CN117726341A - Method and system for user transaction characteristic analysis and early warning - Google Patents

Method and system for user transaction characteristic analysis and early warning Download PDF

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CN117726341A
CN117726341A CN202311776426.1A CN202311776426A CN117726341A CN 117726341 A CN117726341 A CN 117726341A CN 202311776426 A CN202311776426 A CN 202311776426A CN 117726341 A CN117726341 A CN 117726341A
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amount
transaction
rate
target user
reasonable
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CN117726341B (en
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樊奋前
李百建
郑正锋
周瑞
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Guangzhou Anyida Internet Small Loan Co ltd
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Guangzhou Anyida Internet Small Loan Co ltd
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    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
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Abstract

The application relates to the technical field of transaction risk detection and discloses a method and a system for user transaction characteristic analysis and early warning, wherein the method comprises the steps of acquiring a financial loan agreement of a target user so as to determine a loan amount and a fee-extinguishing settlement rule of the target user; obtaining each item of transaction detail information of a target user, and calculating loan use rate, preferential merchant consumption rate, average fund free period rate and fund paying rate of each settlement period; acquiring income information and asset declaration information of a target user to analyze reasonable expense amount and reasonable preferential merchant expense amount of the target user, and further calculating reasonable expense correction rate and reasonable preferential correction rate; calculating a transaction risk feature value z=k A (A‑A 0 )+K B (B‑B 0 )+K C (C‑C 0 )‑K D (D‑D 0 ) +N; when Z is more than Z0, transaction risk early warning information is generated; the method has the effect of reducing economic losses caused by abnormal transaction behaviors.

Description

Method and system for user transaction characteristic analysis and early warning
Technical Field
The present disclosure relates to the field of transaction risk detection, and in particular, to a method and system for user transaction feature analysis and early warning.
Background
As the application range of financial loans becomes wider, more and more people begin to use the financial loans, and financial institutions also begin to provide financial loans to more users, however, many users lacking the concept of financial management often use the financial loans by mistake; the abnormal transaction behaviors commonly seen at present comprise loan cash register, abnormal loan use and the like, and the abnormal transaction behaviors generated by users in the process of using financial loans are easy to cause great economic losses for the users or financial institutions.
Disclosure of Invention
In order to reduce economic losses caused by abnormal transaction behaviors, the application provides a method and a system for analyzing and early warning user transaction characteristics.
The first technical scheme adopted by the invention of the application is as follows:
a method for user transaction characteristic analysis and pre-warning, comprising:
acquiring a financial loan agreement of a target user to determine a loan amount and a charge settlement rule of the target user;
acquiring each item of transaction detail information of a target user, and calculating loan use rate A, preferential merchant consumption rate B, average fund free period rate C and paying fund rate D of each settlement period;
acquiring income information and asset declaration information of a target user to analyze reasonable expense amount and reasonable preferential merchant expense amount of the target user, and calculating reasonable expense correction rate A based on the reasonable expense amount and loan amount 0 Calculating reasonable benefit correction rate B based on reasonable benefit merchant consumption amount and current consumption amount 0 ；
Calculating a transaction risk feature value z=k A (A-A 0 )+K B (B-B 0 )+K C (C-C 0 )-K D (D-D 0 ) +N, where K A For the first weight coefficient, K B For the second weight coefficient, K C Is a third weight coefficient,K D For the fourth weight coefficient, C 0 For group average phase-free rate, D 0 Average fund rate of interest for group, N is additional feature item;
the transaction risk characteristic value Z and a preset risk threshold value Z are combined 0 In contrast, when Z > Z 0 Generating transaction risk early warning information;
the transaction detail information comprises transaction time, transaction amount, transaction type and used amount, and the preferential merchant refers to a merchant with a procedure rate of payment by using loans lower than a preset preferential threshold.
By adopting the technical scheme, the financial loan agreement of the target user is obtained so as to acquire the loan amount of the target user and the information of the charge settlement rule; since the behaviors of the illegal use of the loan such as loan cash register generally have the characteristics of high loan amount utilization rate, high preferential merchant consumption rate, long average fund free period, low payment rate and the like, each item of transaction detail information of the target user is acquired so as to know the transaction time, the transaction amount and the transaction type of each order of the user, and the loan utilization rate, the preferential merchant utilization rate, the average fund free period rate and the payment fund rate of the target user in each settlement period are calculated so as to analyze whether the transaction characteristics of the user conform to the characteristics of the cash register or other use of the loan or not; based on income information of the target user, reasonable consumption level of the user is analyzed, reasonable expenditure correction rate is calculated according to reasonable consumption amount and loan amount of the user, reasonable preferential merchant consumption amount required by the user for maintaining property such as real estate, vehicle and the like is analyzed based on property declaration information of the target user, and further reasonable preferential correction rate is calculated according to the reasonable preferential merchant consumption amount and current consumption amount; calculating a transaction risk characteristic value, wherein in the calculation process of the transaction risk characteristic value, loan use rate, preferential merchant use rate, average fund rest period rate and pay fund rate factors are taken into consideration for evaluating transaction risk, reasonable consumption characteristics of users are removed through reasonable expenditure correction rate, reasonable preferential correction rate, group average rest period rate and group average pay fund rate, and the weight of each index is adjusted by utilizing various weight coefficients so as to calculate the transaction risk characteristic value; when the transaction risk characteristic value is larger than the set risk threshold value, transaction risk early warning information is generated to prompt the financial institution that the transaction characteristic of the target user is abnormal, so that the possibility of economic loss and loss amount caused by abnormal transaction behaviors are reduced.
