein, the responding to the weight setting operation executed by the user on the bank viscosity index interface, and setting the weight value of each viscosity index in the bank viscosity index interface, includes:
responding to weight setting operation executed by a user on the bank viscosity index interface, and setting a weight value of each level of viscosity index under each banking business category in the bank viscosity index interface;
aiming at each viscosity index, calculating to obtain the value of the target bank customer under the viscosity index by using the historical customer data associated with the viscosity index in the historical customer data of the target bank customer and the standard value assignment rule corresponding to the viscosity index; and calculating the viscosity of the target bank client under the viscosity index by using the assignment of the target bank client under the viscosity index and the weight value of the viscosity index, wherein the calculation comprises the following steps:
aiming at the lowest-level viscosity index under each banking business category, calculating to obtain the value of the target bank client under the lowest-level viscosity index by utilizing the historical client data associated with the lowest-level viscosity index in the historical client data of the target bank client and the standard value assignment rule corresponding to the lowest-level viscosity index; multiplying the value assigned by the target bank client under the lowest-level viscosity index, the weight value corresponding to the lowest-level viscosity index and the weight value corresponding to each level of viscosity index above the lowest-level viscosity index to calculate the viscosity of the target bank client under the lowest-level viscosity index;
the step of summing the viscosities of the target bank customer under each viscosity index and calculating the viscosity between the target bank customer and the bank includes:
and summing the viscosities of the target bank customer under each low-level viscosity index, and calculating to obtain the viscosity between the target bank customer and the bank.
Optionally, in the method for evaluating client viscosity, for each viscosity index, the calculating, by using historical client data associated with the viscosity index in historical client data of a target bank client and a standard assignment rule corresponding to the viscosity index, an assignment of the target bank client under the viscosity index includes:
for each viscosity index, matching historical customer data associated with the viscosity index in the historical customer data of the target bank customer with each assignment rule in standard assignment rules corresponding to the viscosity index respectively to determine an assignment rule matched with the target bank customer, and determining an assignment specified in the assignment rule matched with the target bank customer as the assignment of the target bank customer under the viscosity index; and the assignment rule is used for specifying the assignment corresponding to the historical client data associated with the viscosity index when a specific condition is met.
Optionally, in the method for evaluating the client viscosity, the calculating, by using the value assigned by the target bank client under the viscosity index and the weight value of the viscosity index, the viscosity of the target bank client under the viscosity index includes:
and multiplying the value of the target bank customer under the viscosity index by the weight value of the viscosity index, and calculating to obtain the viscosity of the target bank customer under the viscosity index.
A second aspect of the present application discloses an evaluation device of client viscosity, including:
the output unit is used for outputting a bank viscosity index interface to a user; wherein, the bank viscosity index interface includes: a plurality of viscosity indicators under a plurality of banking categories; the plurality of banking categories, including: a bank liability category, a bank asset category, a bank transaction category, and a bank viscosity product category; the bank viscosity product category is a business category formed by a plurality of bank products with the highest historical viscosity with a bank client;
the setting unit is used for responding to weight setting operation executed by a user on the bank viscosity index interface and setting the weight value of each viscosity index in the bank viscosity index interface; the higher the weight value of the viscosity index is, the higher the importance degree of the viscosity index in evaluating the viscosity between the target bank customer and the bank is;
the first calculation unit is used for calculating to obtain the assignment of the target bank customer under the viscosity index by utilizing the historical customer data associated with the viscosity index in the historical customer data of the target bank customer and the standard assignment rule corresponding to the viscosity index aiming at each viscosity index; calculating the viscosity of the target bank customer under the viscosity index by utilizing the assignment of the target bank customer under the viscosity index and the weight value of the viscosity index; the value of the target bank customer under the viscosity index is used for explaining the viscosity reflected by the target bank customer under the viscosity index;
the second calculation unit is used for summing the viscosity of the target bank customer under each viscosity index, and calculating to obtain the viscosity between the target bank customer and the bank; and the viscosity between the target bank customer and the bank is used for reflecting the intimacy degree between the target bank customer and the bank.
Optionally, in the apparatus for evaluating client viscosity, the viscosity index is set according to a time influence factor and/or a client data volatility influence factor; the time influence factor is an influence factor caused by the time of generating customer data related to the banking business category on the viscosity; the influence factor of the fluctuation of the customer data is the influence factor of the fluctuation condition of the customer data associated with the banking classes in two adjacent time periods on the viscosity.
Optionally, in the evaluation apparatus for client viscosity, the viscosity indexes under the banking categories are divided into a plurality of levels;
wherein, the setting unit includes:
the setting subunit is used for responding to weight setting operation executed by a user on the bank viscosity index interface and setting a weight value of each level of viscosity index under each banking business category in the bank viscosity index interface;
the first calculation unit includes:
the first calculating subunit is configured to calculate, for the lowest-level viscosity index under each banking service category, an assignment of the target bank customer under the lowest-level viscosity index by using historical customer data associated with the lowest-level viscosity index in historical customer data of the target bank customer and a standard assignment rule corresponding to the lowest-level viscosity index; multiplying the value assigned by the target bank client under the lowest-level viscosity index, the weight value corresponding to the lowest-level viscosity index and the weight value corresponding to each level of viscosity index above the lowest-level viscosity index to calculate the viscosity of the target bank client under the lowest-level viscosity index;
the second calculation unit includes:
and the second calculating subunit is configured to sum the viscosities of the target bank customer under each of the lowest-level viscosity indexes, and calculate to obtain the viscosity between the target bank customer and the bank.
