CN116433352A - Method and device for determining potential loan object and electronic equipment - Google Patents
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Abstract
The application discloses a method and a device for determining a potential loan object and electronic equipment, and relates to the field of financial science and technology and other related technical fields. Wherein the method comprises the following steps: acquiring N historical transaction data of a first object in a preset time period; determining M target transaction data from N historical transaction data according to transaction places in the historical transaction data; determining a transaction place corresponding to the target transaction data as a target transaction place; and determining a target object according to the transaction time and the transaction amount corresponding to the target transaction data, and determining the target object as a potential loan object to be marketed. The method and the device solve the technical problem that the determination efficiency of the potential loan object is low in the prior art.
Description
Technical Field
The present disclosure relates to the field of financial science and technology and other related technical fields, and in particular, to a method and apparatus for determining a potential loan object, and an electronic device.
Background
In the prior art, when identifying whether a user is a marketing object requiring loan, the determination is usually performed according to the credit card consumption record of the user, for example, the user a is used to consume with the credit card, and then the user a is determined as a potential loan object possibly requiring loan service, and the determination mode of the potential loan object is too simple, so that the determination accuracy of the potential loan object is low, the determination efficiency of the potential loan object is affected, and the problem of low success rate of the later marketing process of the potential loan object is caused.
In view of the above problems, no effective solution has been proposed at present.
Disclosure of Invention
The embodiment of the application provides a method, a device and electronic equipment for determining a potential loan object, which are used for at least solving the technical problem of low determination efficiency of the potential loan object in the prior art.
According to one aspect of an embodiment of the present application, there is provided a method of determining a potential loan object, comprising: acquiring N historical transaction data of a first object in a preset time period, wherein the first object is an object with a historical loan record, and the historical transaction data at least comprises transaction time, transaction amount and transaction place, and N is a positive integer; determining M target transaction data from N historical transaction data according to transaction places in the historical transaction data, wherein the transaction places of the M target transaction data are the same transaction place, and M is a positive integer which is larger than a preset threshold and smaller than or equal to N; determining a transaction place corresponding to the target transaction data as a target transaction place; determining a target object according to the transaction time and the transaction amount corresponding to the target transaction data, wherein the target object is an object with target transaction behaviors, the target transaction behaviors represent that the target object transacts the target amount at a target transaction place when the target object is at the target time, the time interval between the target time and the transaction time corresponding to the target transaction data is smaller than a preset time interval, and the ratio between the target amount and the transaction amount corresponding to the target transaction data is within the preset interval; the target object is determined to be a potential loan object to be marketed.
Further, the method for determining the potential loan object further comprises the following steps: detecting whether a loan record exists in a target object; determining the target object as a first potential loan object under the condition that the target object does not have a loan record; and determining the target object as a second potential loan object under the condition that the target object has a loan record, wherein the marketing priority of the first potential loan object is higher than that of the second potential loan object.
Further, the method for determining the potential loan object further comprises the following steps: after determining that the target object is a potential loan object to be marketed, acquiring a historical loan record of the first object; determining a loan product of the first object according to the historical loan record; the loan product is determined as the loan product recommended to the potential lender during the marketing process.
Further, the method for determining the potential loan object further comprises the following steps: after determining that the target object is a potential loan object to be marketed, acquiring X pieces of first transaction data of the target object in a preset time period, wherein X is a positive integer; determining a first balance sum of the target object in a preset time period according to the X pieces of first transaction data; determining a target balance sum of the first object in a preset time period according to the N historical transaction data; determining a loan amount corresponding to the first object according to the historical loan record of the first object, wherein the loan amount corresponding to the first object is all funds which can be obtained by the first object on a loan product; and determining the loan amount corresponding to the target object according to the first balance sum, the target balance sum and the loan amount corresponding to the first object, wherein the loan amount corresponding to the target object is all funds which can be obtained by the target object on a loan product.
Further, the method for determining the potential loan object further comprises the following steps: identifying H first sub-transaction data and K second sub-transaction data in the X first transaction data, wherein the first sub-transaction data is transaction data of target object income funds, the second sub-transaction data is transaction data of target object expenditure funds, and the sum of H and K is X; determining the fund income corresponding to each first sub-transaction data as first fund income to obtain H first fund incomes; determining the fund expenditure corresponding to each piece of second sub-transaction data as first fund expenditure, and obtaining K first fund expenditure; summing the H first fund incomes to obtain a first total incomes of the target object in a preset time period; summing the K first capital expenditures to obtain a first total expenditure of the target object in a preset time period; and calculating a difference value between the first total income and the first total expenditure to obtain a first balance sum of the target object in a preset time period.