In a preferred example, the present application: the calculating of the loan usage rate A, the preferential merchant consumption rate B, the average fund free period rate C and the paying fund rate D of each settlement period comprises the following steps:
calculating the quotient of the used amount and the loan amount based on a preset data sampling frequency to obtain sampling utilization rate, and calculating the average value of all sampling utilization rates in each settlement period to obtain a loan utilization rate A;
counting the consumption amount M of the preferential merchant paid to the preferential merchant in each settlement period k Acquiring corresponding current consumption amount M j Calculating a preferential merchant consumption rate B, wherein,
based on the fee-extinguishing settlement rules and the transaction detail information, acquiring the transaction amount M of each transaction in each settlement period i Transaction date X i And the corresponding repayment date Y i And the current consumption amount M j The average prime phase rate C is calculated, wherein,
counting the payoff amount in each settlement period, and calculating the payoff amount and the current consumption amount M j To obtain the payoff funds rate D;
the fee-extinguishing settlement rule comprises a settlement period starting day T of each settlement period 1 Day T of settlement period termination 2 And a repayment date Y i The transaction time includes a transaction date.
By adopting the technical scheme, according to the preset data sampling frequency, the quotient of the used amount and the loan amount at a plurality of time nodes is calculated from one settlement period to obtain the sampling utilization rate, and the loan utilization rate is calculated through the average value of the sampling utilization rates, so that the time for a user to use the loan amount in one settlement period can be better judged compared with the time for only collecting the utilization rate of the loan when the settlement period is ended, and the identification accuracy of the user with the intention of registering the loan is improved; because the user with loan registering intention usually carries out false transaction through the merchant with lower loan payment procedure rate, the user registers the money, thus counting the amount paid to the preferential merchant in each settlement period, calculating the proportion of the consumption amount of the preferential merchant to the consumption amount in the current period, obtaining the consumption rate value of the preferential merchant, and being convenient for improving the recognition sensitivity of the abnormal transaction behavior of the user; based on the fee-extinguishing settlement rules and the transaction detail information, calculating the average free period rate enjoyed by the money involved in each transaction in each settlement period by taking the transaction amount of each transaction as a weight, and identifying abnormal transaction behaviors of a user; and counting the total amount of loans which are used by the user and need to pay interest in each settlement period to obtain the payment amount, and calculating the proportion of the payment amount to the current consumption amount to obtain the payment fund rate, wherein the payment fund rate is used for assisting in judging whether the user has abnormal transaction behaviors.
In a preferred example, the present application: the obtaining the income information and the asset declaration information of the target user to analyze the reasonable consumption amount of the target user and the reasonable preferential merchant consumption amount comprises the following steps:
acquiring income information of a target user to determine income amount, and calculating the product of the income amount and a preset compensation coefficient to obtain compensation capacity amount;
acquiring a personal credit report of a target user to determine the existing debt amount of the target user in each settlement period;
and calculating the difference between the compensation capacity amount and the existing debt amount of each settlement period to obtain the corresponding reasonable consumption amount.
By adopting the technical scheme, the income information of the target user is obtained to further determine the income amount of the target user, and the compensation capacity amount is calculated according to the product of the income amount and the preset compensation coefficient so as to obtain the fund amount which can be used for repaying the loan in the income of the user; acquiring a personal credit report of a target user so as to acquire other liabilities of the user and determine the existing liability amount of the user in each settlement period; and calculating the difference between the compensation capacity amount and the existing liability amount as a reasonable consumption amount so as to judge whether the loan amount used by the user exceeds the reasonable consumption level.
In a preferred example, the present application: the obtaining the income information and the asset declaration information of the target user to analyze the reasonable consumption amount of the target user and the reasonable preferential merchant consumption amount, and the method further comprises the following steps:
acquiring asset declaration information of a target user to determine the property owned by the target user, the number and the specification of vehicles;
based on the property possessed by the target user, the number and specifications of vehicles, the reasonable preferential merchant spending amount per settlement period of the target user is assessed.
By adopting the technical scheme, as common loan payment procedure rate preferential merchants comprise operators of fuel consumption, water cost, electricity cost, fuel cost, property cost, public transportation cost and the like, the asset declaration information of the target user is acquired so as to acquire the property owned by the target user and the number and the specification of vehicles, and thus the reasonable amount of preferential merchant consumption required by the user for maintaining or supporting the property, the vehicles and the commute is determined in each settlement period.
In a preferred example, the present application: the transaction detail information comprises a collection identification of a collection merchant;
the calculated transaction risk characteristic value Z=K A (A-A 0 )+K B (B-B 0 )+K C (C-C 0 )-K D (D-D 0 ) +n, where n=k E E, E is the abnormal transaction number, K E Is a fifth weight coefficient;
the abnormal transaction times are the transaction times of the target user account and the collection merchant in the illegal transaction wind control list.
By adopting the technical scheme, the transaction detail information comprises the collection identification of the collection merchant, so that whether the user has a transaction relationship with the merchant with suspected illegal transaction risk or not can be conveniently judged later, and the additional characteristic item is used for evaluating the transaction condition of the target user and the collection merchant in the illegal transaction wind control list, so that the identification sensitivity of the abnormal transaction behavior of the user is further improved.
The second object of the present application is achieved by the following technical scheme:
a system for user transaction characteristic analysis and early warning, applied to any one of the above methods for user transaction characteristic analysis and early warning, comprising:
the agreement analysis module is used for acquiring a financial loan agreement of the target user so as to determine the loan amount and the charge settlement rule of the target user;
the transaction characteristic data calculation module is used for acquiring various transaction detail information of a target user and calculating loan utilization rate A, preferential merchant consumption rate B, average fund free period rate C and paying fund rate D of each settlement period;
The transaction characteristic correction data calculation module is used for acquiring income information and asset declaration information of the target user so as to analyze reasonable expense amount of the target user and reasonable preferential merchant expense amount, and calculating reasonable expense correction rate A based on the reasonable expense amount and loan amount 0 Calculating reasonable benefit correction rate B based on reasonable benefit merchant consumption amount and current consumption amount 0 ；
The transaction risk assessment module is used for calculating a transaction risk characteristic value Z=K A (A-A 0 )+K B (B-B 0 )+K C (C-C 0 )-K D (D-D 0 ) +N, where K A For the first weight coefficient, K B For the second weight coefficient, K C For the third weight coefficient, K D For the fourth weight coefficient, C 0 For group average phase-free rate, D 0 Average fund rate of interest for group, N is additional feature item;
a transaction risk early warning module for comparing the transaction risk characteristic value Z with a preset risk threshold value Z 0 In contrast, when Z > Z 0 And generating transaction risk early warning information.