Optionally, in the apparatus for evaluating client viscosity, the first calculating unit, when calculating, for each viscosity index, an assignment of a target bank client under the viscosity index by using historical client data associated with the viscosity index in historical client data of the target bank client and a standard assignment rule corresponding to the viscosity index, is configured to:
for each viscosity index, matching historical customer data associated with the viscosity index in the historical customer data of the target bank customer with each assignment rule in standard assignment rules corresponding to the viscosity index respectively to determine an assignment rule matched with the target bank customer, and determining an assignment specified in the assignment rule matched with the target bank customer as the assignment of the target bank customer under the viscosity index; and the assignment rule is used for specifying the assignment corresponding to the historical client data associated with the viscosity index when a specific condition is met.
Optionally, in the apparatus for evaluating client viscosity, the first calculating unit is configured to, when calculating the viscosity of the target bank client under the viscosity index by using the assigned value of the target bank client under the viscosity index and the weight value of the viscosity index,:
and multiplying the value of the target bank customer under the viscosity index by the weight value of the viscosity index, and calculating to obtain the viscosity of the target bank customer under the viscosity index.
A third aspect of the application discloses a computer readable medium having a computer program stored thereon, wherein the program when executed by a processor implements the method as described in any of the first aspects above.
A fourth aspect of the present application discloses an evaluation device of client viscosity, including:
one or more processors;
a storage device having one or more programs stored thereon;
the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method as in any one of the first aspects above.
It can be seen from the foregoing technical solutions that, in the method for evaluating client viscosity provided in the embodiment of the present application, a bank viscosity index interface is output to a user, where the bank viscosity index interface includes: a plurality of viscosity indicators under a plurality of banking categories, the plurality of banking categories comprising: the method comprises the steps of determining the types of bank liability, bank assets, bank transactions and bank viscosity products, responding to weight setting operation executed by a user on a bank viscosity index interface, and setting a weight value of each viscosity index in the bank viscosity index interface, wherein the higher the weight value of the viscosity index is, the higher the importance degree of the viscosity index in evaluating the viscosity between a target bank client and a bank is. Aiming at each viscosity index, calculating to obtain the value of the target bank client under the viscosity index by utilizing the historical client data associated with the viscosity index in the historical client data of the target bank client and the standard value assignment rule corresponding to the viscosity index, multiplying the value of the target bank client under the viscosity index by the weight value of the viscosity index, calculating to obtain the viscosity of the target bank client under the viscosity index, finally summing the viscosities of the target bank client under each viscosity index, and calculating to obtain the viscosity between the target bank client and the bank. According to the embodiment of the application, the viscosity between the target bank customer and the bank is quantitatively evaluated through the viscosity indexes under the bank liability category, the bank asset category, the bank transaction category and the bank viscosity product category, and the requirement for quantitatively evaluating the viscosity of the bank customer in the prior art is met.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
Fig. 1 is a schematic flowchart illustrating a method for evaluating customer viscosity according to an embodiment of the present disclosure;
fig. 2 is a schematic structural diagram of an apparatus for evaluating client viscosity disclosed in an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, the embodiment of the application discloses a method for evaluating client viscosity, which specifically includes the following steps:
s101, outputting a bank viscosity index interface to a user, wherein the bank viscosity index interface comprises: a plurality of viscosity indicators under a plurality of banking categories, the plurality of banking categories including: a bank liability category, a bank asset category, a bank transaction category, and a bank viscosity product category.
The bank viscosity product category is a business category formed by a plurality of bank products with the highest historical viscosity with the bank client. The plurality of bank products with the highest historical viscosity between the bank products and the bank customers can be determined according to historical experience of banking staff, and can also be determined according to the use frequency of the bank customers in historical data of the bank products. The higher the frequency of use of the bank product by the bank customer, the higher the historical viscosity of the bank product.
When the user needs to evaluate the viscosity of the bank client, the output of a bank viscosity index interface can be triggered through the user terminal. For example, a user triggers an evaluation request for generating client viscosity to a user terminal, and then the user terminal responds to the evaluation request for client viscosity and outputs a bank viscosity index interface. Or the user can directly select the output bank viscosity index interface on the user terminal interface.