Further, the method for determining the potential loan object further comprises the following steps: identifying G third sub-transaction data and Y fourth sub-transaction data in the N historical transaction data, wherein the third sub-transaction data is transaction data of the first object income funds, the fourth sub-transaction data is transaction data of the first object expenditure funds, and the sum of G and Y is N; determining the fund income corresponding to each third sub-transaction data as the second fund income to obtain G second fund incomes; determining the fund expenditure corresponding to each fourth sub-transaction data as the second fund expenditure, and obtaining Y second fund expenditure; summing the G second fund incomes to obtain target total incomes of the first object in a preset time period; summing the Y second capital expenditures to obtain a target total expense of the first object in a preset time period; and calculating the difference between the target total income and the target total expenditure to obtain the target total expense sum of the first object in the preset time period.
Further, the method for determining the potential loan object further comprises the following steps: calculating a ratio between the first sum of the balances and the target sum of the balances; and calculating the product of the ratio and the loan amount of the first object to obtain the loan amount corresponding to the target object.
According to another aspect of the embodiments of the present application, there is also provided a device for determining a potential loan object, including: the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring N pieces of historical transaction data of a first object in a preset time period, the first object is an object with a historical loan record, the historical transaction data at least comprise transaction time, transaction amount and transaction place, and N is a positive integer; the first determining module is used for determining M target transaction data from N pieces of historical transaction data according to transaction places in the historical transaction data, wherein the transaction places of the M target transaction data are the same transaction place, and M is a positive integer which is larger than a preset threshold value and smaller than or equal to N; the second determining module is used for determining the transaction place corresponding to the target transaction data as a target transaction place; the third determining module is used for determining a target object according to the transaction time and the transaction amount corresponding to the target transaction data, wherein the target object is an object with target transaction behaviors, the target transaction behaviors represent that the target object transacts the target amount at the target transaction place when the target object is at the target time, the time interval between the target time and the transaction time corresponding to the target transaction data is smaller than the preset time interval, and the difference between the target amount and the transaction amount corresponding to the target transaction data is smaller than the preset amount; and the fourth determining module is used for determining that the target object is a potential loan object to be marketed.
According to another aspect of the embodiments of the present application, there is also provided a computer readable storage medium having a computer program stored therein, wherein the computer program is configured to perform the above-described method of determining a potential loan object at runtime.
According to another aspect of the embodiments of the present application, there is also provided an electronic device, including one or more processors and a memory for storing one or more programs, wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method for determining a potential loan object described above.
In the application, by analyzing the transaction location, the transaction time and the transaction amount in the historical transaction data of the first object, determining that a target object similar to the first object is a potential loan object, firstly acquiring N historical transaction data of the first object in a preset time period, wherein the first object is an object with a historical loan record, the historical transaction data at least comprises the transaction time, the transaction amount and the transaction location, N is a positive integer, and then determining M target transaction data from the N historical transaction data according to the transaction location in the historical transaction data, wherein the transaction location of the M target transaction data is the same transaction location, and M is a positive integer which is greater than a preset threshold and less than or equal to N. And then determining a transaction place corresponding to the target transaction data as a target transaction place, and determining a target object according to the transaction time and the transaction amount corresponding to the target transaction data, wherein the target object is an object with target transaction behaviors, the target transaction behaviors represent that the target object transacts the target amount at the target transaction place when the target transaction behaviors are at the target time, the time interval between the target time and the transaction time corresponding to the target transaction data is smaller than a preset time interval, and the ratio between the target amount and the transaction amount corresponding to the target transaction data is in the preset interval. Finally, the target object is determined to be the potential loan object to be marketed.
As can be seen from the above, according to the present application, by acquiring the historical transaction data of the loan user (the first object) with the historical loan record, by analyzing the transaction location, the transaction time and the transaction amount in the historical transaction data of the loan user, the target user similar to the loan user is determined to be the potential loan object, and since three dimensions of the transaction location + the transaction time + the transaction amount can reflect the consumption habit of the user to a great extent, the user similar to the loan user is determined to be the potential loan object through the three dimensions, not only can the determination accuracy and the determination efficiency of the potential loan object be improved, but also the subsequent marketing success rate to the potential loan object can be improved.
Therefore, the technical scheme of the method and the device achieves the aim of determining the potential loan object based on the loan user, thereby achieving the technical effect of improving the determination accuracy of the potential loan object, and further solving the technical problem of low determination efficiency of the potential loan object in the prior art.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute an undue limitation to the application. In the drawings:
FIG. 1 is a flow chart of an alternative method of determining potential loan objects, in accordance with an embodiment of the application;
FIG. 2 is a flowchart of an alternative method of determining a loan amount for a target object, in accordance with an embodiment of the application;
FIG. 3 is a flowchart of an alternative method of calculating a first sum of balances according to an embodiment of the application;
FIG. 4 is a flowchart of an alternative method of calculating a target balance sum, according to an embodiment of the present application;
FIG. 5 is a schematic diagram of an alternative potential loan object determination device, in accordance with an embodiment of the application;
fig. 6 is a schematic diagram of an alternative electronic device according to an embodiment of the present application.