In a preferred example, the present application: the transaction characteristic data calculation module includes:
the loan use rate calculation sub-module is used for calculating the quotient of the used amount and the loan amount based on the preset data sampling frequency to obtain the sampling use rate, and calculating the average value of all the sampling use rates in each settlement period to obtain the loan use rate A;
The discount merchant consumption rate calculation sub-module is used for counting discount merchant consumption amount M paid to the discount merchant in each settlement period k Acquiring corresponding current consumption amount M j Calculating a preferential merchant consumption rate B, wherein,
a fund average free period rate calculation sub-module for obtaining transaction amount M of each transaction in each settlement period based on fee settlement rules and transaction detail information i Transaction date X i And the corresponding repayment date Y i And the current consumption amount M j The average prime phase rate C is calculated, wherein,
a payoff fund rate calculation sub-module for counting payoff amount in each settlement period and calculating payoff amount and current consumption amount M j To obtain the payoff funds rate D.
In a preferred example, the present application: the transaction characteristic correction data calculation module includes:
the compensation capacity amount calculation sub-module is used for acquiring the income information of the target user to determine the income amount, and calculating the product of the income amount and a preset compensation coefficient to obtain the compensation capacity amount;
the existing debt amount analysis submodule is used for acquiring a personal credit report of the target user so as to determine the existing debt amount of the target user in each settlement period;
And the reasonable consumption amount calculation sub-module is used for calculating the difference value between the compensation capacity amount and the existing debt amount of each settlement period so as to obtain the corresponding reasonable consumption amount.
The third object of the present application is achieved by the following technical scheme:
a computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the steps of the method for user transaction characteristic analysis and pre-warning described above when the computer program is executed.
The fourth object of the present application is achieved by the following technical scheme:
a computer readable storage medium storing a computer program which when executed by a processor performs the steps of the method for user transaction signature analysis and pre-warning described above.
In summary, the present application includes at least one of the following beneficial technical effects:
1. acquiring a financial loan agreement of a target user so as to acquire information of a loan amount and a charge settlement rule of the target user; since the behaviors of the illegal use of the loan such as loan cash register generally have the characteristics of high loan amount utilization rate, high preferential merchant consumption rate, long average fund free period, low payment rate and the like, each item of transaction detail information of the target user is acquired so as to know the transaction time, the transaction amount and the transaction type of each order of the user, and the loan utilization rate, the preferential merchant utilization rate, the average fund free period rate and the payment fund rate of the target user in each settlement period are calculated so as to analyze whether the transaction characteristics of the user conform to the characteristics of the cash register or other use of the loan or not; based on income information of the target user, reasonable consumption level of the user is analyzed, reasonable expenditure correction rate is calculated according to reasonable consumption amount and loan amount of the user, reasonable preferential merchant consumption amount required by the user for maintaining property such as real estate, vehicle and the like is analyzed based on property declaration information of the target user, and further reasonable preferential correction rate is calculated according to the reasonable preferential merchant consumption amount and current consumption amount; calculating a transaction risk characteristic value, wherein in the calculation process of the transaction risk characteristic value, loan use rate, preferential merchant use rate, average fund rest period rate and pay fund rate factors are taken into consideration for evaluating transaction risk, reasonable consumption characteristics of users are removed through reasonable expenditure correction rate, reasonable preferential correction rate, group average rest period rate and group average pay fund rate, and the weight of each index is adjusted by utilizing various weight coefficients so as to calculate the transaction risk characteristic value; when the transaction risk characteristic value is larger than the set risk threshold value, transaction risk early warning information is generated to prompt the financial institution that the transaction characteristic of the target user is abnormal, so that the possibility of economic loss and loss amount caused by abnormal transaction behaviors are reduced.
2. According to the preset data sampling frequency, calculating quotient values of the used amount and the loan amount at a plurality of time nodes in one settlement period to obtain sampling utilization rate, calculating the loan utilization rate through an average value of the sampling utilization rates, and better judging time of using the loan amount by a user in one settlement period relative to the utilization rate of only collecting the loan when the settlement period is ended, so that identification accuracy of users with loan cash registering intention is improved; because the user with loan registering intention usually carries out false transaction through the merchant with lower loan payment procedure rate, the user registers the money, thus counting the amount paid to the preferential merchant in each settlement period, calculating the proportion of the consumption amount of the preferential merchant to the consumption amount in the current period, obtaining the consumption rate value of the preferential merchant, and being convenient for improving the recognition sensitivity of the abnormal transaction behavior of the user; based on the fee-extinguishing settlement rules and the transaction detail information, calculating the average free period rate enjoyed by the money involved in each transaction in each settlement period by taking the transaction amount of each transaction as a weight, and identifying abnormal transaction behaviors of a user; and counting the total amount of loans which are used by the user and need to pay interest in each settlement period to obtain the payment amount, and calculating the proportion of the payment amount to the current consumption amount to obtain the payment fund rate, wherein the payment fund rate is used for assisting in judging whether the user has abnormal transaction behaviors.