The interface of the bank viscosity index comprises a plurality of viscosity indexes under the bank liability category, a plurality of viscosity indexes under the bank asset category, a plurality of viscosity indexes under the bank transaction category and viscosity indexes under the bank viscosity product category. The viscosity indexes under the bank liability category are set through the behavior of the bank client on the bank liability plate, and the viscosity between the bank client and the bank in the bank liability category plate is evaluated through the viscosity indexes under the bank liability category. The viscosity indexes under the bank asset category are set through the behavior of the bank client on the bank asset plate, the viscosity between the bank client and the bank in the bank asset plate is evaluated through the viscosity indexes under the bank asset category, and the viscosity indexes under the bank transaction category and the viscosity indexes under the bank viscosity product category are also set in a similar manner. The bank debt category mainly comprises the services of deposit, investment and financing, the bank asset category mainly comprises the services of loan, credit card and the like, the bank transaction category mainly comprises the services of transfer transaction, payment, consumption and the like, the bank viscosity product category mainly comprises the services of a plurality of products with the highest historical viscosity, and the bank viscosity product category also can comprise some interactive relations between bank customers and banks capable of reflecting the viscosity, such as mobile phone banks, shopping malls, support degrees for the banks, relations with bank customer managers and the like.
Optionally, in an embodiment of the present application, when setting the viscosity index, the viscosity index may be set in consideration of a time influence factor and/or a client data volatility influence factor. The time influence factor is the influence factor of the generation time of the customer data associated with the banking business category on the viscosity. Specifically, the closer the generation time of the client data associated with the banking business category is, the more the viscosity of the banking client can be reflected, so that the closer the set time point can be considered when setting the viscosity index, for example, when setting the viscosity index of the banking debt category, the time interval between the latest regular deposit of the banking client and the current time interval or whether the banking client has deposit in the latest month can be set.
The influence factor of the fluctuation of the client data is the influence factor of the fluctuation situation of the client data associated with the banking classes in two adjacent time periods on the viscosity. For example, the viscosity index may be set in consideration of fluctuations of customer data associated with banking classes in two periods adjacent to the key business time point. The critical service time point is the time point that is most critical to the service. Such as a financial key month and a fund key month. When the viscosity index is set for the bank liability class in consideration of influence factors of fluctuation of client data, the viscosity index under the bank liability class can be set to be the fluctuation of the deposit times between the end of the key month of the last quarter deposit in the last 1 year and the end of the month one month before the key month, and the like.
The viscosity indexes under the bank liability category, the bank asset category, the bank transaction category and the bank viscosity product category included in the bank viscosity index interface in the embodiment of the application can reflect the viscosity condition between the bank customer and the bank through different business categories of the bank.
Optionally, in a specific embodiment of the present application, the viscosity indexes under the banking categories are divided into a plurality of levels. Namely, the interface of the bank viscosity index comprises a plurality of levels of viscosity indexes under a plurality of banking classes. The higher the level of the viscosity index, the wider the banking range covered. For example, the plurality of viscosity indexes under the bank liability category may divide the liability category into first-level viscosity indexes, and the liability category may be subdivided into a deposit business category and an investment financing business category, so that both the deposit business category and the investment financing business category are divided into second-level viscosity indexes. The deposit types can be further divided into two three-level viscosity indexes of a current deposit and a periodic deposit, and the four-level viscosity index of the periodic deposit types can be the time interval between the last periodic deposit and the current deposit, whether the bank client carries out the periodic deposit in the last month or not, and the like. Similarly, the investment and financing business category may continue to be ranked down like the deposit business category.
Optionally, the plurality of viscosity indexes under the plurality of banking categories may not be classified, that is, all viscosity indexes under the banking categories are indexes of the same level. For example, the bank liability category may include viscosity indexes such as fluctuation of the deposit times between the end of the key month and the end of the month before the key month in the last quarter of the last year in the last 1 year, whether the deposit is made in the last month, the time interval between the last periodical deposit and the current time interval, and the like.
And S102, responding to weight setting operation executed by a user on the bank viscosity index interface, and setting a weight value of each viscosity index in the bank viscosity index interface, wherein the higher the weight value of the viscosity index is, the higher the importance degree of the viscosity index in evaluating the viscosity between a target bank client and a bank is.
Specifically, the bank viscosity index interface output in step S101 can be used to perform weight setting on the viscosity index. Because the influence of the emphasized business category is different when the viscosity of the bank customer is considered by different users, the interface of the index of the viscosity of the bank can be adjusted by setting the weight. For example, the bank where a certain user is located mainly deals with the business of the bank transaction category, and the business related to the bank liability category is not many, so the importance degree of the bank liability category is not high when the viscosity between the target bank client and the bank is evaluated, but the importance degree of the bank transaction category is high when the viscosity between the target bank client and the bank is evaluated, so the weight value corresponding to the viscosity index in the bank transaction category can be set to be higher, and the weight value corresponding to the viscosity index in the bank liability category can be set to be lower. If the user does not intend to consider the influence of the partial viscosity index on the viscosity between the bank customer and the bank when considering the viscosity between the bank customer and the bank, the weight value corresponding to the partial viscosity index can be set to be zero.
Optionally, in a specific embodiment of the present application, the bank viscosity index interface further displays default weight values corresponding to each viscosity index. The default weight value may be preset according to historical experience. When step S102 is executed, the weight setting operation performed on the bank viscosity index interface by the user may also be to select not to change the weight value, and at this time, the weight value of each viscosity index in the bank viscosity index interface is set as a corresponding default weight value.