Detailed Description
In order to make the present application solution better understood by those skilled in the art, the following description will be made in detail and with reference to the accompanying drawings in the embodiments of the present application, it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, shall fall within the scope of the present application.
It should be noted that the terms "first," "second," and the like in the description and claims of the present application and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that embodiments of the present application described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
It should be further noted that, related information (including, but not limited to, user equipment information, user personal information, etc.) and data (including, but not limited to, data for presentation, analyzed data, etc.) related to the present disclosure are information and data authorized by a user or sufficiently authorized by each party. For example, an interface is provided between the system and the relevant user or institution, before acquiring the relevant information, the system needs to send an acquisition request to the user or institution through the interface, and acquire the relevant information after receiving the consent information fed back by the user or institution.
Example 1
In accordance with embodiments of the present application, there is provided an embodiment of a method of determining a potential loan object, it being noted that the steps illustrated in the flowchart of the figures may be performed in a computer system, such as a set of computer-executable instructions, and, although a logical order is illustrated in the flowchart, in some cases, the steps illustrated or described may be performed in an order other than that illustrated herein.
FIG. 1 is a flow chart of an alternative method of determining potential loan objects, as shown in FIG. 1, comprising the steps of:
step S101, N pieces of historical transaction data of a first object in a preset time period are obtained.
In step S101, the first object is an object with a history loan record, and the history transaction data includes at least a transaction time, a transaction amount, and a transaction location, where N is a positive integer.
In an alternative embodiment, a potential loan object determination system may be the subject of execution of the potential loan object determination method of the present application. The potential loan object determining system may be a plug-in mobile payment software, where the mobile payment software is installed in a terminal device such as a smart phone of the user.
Specifically, the preset time period may be set in a customized manner, for example, a month, a year, a quarter, etc. Suppose user A is a user with a history of loan records, for example, user A applies for a 10 ten thousand yuan loan. Under the condition that the user A is authorized, the potential loan object determining system can acquire N pieces of historical transaction data of the user A in a preset time period, wherein each piece of historical transaction data at least comprises a transaction place, a transaction time and a transaction amount corresponding to the historical transaction data. In the N pieces of history transaction data, there may be at least one transaction location corresponding to the history transaction data as the same location, for example, the history transaction data 1 occurs at the location a, the history transaction data 2 occurs at the location B, the history transaction data 3 occurs at the location a, and the history transaction data 4 occurs at the location a.
Step S102, M target transaction data are determined from N historical transaction data according to the transaction places in the historical transaction data.
In step S102, the transaction locations of the M target transaction data are the same transaction location, and M is a positive integer greater than a preset threshold and less than or equal to N.
Specifically, the preset threshold may be set by a user, for example, the preset threshold may be set to 2, and the potential loan object determining system may determine the historical transaction data 1, the historical transaction data 3, and the historical transaction data 4 as the target transaction data in combination with the historical transaction data 1 occurring at the location a, the historical transaction data 2 occurring at the location B, the historical transaction data 3 occurring at the location a, and the historical transaction data 4 occurring at the location a.
Step S103, determining the transaction location corresponding to the target transaction data as the target transaction location.
Still taking the above-mentioned historical transaction data 1, historical transaction data 3 and historical transaction data 4 as the target transaction data as an example, since the transaction location of the three target transaction data is location a, the potential loan object determination system will determine location a as the target transaction location. It is readily understood that the target transaction location is the location where the first subject frequently conducts transactions.
Step S104, determining a target object according to the transaction time and the transaction amount corresponding to the target transaction data.
In step S104, the target object is an object with a target transaction behavior, and the target transaction behavior characterizes that the target object transacts a target amount at the target transaction location when the target transaction object is at the target time, the time interval between the target time and the transaction time corresponding to the target transaction data is smaller than the preset time interval, and the ratio between the target amount and the transaction amount corresponding to the target transaction data is within the preset interval.
Specifically, the potential loan object determination system may determine a target object similar to the first object based on the target transaction location and the transaction time and transaction amount corresponding to the target transaction data. For example, the historical transaction data 1 is a target transaction data, and it is assumed that the transaction time of the historical transaction data 1 is time T1, and the user a consumes 20 yuan in this transaction.