3. Acquiring income information of a target user to further determine income amount of the target user, and calculating to obtain compensation capacity amount according to the product of the income amount and a preset compensation coefficient so as to acquire fund amount which can be used for repayment of loan in income of the user; acquiring a personal credit report of a target user so as to acquire other liabilities of the user and determine the existing liability amount of the user in each settlement period; and calculating the difference between the compensation capacity amount and the existing liability amount as a reasonable consumption amount so as to judge whether the loan amount used by the user exceeds the reasonable consumption level.
Drawings
Fig. 1 is a flowchart of a method for user transaction characteristic analysis and early warning in accordance with an embodiment of the present application.
Fig. 2 is a schematic block diagram of a system for user transaction characteristic analysis and early warning in a second embodiment of the present application.
Fig. 3 is a schematic view of an apparatus in a third embodiment of the present application.
Detailed Description
The present application is described in further detail below in conjunction with figures 1 to 3.
Example 1
Referring to fig. 1, the present application discloses a method for analyzing and early warning transaction characteristics of a user, which can be used for analyzing transaction characteristics of a user using a financial loan service when using loan funds, so as to send early warning when finding that the user has abnormal transaction behaviors, so as to reduce the possibility of economic loss and loss limit of the financial institution caused by the abnormal transaction behaviors, and the embodiment takes credit cards or other forms of cyclic loans as examples for further detailed description; the method for analyzing and early warning the transaction characteristics of the user specifically comprises the following steps:
S10: and acquiring a financial loan agreement of the target user to determine the loan amount and the charge settlement rule of the target user.
In this embodiment, the financial loan agreement refers to an agreement signed by a user with a financial institution when applying for a financial loan, and specifically records a loan amount and a fee-extinguishing settlement rule, wherein the fee-extinguishing settlement rule records a settlement period start day, a settlement period end day, and a payment date of each settlement period, and the payment date is later than the settlement period end day, and the consumption amount of each settlement period is kept before the payment date, and the consumption amount begins to be paid after exceeding the payment date.
Specifically, the financial loan agreement of the target user is obtained so as to acquire the information of the loan amount and the charge settlement rule of the target user, and the judgment rule of abnormal transaction behaviors such as loan cash register and the like can be conveniently determined according to the specific rules of the financial loan agreement.
S20: and acquiring each item of transaction detail information of the target user, and calculating the loan use rate A, the preferential merchant consumption rate B, the average fund free period rate C and the paying fund rate D of each settlement period.
In this embodiment, the transaction detail information includes transaction time, transaction amount, transaction type and used amount, and the preferential merchant refers to a merchant whose procedure rate paid by using loan is lower than a preset preferential threshold, preferably, the preferential threshold may be set to 0.55%; the transaction time comprises transaction date and time-sharing second information, the transaction type comprises a consumption type and a merchant type, the merchant type comprises a preferential merchant and a non-preferential merchant, and the used amount refers to the sum of the current settlement period including interest and the payment amount required for the future settlement period.
Since loan cash is usually consumed by false transaction and is exchanged for cash from a merchant to move to other uses or to forge money flow, so that larger credit can be obtained later; however, in the common loan consumption scene, merchants are required to pay the commission, so in order to reduce the loan cash-out cost, lawless persons can increase the cash-out amount as much as possible, reduce the commission cost and the paid interest, and therefore, the behaviors of illegal use of loans such as loan cash-out and the like generally have the characteristics of high loan amount use rate, high preferential merchant consumption rate, long average fund free period, low payment rate and the like.
Specifically, each item of transaction detail information of the target user is acquired so as to acquire the transaction time, transaction amount and transaction type of each order of the user, and the loan use rate, preferential merchant use rate, average funds free period rate and pay funds rate of each settlement period of the target user are calculated so as to analyze whether the transaction characteristics of the user conform to the characteristics of loan cash or other actions or not.
Wherein, in step S20, it includes:
s21: and calculating the quotient of the used amount and the loan amount based on the preset data sampling frequency to obtain the sampling utilization rate, and calculating the average value of all the sampling utilization rates in each settlement period to obtain the loan utilization rate A.
In the present embodiment, the data sampling frequency refers to a frequency for calculating the sampling usage rate, and preferably, the data sampling frequency may be set to be once per 1 day.
Specifically, acquiring the used credit data of a plurality of time nodes from a settlement period according to a preset data sampling frequency, calculating the quotient of each used credit and loan credit, and taking the numerical value of the quotient of the used credit and the loan credit as the sampling utilization rate; taking the average value of all sampling use rate data in the settlement period as the loan use rate; compared with the use rate of collecting the loan only once in a settlement period, the method can better judge the time of using the loan amount by a user in one settlement period, improves the identification accuracy of the user with the loan registering intention, and reduces the possibility of mistakenly identifying the person who normally uses the loan as the user with the loan registering intention; wherein, the larger the value of the loan usage rate A, the more likely the user has a loan intention to register.
S22: counting the consumption amount M of the preferential merchant paid to the preferential merchant in each settlement period k Acquiring corresponding current consumption amount M j Calculating a preferential merchant consumption rate B, wherein,
in this embodiment, the consumption amount of the preferential merchant refers to the total amount of transactions between the user and the preferential type merchant in one settlement period; the current consumption amount refers to the total amount of all consumption by the user during one settlement period.
Specifically, since the user with loan registering intention usually carries out false transaction through the merchant with lower loan payment procedure rate, the user registers money, so the amount paid to the preferential merchant in each settlement period by the user is counted, the proportion of the consumption amount of the preferential merchant to the consumption amount in the current period is calculated, the consumption rate value of the preferential merchant is obtained, and the recognition sensitivity of the abnormal transaction behavior of the user is convenient to improve; wherein, the larger the value of the preferential merchant consumption rate B, the more likely the user has a loan overstock intention.