Optionally, in an embodiment of the present application, if the viscosity indexes under the multiple banking categories are classified into multiple levels, executing step S102 includes:
and responding to weight setting operation executed by a user on the bank viscosity index interface, and setting the weight value of each level of viscosity index under each banking business category in the bank viscosity index interface. For each viscosity index, the higher the weight value of the viscosity index is, the higher the importance degree of the viscosity between the target bank customer and the bank reflected when the viscosity index higher by one level corresponding to the viscosity index is evaluated is. For example, the bank liability category has two viscosity indexes of deposit and investment and financing, and the higher the weight value corresponding to the deposit is, the higher the importance degree of the deposit index is when the viscosity reflected by the bank liability category is evaluated.
And the sum of the weighted values of the viscosity indexes at the same level is a fixed value. For example, referring to table one, the weight value corresponding to the bank liability category in the first-level viscosity index is set to 30%, the weight value corresponding to the bank asset category is set to 25%, the weight value corresponding to the bank transaction category is set to 28%, and the weight value corresponding to the bank viscosity product category is set to 17%. Then, the weight value corresponding to the deposit viscosity index in the second-level viscosity indexes under the bank liability category is 60%, the weight value corresponding to the investment and financing is 40%, and the third-level index under the deposit category is the deposit, so that the corresponding weight value is 100%, the fourth-level index under the deposit category has two indexes of 'whether there is a periodic deposit' and 'the current time of the latest periodic deposit', and the weight values corresponding to the two viscosity indexes are both 50%. Similarly, the weight value of the second-level index loan category under the bank property category is set to 40%, the weight value corresponding to the credit card category is set to 60%, and the third-level index under the loan category is also the loan category, the weight value is 100%, and the third-level index under the credit card category is also the credit card category, and the weight value is also 100%. The four-level index under the loan category is 'whether the individual housing loan is held', the corresponding weight value is 100%, the four-level index under the credit card category is 'the transaction number of the credit card of nearly 1 month', and the corresponding weight value is 100%. Similarly, the consumption category of the second-level indicator in table one is set to 40%, the weight value of the consumption of the third-level indicator is 100%, and the weight value corresponding to the fourth-level indicator "number of consumption strokes of debit card for 1 month only" in the consumption category is set to 100%. The weight value of the second-level index payment category is set to be 60%, the weight value of the lower third-level index payment category is 100%, and the weight value of the fourth-level index 'the number of hydropower coal payment strokes in about 1 month' is 100%. The second-level index account age has a weight of 30%, the third-level index client account age has a weight of 100%, and the fourth-level index client account age has a weight of 100%. The weight value of the second-level index viscosity product is 70%, the weight value of the third-level index mobile phone bank is 100%, and the weight value corresponding to the fourth-level index 'login times of nearly 1 month' is 100%.
Watch 1
As can be seen from table one above, the sum of the weight values corresponding to all viscosity indexes one level lower than one viscosity index is 100%. For example, the sum of the weighted values corresponding to the secondary indicators "deposit" and "investment financing" in the bank liability category in table one is 100%.
S103, aiming at each viscosity index, calculating to obtain the value of the target bank client under the viscosity index by using the historical client data associated with the viscosity index in the historical client data of the target bank client and the standard value assignment rule corresponding to the viscosity index, and calculating to obtain the viscosity of the target bank client under the viscosity index by using the value assignment of the target bank client under the viscosity index and the weight value of the viscosity index.
And the value of the target bank client under the viscosity index is used for explaining the viscosity reflected by the target bank client under the viscosity index. The target bank customer refers to a customer who needs to determine the viscosity with the bank. The standard assignment rule corresponding to the viscosity index specifies the assignment corresponding to the historical client data associated with the viscosity index in the historical client data of the target bank client, so that the assignment of the target bank client under the viscosity index can be calculated by using the historical client data associated with the viscosity index in the historical client data of the target bank client and the standard assignment rule corresponding to the viscosity index. For example, in the viscosity index "whether there is a fixed deposit" in table one, the corresponding standard assignment rule may be that if there is a fixed deposit, the corresponding assignment is 5, and if there is no fixed deposit, the corresponding assignment is 1.
The importance degree of the viscosity index when evaluating the viscosity between the target bank client and the bank can be reflected by the weighted value of the viscosity index, and the value of the target bank client under the viscosity index can also indicate the viscosity reflected by the target bank client under the viscosity index, so that the viscosity of the target bank client under the viscosity index can be calculated by utilizing the value of the target bank client under the viscosity index and the weighted value of the viscosity index. The viscosity of the target bank client under the viscosity index refers to the viscosity between the target bank client and the bank reflected under the viscosity index.
Optionally, in a specific embodiment of the present application, an implementation manner of performing, in step S103, calculation to obtain the viscosity of the target bank customer under the viscosity index by using the value assigned by the target bank customer under the viscosity index and the weight value of the viscosity index includes:
and multiplying the value of the target bank customer under the viscosity index by the weight value of the viscosity index, and calculating to obtain the viscosity of the target bank customer under the viscosity index.