On this basis, the potential loan object determination system may determine the target object from the three dimensions of the target transaction location + transaction time + transaction amount. Specifically, if a target amount is transacted at a target transaction location at a target time of a certain object, the object may be determined to be the target object, where a time interval between the target time and a transaction time corresponding to target transaction data is smaller than a preset time interval, and a ratio between the target amount and the transaction amount corresponding to the target transaction data is located in the preset interval. For example, for historical transaction data 1, assuming a preset time interval of 30 minutes, a preset interval of [0.9,1.1], when user B also consumed [18, 22] at location a within (t1±30 minutes), the potential loan object determination system may determine that user B is a target object. Wherein 18=20×0.9, 22=20×1.1.
Step S105, determining the target object as a potential loan object to be marketed.
It is easily noted that people who often conduct similar transactions in the same area will often also have similar economic viability or consumption habits, e.g. employees of the same company will typically consume at the same restaurant in noon. On this basis, since the same company is used, the economic income and consumption of staff A and staff B may not be quite different (excluding extreme cases such as high-rise of the company, the income difference of most people of one company is not too high).
Based on the above background, through the technical scheme of the application, if staff a has a history loan record, a bank can conduct loan marketing for staff B according to the history loan record of staff a, the loan product of marketing can be a loan product applied by staff a or a loan product similar to the loan product applied by staff a, and the loan amount of staff a can be referred to the loan amount of staff B, or the loan amount of staff B can be obtained after certain adjustment is conducted on the loan amount of staff a according to the recent consumption gap between staff a and staff B.
Based on the foregoing contents of steps S101 to S105, in the present application, by analyzing the transaction location, the transaction time and the transaction amount in the historical transaction data of the first object, determining that the target object similar to the first object is a potential loan object, first obtaining N historical transaction data of the first object within a preset time period, where the first object is an object having a historical loan record, the historical transaction data at least includes the transaction time, the transaction amount and the transaction location, N is a positive integer, and then determining M target transaction data from the N historical transaction data according to the transaction location in the historical transaction data, where the transaction location of the M target transaction data is the same transaction location, and M is a positive integer greater than a preset threshold and less than or equal to N. And then determining a transaction place corresponding to the target transaction data as a target transaction place, and determining a target object according to the transaction time and the transaction amount corresponding to the target transaction data, wherein the target object is an object with target transaction behaviors, the target transaction behaviors represent that the target object transacts the target amount at the target transaction place when the target transaction behaviors are at the target time, the time interval between the target time and the transaction time corresponding to the target transaction data is smaller than a preset time interval, and the difference between the target amount and the transaction amount corresponding to the target transaction data is smaller than the preset amount. Finally, the target object is determined to be the potential loan object to be marketed.
As can be seen from the above, according to the present application, by acquiring the historical transaction data of the loan user (the first object) with the historical loan record, by analyzing the transaction location, the transaction time and the transaction amount in the historical transaction data of the loan user, the target user similar to the loan user is determined to be the potential loan object, and since three dimensions of the transaction location + the transaction time + the transaction amount can reflect the consumption habit of the user to a great extent, the user similar to the loan user is determined to be the potential loan object through the three dimensions, not only can the determination accuracy and the determination efficiency of the potential loan object be improved, but also the subsequent marketing success rate to the potential loan object can be improved.
Therefore, the technical scheme of the method and the device achieves the aim of determining the potential loan object based on the loan user, thereby achieving the technical effect of improving the determination accuracy of the potential loan object, and further solving the technical problem of low determination efficiency of the potential loan object in the prior art.
In an alternative embodiment, based on the above-mentioned process from step S101 to step S105, a plurality of target objects may be finally determined, and in order to prioritize marketing among the target objects, the potential loan object determining system may further detect whether a loan record exists in the target objects, and in the case that the target objects do not exist in the loan record, the potential loan object determining system determines that the target object is the first potential loan object; in the case where the target object has a loan record, the potential loan object determination system determines the target object as a second potential loan object, wherein the marketing priority of the first potential loan object is higher than the marketing priority of the second potential loan object.
For example, if the target object corresponding to the first object (user a) has a user C and a user D in addition to the user B, the potential loan object determining system detects whether the user B, the user C, and the user D have loan records, respectively, and if the user B and the user C do not have loan records, the potential loan object determining system determines that the user B and the user C are the first potential loan object, the user D is the second potential loan object, and the marketing priority of the user B and the user C is higher than the marketing priority of the user D.
In an alternative embodiment, after determining that the target object is the potential loan object to be marketed, the potential loan object determination system may further obtain a historical loan record of the first object and determine a loan product of the first object based on the historical loan record, and then the potential loan object determination system may determine the loan product as the loan product recommended to the potential loan object during the marketing process.
Alternatively, assuming that the loan product of the first object (user A) is a loan product P, the potential loan object determination system may treat the loan product P as a loan product to be marketed to the target object (user B).