S23: based on the fee-extinguishing settlement rules and the transaction detail information, acquiring the transaction amount M of each transaction in each settlement period i Transaction date X i And the corresponding repayment date Y i And the current consumption amount M j The average prime phase rate C is calculated, wherein,
specifically, the settlement period start day T of the settlement period is determined based on the charge settlement rule and the transaction detail information 1 Day T of settlement period termination 2 Repayment date Y i Transaction date X i Transaction amount M i Current consumption amount M j According to the formulaThe average free period rate C of funds is calculated, so that the function of calculating the average free period rate enjoyed by the money involved in each transaction in each settlement period by taking the transaction amount of each transaction as a weight is realized, and the average free period rate C is used for identifying abnormal transaction behaviors of users; wherein the greater the value of the funds average exemption period rate C, the greater the likelihood that the user will have a loan cash-out intent.
S24: counting the payoff amount in each settlement period, and calculating the payoff amount and the current consumption amount M j To obtain the payoff funds rate D.
In this embodiment, the payment amount refers to the sum of the amounts of money consumed in the settlement period and paid for interest by means of delayed payment, staged payment, payment and cash withdrawal.
Specifically, counting the total amount of loans needing to pay interest used by the user in each settlement period to obtain a payment amount, and calculating the proportion of the payment amount to the current consumption amount to obtain a payment fund rate, wherein the payment fund rate is used for assisting in judging whether the user has abnormal transaction behaviors; wherein the smaller the value of the payoff funds rate D, the greater the likelihood that the user has a loan overstock intent.
S30: acquiring income information and asset declaration information of a target user to analyze reasonable expense amount and reasonable preferential merchant expense amount of the target user, and calculating reasonable expense correction rate A based on the reasonable expense amount and loan amount 0 Calculating reasonable benefit correction rate B based on reasonable benefit merchant consumption amount and current consumption amount 0 。
In the present embodiment, the property declaration information refers to property information declared by the target user at the time of applying the financial loan.
Specifically, the reasonable consumption level of the user is analyzed based on the income information of the target user, the reasonable expense correction rate is calculated according to the reasonable consumption amount and the loan amount of the user, the reasonable preferential merchant consumption amount required by the user for maintaining the property such as the property, the vehicle and the like is analyzed based on the property declaration information of the target user, and the reasonable preferential correction rate is calculated according to the reasonable preferential merchant consumption amount and the current consumption amount.
Wherein, in step S30, it includes:
s31: and acquiring income information of the target user to determine income amount, and calculating the product of the income amount and a preset compensation coefficient to obtain compensation capacity amount.
In this embodiment, preferably, the compensation coefficient may be set to 0.5.
Specifically, acquiring income information of a target user to further determine income amount of the target user, calculating a product of the income amount and a preset compensation coefficient to obtain compensation capacity amount, so as to obtain fund amount available for repayment of loan in income of the user; the compensation factor is set to evaluate the amount of funds available to pay back the debt without affecting the user's life needs.
S32: a personal credit report of the target user is obtained to determine the existing debt amount of the target user at each settlement period.
In this embodiment, the personal credit report records data such as each debt owed by the target user, and the return period number of each debt, the amount to be returned per period, and the like; the existing debt amount refers to the amount of the payable of the target user for other debts than the loan issued by the present financial institution in each settlement period.
Specifically, a personal credit report of the target user is obtained to obtain other liabilities of the user, and the existing liability amount of the user in each settlement period is determined.
S33: and calculating the difference between the compensation capacity amount and the existing debt amount of each settlement period to obtain the corresponding reasonable consumption amount.
Specifically, the difference between the payable amount and the existing debt amount is calculated to obtain a reasonable consumption amount, so as to subsequently determine whether the loan amount used by the user exceeds the reasonable consumption level.
Wherein, in step S30, further comprising:
s34: asset declaration information of the target user is acquired to determine the property, number of vehicles and specifications owned by the target user.
Specifically, since the common loan payment procedure rate preferential merchants include operators related to civil basic consumption demands, such as fuel consumption, water cost, electric cost, fuel gas cost, property cost, public transportation cost and the like, the property declaration information of the target user is acquired so as to acquire the property owned by the target user, the number and the specification of vehicles and facilitate the subsequent calculation of reasonable preferential merchant consumption amount.
S35: based on the property possessed by the target user, the number and specifications of vehicles, the reasonable preferential merchant spending amount per settlement period of the target user is assessed.
Specifically, the amount that the user consumes at the preferential merchant for maintaining or supporting his premises, vehicles, commutes at each settlement period is determined based on the number and specifications of the premises, vehicles owned by the target user to determine a reasonable preferential merchant consumption amount.
S40: calculating a transaction risk characteristic value Z-K A (A-A 0 )+K B (B-B 0 )+K C (C-C 0 )-K D (D-D 0 ) +N, where K A For the first weight coefficient, K B For the second weight coefficient, K C For the third weight coefficient, K D For the fourth weight coefficient, C 0 For group average phase-free rate, D 0 And (3) paying funds rate for the group average, wherein N is an additional characteristic item.
In this embodiment, the transaction risk feature value refers to data for evaluating the degree of risk of the transaction feature when the user uses the loan daily; the first weight coefficient, the second weight coefficient, the third weight coefficient and the fourth weight coefficient refer to coefficients used for setting the weights of all influence factor indexes of the transaction risk characteristic values, and specific values of all weight coefficients can be selected according to actual conditions; the group average exemption period rate refers to the average value of the average exemption period rate of other users who apply for the same financial loan service with the target user; the group average payoff fund rate refers to the average value of the average payoff fund rates of other users who apply for the same financial loan service with the target user; the additional feature value refers to other influencing factor index items for calculating the transaction risk feature value, and can be increased according to actual requirements.
Specifically, calculating a transaction risk characteristic value, wherein in the calculation process of the transaction risk characteristic value, loan use rate, preferential merchant use rate, average fund rest period rate and pay fund rate factors are taken into consideration for evaluating the transaction risk, reasonable consumption characteristics of users are removed through reasonable expenditure correction rate, reasonable preferential correction rate, group average rest period rate and group average pay fund rate, and the weight of each index is adjusted by utilizing various weight coefficients so as to calculate the transaction risk characteristic value.