If the plurality of viscosity indexes under the plurality of banking business categories are not graded, namely all the viscosity indexes are in the same grade, the assignment of the target bank client under the viscosity indexes can be directly multiplied by the weight values of the viscosity indexes, and the viscosity of the target bank client under the viscosity indexes is obtained through calculation. The value of the target bank client under the viscosity index is used for indicating the viscosity reflected by the target bank client under the viscosity index, the higher the weight value of the viscosity index is, the higher the importance degree of the viscosity index when evaluating the viscosity between the target bank client and the bank is, and the viscosity indexes are not graded, so that the value of the target bank client under the viscosity index is multiplied by the weight value of the viscosity index, and the viscosity of the target bank client under the viscosity index can be obtained.
Optionally, in an embodiment of the present application, if the viscosity indexes under the multiple banking categories are divided into multiple levels, an implementation manner of step S103 is executed, where the implementation manner includes:
aiming at the lowest-level viscosity index under each banking business category, calculating to obtain the assignment of the target bank client under the lowest-level viscosity index by utilizing the historical client data associated with the lowest-level viscosity index in the historical client data of the target bank client and the standard assignment rule corresponding to the lowest-level viscosity index, multiplying the assignment of the target bank client under the lowest-level viscosity index, the weight value corresponding to the lowest-level viscosity index and the weight value corresponding to each level of viscosity index above the lowest-level viscosity index by each other, and calculating to obtain the viscosity of the target bank client under the lowest-level viscosity index.
The level of the viscosity index is actually a classification level, and the higher the level, the wider the range of viscosity evaluation covered. And the lowest-level viscosity index is an index used in the actual quantitative evaluation of viscosity. Therefore, when step S103 is executed, the lowest-level viscosity index is executed for each banking category, and the standard assignment rule is also set for the lowest-level viscosity index. And the weight value corresponding to the viscosity index reflects the importance degree of the viscosity between the target bank client and the bank when the viscosity index higher by one level is evaluated. And the importance degree of the lowest-level viscosity index when evaluating the viscosity between the target bank customer and the bank is represented by an actual weight value obtained by multiplying the weight value corresponding to the lowest-level viscosity index by the weight value corresponding to each level of viscosity index above the lowest-level viscosity index. For example, referring to the above table one, the lowest level is four levels, and the actual weight of the viscosity index of "presence or absence of a fixed deposit" in the four-level indexes when the viscosity between the target bank client and the bank is evaluated is obtained by multiplying the weight values corresponding to the first-level index bank liability category, the second-level index deposit, the third-level index deposit, and the fourth-level index "presence or absence of a fixed deposit", that is, the actual weight value y corresponding to the viscosity index of "presence or absence of a fixed deposit" is 30% × 60% × 100% × 50% × 9%.
Optionally, in a specific embodiment of the present application, an implementation manner of performing, for each viscosity index in step S103, calculating, by using historical client data associated with the viscosity index in the historical client data of the target bank client and a standard assignment rule corresponding to the viscosity index, an assignment of the target bank client under the viscosity index is obtained, where the implementation manner includes:
and aiming at each viscosity index, matching the historical client data associated with the viscosity index in the historical client data of the target bank client with each assignment rule in the standard assignment rules corresponding to the viscosity index respectively to determine the assignment rule matched with the target bank client, and determining the assignment specified in the assignment rule matched with the target bank client as the assignment of the target bank client under the viscosity index.
The assignment rule is used for specifying the assignment corresponding to the historical client data associated with the viscosity index when the historical client data meets a specific condition. And determining an assignment rule matched with the target bank client from the standard assignment rule corresponding to the viscosity index through matching of the historical client data associated with the viscosity index in the historical client data of the target bank client, and determining the assignment of the target bank client under the viscosity index through the matched assignment rule.
For example, if a certain viscosity index is "the time from the last periodic deposit to the present time", three standard assignment rules corresponding to the index may be set, one is that the time from the last periodic deposit to the present time is assigned to 5 within 1 month, the second is that the time from the last periodic deposit to the present time is assigned to 3 within 1 to 3 months, and the third is that the time from the last periodic deposit to the present time is assigned to 1 within more than 3 months. And the historical customer data associated with the viscosity index in the historical customer data of the target bank customer reflects that the current time of the last periodic deposit distance of the target bank customer is 6 months, so that the matching is a third assignment rule, and the assignment of the target bank customer under the viscosity index is 1.
And S104, summing the viscosities of the target bank customer under each viscosity index, and calculating to obtain the viscosity between the target bank customer and the bank.
And the viscosity between the target bank client and the bank is used for reflecting the intimacy degree between the target bank client and the bank. The viscosity under the viscosity index reflects the intimacy degree of the target bank customer when the target bank customer is evaluated by using the viscosity index. And the viscosity between the target bank client and the bank is obtained by integrating the viscosities of the target bank client under all viscosity indexes, so that the viscosities of the target bank client under each viscosity index can be summed, and the viscosity between the target bank client and the bank can be calculated.
Optionally, in an embodiment of the present application, if the viscosity indexes under the multiple banking categories are classified into multiple levels, executing step S104 includes:
and summing the viscosities of the target bank customer under each lowest-level viscosity index, and calculating to obtain the viscosity between the target bank customer and the bank.