In an alternative embodiment, FIG. 2 illustrates a flowchart of an alternative method of determining a loan amount for a target object, after determining that the target object is a potential loan object to be marketed, in accordance with an embodiment of the application. As shown in fig. 2, the method comprises the following steps:
step S201, X pieces of first transaction data of a target object in a preset time period are obtained;
step S202, determining a first balance sum of the target object in a preset time period according to X pieces of first transaction data;
step S203, determining a target balance sum of the first object in a preset time period according to the N historical transaction data;
step S204, determining the loan amount corresponding to the first object according to the historical loan record of the first object, wherein the loan amount corresponding to the first object is all funds which can be obtained by the first object on the loan product;
in step S205, a loan amount corresponding to the target object is determined according to the first balance sum, the target balance sum, and the loan amount corresponding to the first object, where the loan amount corresponding to the target object is all funds that the target object can loan on the loan product.
For example, after determining that the user B is the target object, the potential loan object determining system may formulate a marketing strategy for the user B according to the history loan record of the first object (user a), where one of the critical information in the marketing strategy is the loan amount corresponding to the user B.
In order to improve the accuracy of evaluating the loan amount of the user B, historical transaction data of the user B and the user A can be compared, and then the loan amount of the user A is adjusted according to the comparison result to obtain the loan amount of the user B. Specifically, historical transaction data of the user B in the same preset time period is obtained, total income and total expenditure of the user B in the preset time period are calculated to obtain the sum of the incomes and the total expenditure of the user A in the preset time period, the sum of the incomes of the user A in the preset time period is obtained, and finally, the loan amount of the user A (the loan amount of the user A is known) is correspondingly adjusted according to the difference between the sum of the incomes of the user B and the sum of the incomes of the user A, so that the loan amount of the user B can be obtained.
Optionally, fig. 3 shows a flowchart of a method for calculating a sum of the balance of the target object (i.e. the first sum of the balance), which specifically includes the following steps:
step S301, identifying H first sub-transaction data and K second sub-transaction data in the X first transaction data, wherein the first sub-transaction data is transaction data of target object income funds, the second sub-transaction data is transaction data of target object expenditure funds, and the sum of H and K is X;
Step S302, determining the fund income corresponding to each piece of first sub-transaction data as first fund income, and obtaining H first fund incomes;
step S303, determining that the fund expenditure corresponding to each piece of second sub-transaction data is the first fund expenditure, and obtaining K first fund expenditure;
step S304, summing the H first fund incomes to obtain a first total incomes of the target object in a preset time period;
step S305, summing the K first capital expenditures to obtain a first total expenditure of the target object in a preset time period;
step S306, calculating the difference between the first total income and the first total expenditure to obtain a first balance sum of the target object in a preset time period.
Optionally, assuming that the first transaction data has 10 (corresponding to X) pieces in total, wherein the first sub-transaction data has 0 (corresponding to H) pieces, the second sub-transaction data has 10 (corresponding to K) pieces, and determining that the first total expenditure of the target object in the preset time period is 1000 yuan by calculating the sum of the funds expenditure of the 10 second sub-transaction data. Since the first sub-transaction data is 0 pieces, the first total income of the target object in the preset time period is 0 yuan. On the basis, the first sum of the balance of the target object in the preset time period is 1000 yuan.
In an alternative embodiment, fig. 4 shows a flowchart of a method for calculating a sum of the balance of the first object (i.e. the target sum of the balance), according to an embodiment of the present application, specifically including the following steps:
step S401, identifying G third sub-transaction data and Y fourth sub-transaction data in the N pieces of historical transaction data, wherein the third sub-transaction data is transaction data of funds received by a first object, the fourth sub-transaction data is transaction data of funds paid out by the first object, and the sum of G and Y is N;
step S402, determining the fund income corresponding to each third sub-transaction data as the second fund income, and obtaining G second fund incomes;
step S403, determining that the fund expenditure corresponding to each fourth sub-transaction data is the second fund expenditure, and obtaining Y second fund expenditure;
step S404, summing G second fund incomes to obtain a target total incomes of the first object in a preset time period;
step S405, summing Y second capital expenditures to obtain a target total expenditure of the first object in a preset time period;
step S406, calculating the difference between the target total income and the target total expenditure to obtain the target balance sum of the first object in the preset time period.
Optionally, assuming that the historical transaction data has 20 (corresponding to N) pieces in total, wherein the third sub-transaction data has 2 (corresponding to G) pieces, the fourth sub-transaction data has 18 (corresponding to Y) pieces, determining that the target total expense of the target object in the preset time period is 1200 yuan by calculating the sum of the funds expense of the 18 fourth sub-transaction data, and determining that the target total income of the target object in the preset time period is 100 yuan by calculating the sum of the funds income of the 2 third sub-transaction data. On this basis, the first sum of the balance of the target object in the preset time period is 1100 yuan.