Wherein, in the present embodiment, the transaction detail information includes a collection identification of a collection merchant; the abnormal transaction times are the transaction times of the target user account and the collection merchant in the illegal transaction wind control list; the offensive transaction wind control list refers to a list of merchants with suspected offensive transactions determined by a financial institution, and a specific method for determining the offensive transaction wind control list is known to a person skilled in the art from the prior art; the fifth weight coefficient is a coefficient for setting the weight of the factor index for influencing the abnormal number of transactions of the transaction risk characteristic value, and the specific value thereof can be selected according to the actual situation.
Specifically, let E be the number of abnormal transactions, K E For the fifth weight coefficient, by n=k E E, calculating an additional characteristic item so as to calculate a transaction risk characteristic value; the transaction detail information comprises a collection identification of a collection merchant, so that whether a user has a transaction relation with the merchant suspected of the illegal transaction risk or not is conveniently judged, and the additional characteristic item is used for evaluating the transaction condition of the target user and the collection merchant in the illegal transaction wind control list, so that the identification sensitivity of the abnormal transaction behavior of the user is further improved; wherein, the larger the value of the abnormal transaction number is, the more likely the user has a loan registering intention.
S50: the transaction risk characteristic value Z and a preset risk threshold value Z are combined 0 In contrast, when Z > Z 0 And generating transaction risk early warning information.
In this embodiment, the risk threshold is threshold data for comparing with the transaction risk feature value, and is used to determine whether the risk of the abnormal transaction behavior of the target user reaches the degree of early warning, where the specific value of the risk threshold may be set according to the actual requirement.
Specifically, when the transaction risk characteristic value is larger than the set risk threshold value, transaction risk early warning information is generated to prompt the financial institution that the transaction characteristic of the target user is abnormal, so that the possibility of economic loss and loss amount caused by abnormal transaction behaviors are reduced.
It should be understood that the sequence number of each step in the foregoing embodiment does not mean that the execution sequence of each process should be determined by the function and the internal logic of each process, and should not limit the implementation process of the embodiment of the present application in any way.
Example two
A system for analyzing and pre-warning user transaction characteristics corresponds to the method for analyzing and pre-warning user transaction characteristics in the embodiment.
As shown in fig. 2, the system for analyzing and early warning the transaction characteristics of the user comprises a protocol analysis module, a transaction characteristic data calculation module, a transaction characteristic correction data calculation module, a transaction risk assessment module and a transaction risk early warning module. The detailed description of each functional module is as follows:
the agreement analysis module is used for acquiring a financial loan agreement of the target user so as to determine the loan amount and the charge settlement rule of the target user;
the transaction characteristic data calculation module is used for acquiring various transaction detail information of a target user and calculating loan utilization rate A, preferential merchant consumption rate B, average fund free period rate C and paying fund rate D of each settlement period;
the transaction characteristic correction data calculation module is used for acquiring income information and asset declaration information of the target user so as to analyze reasonable expense amount of the target user and reasonable preferential merchant expense amount, and calculating reasonable expense correction rate A based on the reasonable expense amount and loan amount 0 Calculating reasonable benefit correction rate B based on reasonable benefit merchant consumption amount and current consumption amount 0 ；
The transaction risk assessment module is used for calculating a transaction risk characteristic value Z=K A (A-A 0 )+K B (B-B 0 )+K C (C-C 0 )-K D (D-D 0 ) +N, where K A For the first weight coefficient, K B For the second weight coefficient, K C For the third weight coefficient, K D For the fourth weight coefficient, C 0 For group average phase-free rate, D 0 Average fund rate of interest for group, N is additional feature item;
a transaction risk early warning module for comparing the transaction risk characteristic value Z with a preset risk threshold value Z 0 In contrast, when Z > Z 0 And generating transaction risk early warning information.
Wherein, the transaction characteristic data calculation module includes:
the loan use rate calculation sub-module is used for calculating the quotient of the used amount and the loan amount based on the preset data sampling frequency to obtain the sampling use rate, and calculating the average value of all the sampling use rates in each settlement period to obtain the loan use rate A;
the discount merchant consumption rate calculation sub-module is used for counting discount merchant consumption amount M paid to the discount merchant in each settlement period k Acquiring corresponding current consumption amount M j Calculating a preferential merchant consumption rate B, wherein,
a fund average free period rate calculation sub-module for obtaining transaction amount M of each transaction in each settlement period based on fee settlement rules and transaction detail information i Transaction date X i And the corresponding repayment date Y i And the current consumption amount M j The average prime phase rate C is calculated, wherein,
a payoff fund rate calculation sub-module for counting payoff amount in each settlement period and calculating payoff amount and current consumption amount M j To obtain the payoff funds rate D.
Wherein, the transaction characteristic correction data calculation module includes:
the compensation capacity amount calculation sub-module is used for acquiring the income information of the target user to determine the income amount, and calculating the product of the income amount and a preset compensation coefficient to obtain the compensation capacity amount;
the existing debt amount analysis submodule is used for acquiring a personal credit report of the target user so as to determine the existing debt amount of the target user in each settlement period;
and the reasonable consumption amount calculation sub-module is used for calculating the difference value between the compensation capacity amount and the existing debt amount of each settlement period so as to obtain the corresponding reasonable consumption amount.
Wherein, the transaction characteristic correction data calculation module further comprises:
the asset declaration information analysis sub-module is used for acquiring asset declaration information of the target user so as to determine the property owned by the target user, the number and the specification of vehicles;
And the reasonable preferential merchant consumption evaluation sub-module is used for evaluating the reasonable preferential merchant consumption amount of each settlement period of the target user based on the property owned by the target user, the number and the specification of the vehicles.