In the method for evaluating customer viscosity provided by the embodiment of the application, a bank viscosity index interface is output to a user, wherein the bank viscosity index interface comprises: a plurality of viscosity indicators under a plurality of banking categories, the plurality of banking categories comprising: the method comprises the steps of determining the types of bank liability, bank assets, bank transactions and bank viscosity products, responding to weight setting operation executed by a user on a bank viscosity index interface, and setting a weight value of each viscosity index in the bank viscosity index interface, wherein the higher the weight value of the viscosity index is, the higher the importance degree of the viscosity index in evaluating the viscosity between a target bank client and a bank is. Aiming at each viscosity index, calculating to obtain the value of the target bank client under the viscosity index by utilizing the historical client data associated with the viscosity index in the historical client data of the target bank client and the standard value assignment rule corresponding to the viscosity index, multiplying the value of the target bank client under the viscosity index by the weight value of the viscosity index, calculating to obtain the viscosity of the target bank client under the viscosity index, finally summing the viscosities of the target bank client under each viscosity index, and calculating to obtain the viscosity between the target bank client and the bank. According to the embodiment of the application, the viscosity between the target bank customer and the bank is quantitatively evaluated through the viscosity indexes under the bank liability category, the bank asset category, the bank transaction category and the bank viscosity product category, and the requirement for quantitatively evaluating the viscosity of the bank customer in the prior art is met.
Referring to fig. 2, based on the evaluation method of client viscosity provided in the embodiment of the present application, the embodiment of the present application correspondingly discloses an evaluation apparatus of client viscosity, which includes: an output unit 201, a setting unit 202, a first calculation unit 203, and a second calculation unit 204.
Output unit 201 is used for outputting bank viscosity index interface to the user, wherein, bank viscosity index interface includes: a plurality of viscosity indicators under a plurality of banking categories. A plurality of banking categories comprising: the bank account type, the bank asset type, the bank transaction type and the bank viscosity product type, wherein the bank viscosity product type is a business type formed by a plurality of bank products with the highest historical viscosity with the bank client.
Optionally, in an embodiment of the present application, the viscosity index is set according to a time influence factor, and/or a client data volatility influence factor. The time influence factor is an influence factor brought by the generation time of the client data associated with the banking business category to the viscosity, and the client data fluctuation influence factor is an influence factor brought by the fluctuation condition of the client data associated with the banking business category in two adjacent time periods to the viscosity.
The setting unit 202 is configured to set a weight value of each viscosity index in the bank viscosity index interface in response to a weight setting operation performed by a user on the bank viscosity index interface. Wherein, the higher the weight value of the viscosity index is, the higher the importance degree of the viscosity index in evaluating the viscosity between the target bank customer and the bank is.
The first calculating unit 203 is configured to calculate, for each viscosity index, an assignment of the target bank client under the viscosity index by using historical client data associated with the viscosity index in the historical client data of the target bank client and a standard assignment rule corresponding to the viscosity index, and calculate a viscosity of the target bank client under the viscosity index by using the assignment of the target bank client under the viscosity index and a weight value of the viscosity index. And the value of the target bank client under the viscosity index is used for explaining the viscosity reflected by the target bank client under the viscosity index.
Optionally, in an embodiment of the present application, the first calculating unit 203 is configured to, when calculating the viscosity of the target bank customer under the viscosity index by using the assigned value of the target bank customer under the viscosity index and the weight value of the viscosity index,:
and multiplying the value of the target bank customer under the viscosity index by the weight value of the viscosity index, and calculating to obtain the viscosity of the target bank customer under the viscosity index.
Optionally, in a specific embodiment of the present application, the first calculating unit 203 executes, for each viscosity index, when calculating, by using historical client data associated with the viscosity index in the historical client data of the target bank client and a standard assignment rule corresponding to the viscosity index, an assignment of the target bank client under the viscosity index, to:
and aiming at each viscosity index, matching the historical client data associated with the viscosity index in the historical client data of the target bank client with each assignment rule in the standard assignment rules corresponding to the viscosity index respectively to determine the assignment rule matched with the target bank client, and determining the assignment specified in the assignment rule matched with the target bank client as the assignment of the target bank client under the viscosity index. The assignment rule is used for specifying the assignment corresponding to the historical client data associated with the viscosity index when the historical client data meets a specific condition.
And the second calculating unit 204 is configured to sum the viscosities of the target bank customer under each viscosity index, and calculate to obtain the viscosity between the target bank customer and the bank. And the viscosity between the target bank client and the bank is used for reflecting the intimacy degree between the target bank client and the bank.
Optionally, in a specific embodiment of the present application, the viscosity indexes under the banking categories are divided into a plurality of levels. Wherein, the setting unit 202 includes: and the setting subunit is used for responding to weight setting operation executed by a user on the bank viscosity index interface and setting the weight value of each level of viscosity index under each banking business category in the bank viscosity index interface. A first calculation unit 203, comprising: the first calculating subunit is configured to calculate, for the lowest-level viscosity index under each banking category, an assignment of the target bank client under the lowest-level viscosity index by using historical client data associated with the lowest-level viscosity index in the historical client data of the target bank client and a standard assignment rule corresponding to the lowest-level viscosity index, and multiply the assignment of the target bank client under the lowest-level viscosity index, a weight value corresponding to the lowest-level viscosity index, and a weight value corresponding to each level of viscosity index above the lowest-level viscosity index by each other to calculate a viscosity of the target bank client under the lowest-level viscosity index. A second computing unit 204, comprising: and the second calculating subunit is used for summing the viscosities of the target bank customer under each lowest-level viscosity index, and calculating to obtain the viscosity between the target bank customer and the bank.