In an alternative embodiment, the potential loan object determination system further calculates a ratio between the first sum of the balances and the target sum of the balances, and then calculates a product of the ratio and the loan amount of the first object to obtain the corresponding loan amount of the target object.
For example, assuming that the first object is user a, the target object is user B, the preset time period is one month, the sum of the balances of user a in the one month is 2000 yuan, the sum of the balances of user B in the one month is 10000 yuan, on the basis of the sum, assuming that the historical loan amount of user a is 10 ten thousand yuan, the loan amount of user B can be adjusted to 50 ten thousand yuan, wherein 50 ten thousand= (10000/2000) ×10 ten thousand.
From the above, according to the present application, by acquiring historical transaction data of a loan user with a historical loan record, analyzing a transaction location, a transaction time and a transaction amount in the historical transaction data of the loan user, determining a target object similar to the loan user, which has not yet been loaned, and then determining the target object as an object to be marketed, and adjusting the loan amount of the loan user according to the historical transaction data of the target object and the historical transaction data of the loan user, the loan amount of the target object is obtained.
Example 2
There is also provided, in accordance with an embodiment of the present application, an embodiment of a device for determining a potential loan object, as shown in fig. 5, the device comprising: the obtaining module 501 is configured to obtain N pieces of historical transaction data of a first object in a preset time period, where the first object is an object with a historical loan record, and the historical transaction data at least includes transaction time, transaction amount and transaction location, and N is a positive integer; a first determining module 502, configured to determine M target transaction data from N historical transaction data according to transaction locations in the historical transaction data, where the transaction locations of the M target transaction data are the same transaction location, and M is a positive integer greater than a preset threshold and less than or equal to N; a second determining module 503, configured to determine a transaction location corresponding to the target transaction data as a target transaction location; a third determining module 504, configured to determine a target object according to a transaction time and a transaction amount corresponding to the target transaction data, where the target object is an object having a target transaction behavior, and the target transaction behavior characterizes that the target object transacts a target amount at a target transaction location when the target object is at the target time, a time interval between the target time and the transaction time corresponding to the target transaction data is less than a preset time interval, and a ratio between the target amount and the transaction amount corresponding to the target transaction data is within the preset interval; a fourth determining module 505 is configured to determine that the target object is a potential loan object to be marketed.
Optionally, the third determining module further includes: a first detection unit, a first determination unit and a second determination unit. The first detection unit is used for detecting whether a loan record exists in the target object; a first determining unit configured to determine that the target object is a first potential loan object, in a case where the target object does not have a loan record; and a second determining unit configured to determine that the target object is a second potential loan object in a case where the target object has a loan record, where the marketing priority of the first potential loan object is higher than the marketing priority of the second potential loan object.
Optionally, the determining device of the potential loan object further includes: the device comprises a first acquisition module, a fourth determination module and a fifth determination module. The first acquisition module is used for acquiring a history loan record of the first object; a fourth determining module for determining loan products of the first object according to the historical loan records; and a fifth determining module for determining the loan product as a loan product recommended to the potential loan object in the marketing process.
Optionally, the determining device of the potential loan object further includes: the device comprises a second acquisition module, a sixth determination module, a seventh determination module, an eighth determination module and a ninth determination module. The second acquisition module is used for acquiring X pieces of first transaction data of the target object in a preset time period, wherein X is a positive integer; a sixth determining module, configured to determine a first balance sum of the target object in a preset time period according to the X first transaction data; a seventh determining module, configured to determine a target balance sum of the first object in a preset time period according to the N historical transaction data; an eighth determining module, configured to determine a loan amount corresponding to the first object according to a historical loan record of the first object, where the loan amount corresponding to the first object is all funds that the first object can loan on a loan product; and a ninth determining module, configured to determine a loan amount corresponding to the target object according to the first balance sum, the target balance sum, and the loan amount corresponding to the first object, where the loan amount corresponding to the target object is all funds that the target object can loan on the loan product.
Optionally, the sixth determining module further includes: the device comprises a first identification unit, a third determination unit, a fourth determination unit, a first summation unit, a second summation unit and a first calculation unit. The first identification unit is used for identifying H first sub-transaction data and K second sub-transaction data in the X first transaction data, wherein the first sub-transaction data are transaction data of funds received by a target object, the second sub-transaction data are transaction data of funds paid out by the target object, and the sum of H and K is X; a third determining unit, configured to determine that the fund income corresponding to each first sub-transaction data is a first fund income, so as to obtain H first fund incomes; a fourth determining unit, configured to determine that the funds expenditure corresponding to each second sub-transaction data is the first funds expenditure, to obtain K first funds expenditure; the first summation unit is used for summing the H first fund incomes to obtain first total incomes of the target object in a preset time period; the second summation unit is used for summing the K first capital expenditures to obtain first total expenditures of the target object in a preset time period; the first calculating unit is used for calculating a difference value between the first total income and the first total expenditure to obtain a first total expense sum of the target object in a preset time period.