For specific limitations regarding the system for user transaction characteristic analysis and pre-warning, reference may be made to the above limitations regarding the method for user transaction characteristic analysis and pre-warning, and details thereof will not be repeated herein; all or part of each module in the system for analyzing and early warning the transaction characteristics of the user can be realized by software, hardware and the combination thereof; the above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
Example III
A computer device, which may be a server, may have an internal structure as shown in fig. 3. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer equipment is used for storing data such as financial loan agreements, transaction detail information, loan utilization rate, preferential merchant consumption rate, average fund free period rate, pay-off fund rate, income information, property declaration information, reasonable consumption amount, reasonable preferential merchant consumption amount, reasonable expenditure correction rate, reasonable preferential correction rate, transaction risk characteristic value, preset risk threshold value, transaction risk early warning information and the like. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a method for user transaction characteristic analysis and pre-warning.
In one embodiment, a computer device is provided comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, the processor implementing the following steps when executing the computer program:
s10: acquiring a financial loan agreement of a target user to determine a loan amount and a charge settlement rule of the target user;
s20: acquiring each item of transaction detail information of a target user, and calculating loan use rate A, preferential merchant consumption rate B, average fund free period rate C and paying fund rate D of each settlement period;
s30: acquiring income information and asset declaration information of a target user to analyze reasonable expense amount and reasonable preferential merchant expense amount of the target user, and calculating reasonable expense correction rate A based on the reasonable expense amount and loan amount 0 Calculating reasonable benefit correction rate B based on reasonable benefit merchant consumption amount and current consumption amount 0 ；
S40: calculating a transaction risk feature value z=k A (A-A 0 )+K B (B-B 0 )+K C (C-C 0 )-K D (D-D 0 ) +N, where K A For the first weight coefficient, K B For the second weight coefficient, K C For the third weight coefficient, K D For the fourth weight coefficient, C 0 For group average phase-free rate, D 0 Average fund rate of interest for group, N is additional feature item;
S50: the transaction risk characteristic value Z and a preset risk threshold value Z are combined 0 In contrast, when Z > Z 0 And generating transaction risk early warning information.
In one embodiment, a computer readable storage medium is provided having a computer program stored thereon, which when executed by a processor, performs the steps of:
s10: acquiring a financial loan agreement of a target user to determine a loan amount and a charge settlement rule of the target user;
s20: acquiring each item of transaction detail information of a target user, and calculating loan use rate A, preferential merchant consumption rate B, average fund free period rate C and paying fund rate D of each settlement period;
s30: acquiring income information and asset declaration information of a target user to analyze reasonable expense amount and reasonable preferential merchant expense amount of the target user, and calculating reasonable expense correction rate A based on the reasonable expense amount and loan amount 0 Calculating reasonable benefit correction rate B based on reasonable benefit merchant consumption amount and current consumption amount 0 ；
S40: calculating a transaction risk feature value z=k A (A-A 0 )+K B (B-B 0 )+K C (C-C 0 )-K D (D-D 0 ) +N, where K A For the first weight coefficient, K B For the second weight coefficient, K C For the third weight coefficient, K D For the fourth weight coefficient, C 0 For group average phase-free rate, D 0 Average fund rate of interest for group, N is additional feature item;
s50: the transaction risk characteristic value Z and a preset risk threshold value Z are combined 0 In contrast, when Z > Z 0 And generating transaction risk early warning information.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the various embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink), DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-described functions.
The above embodiments are only for illustrating the technical solution of the present application, and are not limiting; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art will understand; the technical scheme described in the foregoing embodiments can be modified or some of the features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present application, and are intended to be included in the scope of the present application.

Claims (10)

1. A method for user transaction characteristic analysis and pre-warning, comprising:
acquiring a financial loan agreement of a target user to determine a loan amount and a charge settlement rule of the target user;
Acquiring each item of transaction detail information of a target user, and calculating loan use rate A, preferential merchant consumption rate B, average fund free period rate C and paying fund rate D of each settlement period;
acquiring income information and asset declaration information of a target user to analyze reasonable expense amount and reasonable preferential quotation of the target userUser consumption amount, and reasonable expenditure correction rate is calculated based on reasonable consumption amount and loan amountCalculating a reasonable offer correction rate based on the reasonable-offer merchant consumption amount and the current-period consumption amount>；
Calculating transaction risk feature valuesWherein->Is the first weight coefficient,/->Is the second weight coefficient->Is a third weight coefficient->For the fourth weight coefficient, +.>For the average phase-free rate of the population, +.>Average fund rate of interest for group, N is additional feature item;
characterizing the transaction risk valuesAnd a preset risk threshold->In contrast, when->＞/>Generating transaction risk early warning information;
the transaction detail information comprises transaction time, transaction amount, transaction type and used amount, and the preferential merchant refers to a merchant with a procedure rate of payment by using loans lower than a preset preferential threshold.
2. A method for user transaction characteristic analysis and pre-warning according to claim 1, characterized in that: the calculating of the loan usage rate A, the preferential merchant consumption rate B, the average fund free period rate C and the paying fund rate D of each settlement period comprises the following steps:
Calculating the quotient of the used amount and the loan amount based on a preset data sampling frequency to obtain sampling utilization rate, and calculating the average value of all sampling utilization rates in each settlement period to obtain a loan utilization rate A;
counting the consumption amount of the preferential merchant paid to the preferential merchant in each settlement periodObtaining corresponding current consumption amount +.>Calculating a preferential merchant consumption rate B, wherein ∈G>；
Based on the fee-extinguishing settlement rules and the transaction detail information, acquiring the transaction amount of each transaction in each settlement periodDate of transaction->And the corresponding repayment date->And the current consumption amount +.>The average prime phase rate C is calculated, wherein,；
counting the payoff amount in each settlement period, and calculating the payoff amount and the current consumption amountTo obtain the payoff funds rate D;
the fee-extinguishing settlement rule comprises a settlement period starting day of each settlement periodDay of settlement period termination->And repayment date->The transaction time includes a transaction date.