The specific principle and the implementation process of each unit in the apparatus for evaluating client viscosity disclosed in the embodiment of the present application are the same as those of the method for evaluating client viscosity disclosed in the embodiment of the present application, and reference may be made to corresponding parts in the method for evaluating client viscosity disclosed in the embodiment of the present application, and details are not repeated here.
In the evaluation device of customer viscosity that this application embodiment provided, export bank viscosity index interface to the user through output element 201, wherein bank viscosity index interface includes: a plurality of viscosity indicators under a plurality of banking categories, the plurality of banking categories comprising: the setting unit 202 is configured to respond to a weight setting operation performed by a user on a bank viscosity index interface, and set a weight value of each viscosity index in the bank viscosity index interface, where a higher weight value of a viscosity index indicates a higher importance degree of the viscosity index in evaluating the viscosity between a target bank customer and a bank. The first calculating unit 203 calculates, for each viscosity index, an assignment of the target bank client under the viscosity index by using historical client data associated with the viscosity index in the historical client data of the target bank client and a standard assignment rule corresponding to the viscosity index, multiplies the assignment of the target bank client under the viscosity index by a weight value of the viscosity index to calculate a viscosity of the target bank client under the viscosity index, and finally the second calculating unit 204 sums the viscosities of the target bank clients under each viscosity index to calculate a viscosity between the target bank client and the bank. According to the embodiment of the application, the viscosity between the target bank customer and the bank is quantitatively evaluated through the viscosity indexes under the bank liability category, the bank asset category, the bank transaction category and the bank viscosity product category, and the requirement for quantitatively evaluating the viscosity of the bank customer in the prior art is met.
The application discloses a computer readable medium, on which a computer program is stored, wherein the program, when executed by a processor, implements a method for assessing client viscosity as described in any of the above embodiments.
The application also discloses customer viscosity's assessment equipment includes: one or more processors, a storage device, one or more programs stored thereon, which when executed by the one or more processors, cause the one or more processors to implement the method for assessing client viscosity as described in any of the embodiments above.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
It is further noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
Claims (10)
1. A method for assessing customer viscosity, comprising:
outputting a bank viscosity index interface to a user; wherein, the bank viscosity index interface includes: a plurality of viscosity indicators under a plurality of banking categories; the plurality of banking categories, including: a bank liability category, a bank asset category, a bank transaction category, and a bank viscosity product category; the bank viscosity product category is a business category formed by a plurality of bank products with the highest historical viscosity with a bank client;
responding to weight setting operation executed by a user on the bank viscosity index interface, and setting a weight value of each viscosity index in the bank viscosity index interface; the higher the weight value of the viscosity index is, the higher the importance degree of the viscosity index in evaluating the viscosity between the target bank customer and the bank is;
for each viscosity index, calculating to obtain the value of the target bank customer under the viscosity index by using the historical customer data associated with the viscosity index in the historical customer data of the target bank customer and the standard value assignment rule corresponding to the viscosity index; calculating the viscosity of the target bank customer under the viscosity index by utilizing the assignment of the target bank customer under the viscosity index and the weight value of the viscosity index; the value of the target bank customer under the viscosity index is used for explaining the viscosity reflected by the target bank customer under the viscosity index;
summing the viscosity of the target bank customer under each viscosity index, and calculating to obtain the viscosity between the target bank customer and the bank; and the viscosity between the target bank customer and the bank is used for reflecting the intimacy degree between the target bank customer and the bank.
2. The method of claim 1, wherein the viscosity index is set in accordance with a time factor, and/or a customer data volatility factor; the time influence factor is an influence factor caused by the time of generating customer data related to the banking business category on the viscosity; the influence factor of the fluctuation of the customer data is the influence factor of the fluctuation condition of the customer data associated with the banking classes in two adjacent time periods on the viscosity.
3. The method of claim 1, wherein the plurality of viscosity indicators under the plurality of banking categories are divided into a plurality of levels;
wherein, the responding to the weight setting operation executed by the user on the bank viscosity index interface, and setting the weight value of each viscosity index in the bank viscosity index interface, includes:
responding to weight setting operation executed by a user on the bank viscosity index interface, and setting a weight value of each level of viscosity index under each banking business category in the bank viscosity index interface;
aiming at each viscosity index, calculating to obtain the value of the target bank customer under the viscosity index by using the historical customer data associated with the viscosity index in the historical customer data of the target bank customer and the standard value assignment rule corresponding to the viscosity index; and calculating the viscosity of the target bank client under the viscosity index by using the assignment of the target bank client under the viscosity index and the weight value of the viscosity index, wherein the calculation comprises the following steps:
aiming at the lowest-level viscosity index under each banking business category, calculating to obtain the value of the target bank client under the lowest-level viscosity index by utilizing the historical client data associated with the lowest-level viscosity index in the historical client data of the target bank client and the standard value assignment rule corresponding to the lowest-level viscosity index; multiplying the value assigned by the target bank client under the lowest-level viscosity index, the weight value corresponding to the lowest-level viscosity index and the weight value corresponding to each level of viscosity index above the lowest-level viscosity index to calculate the viscosity of the target bank client under the lowest-level viscosity index;
the step of summing the viscosities of the target bank customer under each viscosity index and calculating the viscosity between the target bank customer and the bank includes:
and summing the viscosities of the target bank customer under each low-level viscosity index, and calculating to obtain the viscosity between the target bank customer and the bank.