Optionally, the seventh determining module further includes: the device comprises a second identification unit, a fifth determination unit, a sixth determination unit, a third summation unit, a fourth summation unit and a second calculation unit. The second identifying unit is used for identifying G third sub-transaction data and Y fourth sub-transaction data in the N pieces of historical transaction data, wherein the third sub-transaction data is transaction data of funds received by the first object, the fourth sub-transaction data is transaction data of funds paid out by the first object, and the sum of G and Y is N; a fifth determining unit, configured to determine that the fund revenue corresponding to each third sub-transaction data is a second fund revenue, so as to obtain G second fund revenue; a sixth determining unit, configured to determine that the funds corresponding to each of the fourth sub-transaction data are second funds, to obtain Y second funds; the third summation unit is used for summing G second fund incomes to obtain target total incomes of the first object in a preset time period; a fourth summation unit, configured to sum the Y second capital expenditures to obtain a target total expenditure of the first object in a preset time period; and the second calculation unit is used for calculating the difference value between the target total income and the target total expenditure to obtain the target total expense sum of the first object in the preset time period.
Optionally, the ninth determining module further includes: a third calculation unit and a fourth calculation unit. The third calculation unit is used for calculating the ratio between the first balance sum and the target balance sum; and a fourth calculation unit, configured to calculate a product of the ratio and the loan amount of the first object, to obtain the loan amount corresponding to the target object.
Example 3
According to another aspect of the embodiments of the present application, there is also provided a computer readable storage medium having a computer program stored therein, wherein the computer program is configured to perform the method of determining a potential loan object of embodiment 1 at runtime.
Example 4
According to another aspect of the embodiments of the present application, an electronic device is also provided. As shown in fig. 6, the electronic device includes one or more processors; and a storage means for storing one or more programs which, when executed by the one or more processors, cause the one or more processors to implement a method for running the program, wherein the program is configured to perform the method for determining a potential loan object in embodiment 1 above when run.
The foregoing embodiment numbers of the present application are merely for describing, and do not represent advantages or disadvantages of the embodiments.
In the foregoing embodiments of the present application, the descriptions of the embodiments are emphasized, and for a portion of this disclosure that is not described in detail in this embodiment, reference is made to the related descriptions of other embodiments.
In the several embodiments provided in the present application, it should be understood that the disclosed technology content may be implemented in other manners. The above-described embodiments of the apparatus are merely exemplary, and the division of the units, for example, may be a logic function division, and may be implemented in another manner, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some interfaces, units or modules, or may be in electrical or other forms.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in each embodiment of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be embodied in essence or a part contributing to the prior art or all or part of the technical solution in the form of a software product stored in a storage medium, including several instructions to cause a computer device (which may be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the methods described in the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a Read-only memory (ROM), a random access memory (RAM, random Access Memory), a removable hard disk, a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The foregoing is merely a preferred embodiment of the present application and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present application and are intended to be comprehended within the scope of the present application.
Claims (10)
1. A method of determining a potential loan object, comprising:
acquiring N pieces of historical transaction data of a first object in a preset time period, wherein the first object is an object with a historical loan record, and the historical transaction data at least comprises transaction time, transaction amount and transaction place, and N is a positive integer;
determining M target transaction data from N historical transaction data according to transaction places in the historical transaction data, wherein the transaction places of the M target transaction data are the same transaction place, and M is a positive integer which is larger than a preset threshold and smaller than or equal to N;
determining a transaction place corresponding to the target transaction data as a target transaction place;
determining a target object according to the transaction time and the transaction amount corresponding to the target transaction data, wherein the target object is an object with target transaction behaviors, the target transaction behaviors represent that the target object transacts a target amount at the target transaction place when the target object is at the target time, the time interval between the target time and the transaction time corresponding to the target transaction data is smaller than a preset time interval, and the ratio between the target amount and the transaction amount corresponding to the target transaction data is within the preset interval;
And determining the target object as a potential loan object to be marketed.
2. The method of claim 1, wherein determining that the target object is a potential loan object to be marketed comprises:
detecting whether a loan record exists in the target object;
determining the target object as a first potential loan object if the target object does not have the loan record;
and determining the target object as a second potential loan object under the condition that the target object exists the loan record, wherein the marketing priority of the first potential loan object is higher than that of the second potential loan object.
3. The method of claim 1, wherein after determining that the target object is a potential loan object to be marketed, the method further comprises:
acquiring a history loan record of the first object;
determining a loan product of the first object according to the historical loan record;
the loan product is determined to be the loan product recommended to the potential lender during the marketing process.
4. The method of claim 3, wherein after determining that the target object is a potential loan object to be marketed, the method further comprises:
Acquiring X pieces of first transaction data of the target object in the preset time period, wherein X is a positive integer;
determining a first balance sum of the target object in the preset time period according to the X pieces of first transaction data;
determining target balance sum of the first object in the preset time period according to N historical transaction data;
determining a loan amount corresponding to the first object according to the historical loan record of the first object, wherein the loan amount corresponding to the first object is all funds which can be obtained by the first object in a loan on the loan product;
and determining the loan amount corresponding to the target object according to the first balance sum, the target balance sum and the loan amount corresponding to the first object, wherein the loan amount corresponding to the target object is all funds which can be obtained by the target object on the loan product.
5. The method of claim 4, wherein determining a first sum of the target object's first balance over the preset time period from X pieces of the first transaction data comprises:
identifying H first sub-transaction data and K second sub-transaction data in the X first transaction data, wherein the first sub-transaction data is transaction data of income funds of the target object, the second sub-transaction data is transaction data of expenditure funds of the target object, and the sum of H and K is X;
Determining the fund income corresponding to each piece of first sub-transaction data as first fund income, and obtaining H first fund incomes;
determining the corresponding fund expenditure of each piece of second sub-transaction data as first fund expenditure, and obtaining K first fund expenditure;
summing the H first fund incomes to obtain a first total incomes of the target object in the preset time period;
summing the K first capital expenditures to obtain a first total expenditure of the target object in the preset time period;
and calculating a difference value between the first total income and the first total expenditure to obtain a first expense sum of the target object in the preset time period.
6. The method of claim 5, wherein determining a target sum of the balances of the first object over the preset time period from the N historical transaction data comprises:
identifying G third sub-transaction data and Y fourth sub-transaction data in the N historical transaction data, wherein the third sub-transaction data is the transaction data of the first object income funds, the fourth sub-transaction data is the transaction data of the first object expenditure funds, and the sum of G and Y is N;
Determining the fund income corresponding to each third sub-transaction data as second fund income, and obtaining G second fund incomes;
determining that the fund expenditure corresponding to each piece of fourth sub-transaction data is a second fund expenditure, and obtaining Y second fund expenditure;
summing the G second fund incomes to obtain target total incomes of the first object in the preset time period;
summing the Y second capital expenditures to obtain a target total expense of the first object in the preset time period;
and calculating the difference between the target total income and the target total expenditure to obtain the target total expense sum of the first object in the preset time period.
7. The method of claim 6, wherein determining the loan amount corresponding to the target object based on the first balance sum, the target balance sum, and the loan amount corresponding to the first object comprises:
calculating a ratio between the first sum of balances and the target sum of balances;
and calculating the product of the ratio and the loan amount of the first object to obtain the loan amount corresponding to the target object.
8. A device for determining a potential loan object, comprising:
the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring N pieces of historical transaction data of a first object in a preset time period, the first object is an object with a historical loan record, the historical transaction data at least comprise transaction time, transaction amount and transaction place, and N is a positive integer;
the first determining module is used for determining M target transaction data from N historical transaction data according to transaction places in the historical transaction data, wherein the transaction places of the M target transaction data are the same transaction place, and M is a positive integer which is larger than a preset threshold value and smaller than or equal to N;
the second determining module is used for determining the transaction place corresponding to the target transaction data as a target transaction place;
a third determining module, configured to determine a target object according to a transaction time and a transaction amount corresponding to the target transaction data, where the target object is an object having a target transaction behavior, the target transaction behavior characterizes that the target object transacts a target amount at the target transaction location when the target transaction time, a time interval between the target time and the transaction time corresponding to the target transaction data is less than a preset time interval, and a ratio between the target amount and the transaction amount corresponding to the target transaction data is within a preset interval;
And the fourth determining module is used for determining that the target object is a potential loan object to be marketed.
9. A computer readable storage medium having stored therein a computer program, wherein the computer program is configured to perform the method of determining a potential loan object of any of claims 1-7 at run-time.
10. An electronic device comprising one or more processors and memory for storing one or more programs, wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method of determining potential loan objects of any of claims 1-7.
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| CN117708183A (en) * | 2023-11-08 | 2024-03-15 | 广州西米科技有限公司 | Potential user mining method and system based on user consumption habit |
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| CN117708183A (en) * | 2023-11-08 | 2024-03-15 | 广州西米科技有限公司 | Potential user mining method and system based on user consumption habit |
| CN117708183B (en) * | 2023-11-08 | 2024-06-11 | 广州西米科技有限公司 | Potential user mining method and system based on user consumption habit |
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