4. The method according to claim 1, wherein for each of the viscosity indexes, calculating an assignment of the target bank customer under the viscosity index by using historical customer data associated with the viscosity index in historical customer data of the target bank customer and a standard assignment rule corresponding to the viscosity index includes:
for each viscosity index, matching historical customer data associated with the viscosity index in the historical customer data of the target bank customer with each assignment rule in standard assignment rules corresponding to the viscosity index respectively to determine an assignment rule matched with the target bank customer, and determining an assignment specified in the assignment rule matched with the target bank customer as the assignment of the target bank customer under the viscosity index; and the assignment rule is used for specifying the assignment corresponding to the historical client data associated with the viscosity index when a specific condition is met.
5. The method according to claim 1, wherein the calculating the viscosity of the target bank customer at the viscosity index using the assigned value of the target bank customer at the viscosity index and the weight value of the viscosity index comprises:
and multiplying the value of the target bank customer under the viscosity index by the weight value of the viscosity index, and calculating to obtain the viscosity of the target bank customer under the viscosity index.
6. An apparatus for evaluating viscosity of a customer, comprising:
the output unit is used for outputting a bank viscosity index interface to a user; wherein, the bank viscosity index interface includes: a plurality of viscosity indicators under a plurality of banking categories; the plurality of banking categories, including: a bank liability category, a bank asset category, a bank transaction category, and a bank viscosity product category; the bank viscosity product category is a business category formed by a plurality of bank products with the highest historical viscosity with a bank client;
the setting unit is used for responding to weight setting operation executed by a user on the bank viscosity index interface and setting the weight value of each viscosity index in the bank viscosity index interface; the higher the weight value of the viscosity index is, the higher the importance degree of the viscosity index in evaluating the viscosity between the target bank customer and the bank is;
the first calculation unit is used for calculating to obtain the assignment of the target bank customer under the viscosity index by utilizing the historical customer data associated with the viscosity index in the historical customer data of the target bank customer and the standard assignment rule corresponding to the viscosity index aiming at each viscosity index; calculating the viscosity of the target bank customer under the viscosity index by utilizing the assignment of the target bank customer under the viscosity index and the weight value of the viscosity index; the value of the target bank customer under the viscosity index is used for explaining the viscosity reflected by the target bank customer under the viscosity index;
the second calculation unit is used for summing the viscosity of the target bank customer under each viscosity index, and calculating to obtain the viscosity between the target bank customer and the bank; and the viscosity between the target bank customer and the bank is used for reflecting the intimacy degree between the target bank customer and the bank.
7. The apparatus of claim 6, wherein the viscosity index is set in accordance with a time influence, and/or a customer data volatility influence; the time influence factor is an influence factor caused by the time of generating customer data related to the banking business category on the viscosity; the influence factor of the fluctuation of the customer data is the influence factor of the fluctuation condition of the customer data associated with the banking classes in two adjacent time periods on the viscosity.
8. The apparatus of claim 6, wherein the plurality of viscosity indicators under the plurality of banking categories are divided into a plurality of levels;
wherein, the setting unit includes:
the setting subunit is used for responding to weight setting operation executed by a user on the bank viscosity index interface and setting a weight value of each level of viscosity index under each banking business category in the bank viscosity index interface;
the first calculation unit includes:
the first calculating subunit is configured to calculate, for the lowest-level viscosity index under each banking service category, an assignment of the target bank customer under the lowest-level viscosity index by using historical customer data associated with the lowest-level viscosity index in historical customer data of the target bank customer and a standard assignment rule corresponding to the lowest-level viscosity index; multiplying the value assigned by the target bank client under the lowest-level viscosity index, the weight value corresponding to the lowest-level viscosity index and the weight value corresponding to each level of viscosity index above the lowest-level viscosity index to calculate the viscosity of the target bank client under the lowest-level viscosity index;
the second calculation unit includes:
and the second calculating subunit is configured to sum the viscosities of the target bank customer under each of the lowest-level viscosity indexes, and calculate to obtain the viscosity between the target bank customer and the bank.
9. A computer-readable medium, on which a computer program is stored, wherein the program, when executed by a processor, implements the method of any one of claims 1 to 5.
10. An apparatus for evaluating viscosity of a customer, comprising:
one or more processors;
a storage device having one or more programs stored thereon;
the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method of any of claims 1-5.
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| CN202110603802.1A CN113298398A (en) | 2021-05-31 | 2021-05-31 | Client viscosity evaluation method and device, readable medium and equipment |
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| CN202110603802.1A CN113298398A (en) | 2021-05-31 | 2021-05-31 | Client viscosity evaluation method and device, readable medium and equipment |
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