3. A method for user transaction characteristic analysis and pre-warning according to claim 1, characterized in that: the obtaining the income information and the asset declaration information of the target user to analyze the reasonable consumption amount of the target user and the reasonable preferential merchant consumption amount comprises the following steps:
Acquiring income information of a target user to determine income amount, and calculating the product of the income amount and a preset compensation coefficient to obtain compensation capacity amount;
acquiring a personal credit report of a target user to determine the existing debt amount of the target user in each settlement period;
and calculating the difference between the compensation capacity amount and the existing debt amount of each settlement period to obtain the corresponding reasonable consumption amount.
4. A method for user transaction characteristic analysis and pre-warning according to claim 3, characterized in that: the obtaining the income information and the asset declaration information of the target user to analyze the reasonable consumption amount of the target user and the reasonable preferential merchant consumption amount, and the method further comprises the following steps:
acquiring asset declaration information of a target user to determine the property owned by the target user, the number and the specification of vehicles;
based on the property possessed by the target user, the number and specifications of vehicles, the reasonable preferential merchant spending amount per settlement period of the target user is assessed.
5. A method for user transaction characteristic analysis and pre-warning according to claim 1, characterized in that: the transaction detail information comprises a collection identification of a collection merchant;
The calculating transaction risk characteristic valueWherein->E is the number of abnormal transactions, ++>Is a fifth weight coefficient;
the abnormal transaction times are the transaction times of the target user account and the collection merchant in the illegal transaction wind control list.
6. A system for user transaction characteristic analysis and pre-warning, characterized in that it is applied to the method for user transaction characteristic analysis and pre-warning according to any one of claims 1 to 5, comprising:
the agreement analysis module is used for acquiring a financial loan agreement of the target user so as to determine the loan amount and the charge settlement rule of the target user;
the transaction characteristic data calculation module is used for acquiring various transaction detail information of a target user and calculating loan utilization rate A, preferential merchant consumption rate B, average fund free period rate C and paying fund rate D of each settlement period;
the transaction characteristic correction data calculation module is used for acquiring income information and asset declaration information of the target user so as to analyze reasonable expense amount of the target user and reasonable preferential merchant expense amount, and calculating reasonable expense correction rate based on the reasonable expense amount and loan amountCalculating a reasonable offer correction rate based on the reasonable-offer merchant consumption amount and the current-period consumption amount >；
The transaction risk assessment module is used for calculating a transaction risk characteristic valueWherein->Is the first weight coefficient,/->Is the second weight coefficient->Is a third weight coefficient->For the fourth weight coefficient, +.>For the average phase-free rate of the population, +.>Average fund rate of interest for group, N is additional feature item;
a transaction risk early warning module for warning the transaction risk characteristic valueAnd a preset risk threshold->In contrast, when->＞/>And generating transaction risk early warning information.
7. A system for user transaction characteristic analysis and early warning according to claim 6, characterized in that: the transaction characteristic data calculation module includes:
the loan use rate calculation sub-module is used for calculating the quotient of the used amount and the loan amount based on the preset data sampling frequency to obtain the sampling use rate, and calculating the average value of all the sampling use rates in each settlement period to obtain the loan use rate A;
the discount merchant consumption rate calculation sub-module is used for counting discount merchant consumption amount paid to the discount merchant in each settlement periodObtaining corresponding current consumption amount +.>Calculating a preferential merchant consumption rate B, wherein ∈G>；
Fund average rest period rate calculation sub-module, using Acquiring transaction amount of each transaction in each settlement period based on fee-extinguishing settlement rules and transaction detail informationDate of transaction->And the corresponding repayment date->And the current consumption amount +.>Calculating a fund average rest period rate C, wherein +.>；
The fund rate calculation sub-module is used for counting the fund amount in each settlement period and calculating the fund amount and the current consumption amountTo obtain the payoff funds rate D.
8. A system for user transaction characteristic analysis and early warning according to claim 6, characterized in that: the transaction characteristic correction data calculation module includes:
the compensation capacity amount calculation sub-module is used for acquiring the income information of the target user to determine the income amount, and calculating the product of the income amount and a preset compensation coefficient to obtain the compensation capacity amount;
the existing debt amount analysis submodule is used for acquiring a personal credit report of the target user so as to determine the existing debt amount of the target user in each settlement period;
and the reasonable consumption amount calculation sub-module is used for calculating the difference value between the compensation capacity amount and the existing debt amount of each settlement period so as to obtain the corresponding reasonable consumption amount.
9. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor, when executing the computer program, carries out the steps of the system method for user transaction characteristic analysis and pre-warning according to any one of claims 1 to 5.
10. A computer-readable storage medium storing a computer program, characterized in that the computer program when executed by a processor implements the steps of the system method for user transaction characteristic analysis and early warning according to any one of claims 1 to 5.
CN202311776426.1A 2023-12-21 Method and system for user transaction characteristic analysis and early warning Active CN117726341B (en)

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Application Number Priority Date Filing Date Title
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CN117726341B CN117726341B (en) 2024-05-17

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Publication number Priority date Publication date Assignee Title
AU2009202196A1 (en) * 2009-06-01 2010-12-16 Advanced Merchant Payments Limited Loan portfolio management and automatic loan repayment method and system
KR20140134492A (en) * 2013-05-14 2014-11-24 주식회사 우리은행 Method of loaning and repaying loaned money, server performing the same and system performing the same
CN112767127A (en) * 2021-01-21 2021-05-07 中信银行股份有限公司 Loan fund monitoring method and device
CN114331683A (en) * 2021-12-29 2022-04-12 北京优品三悦科技发展有限公司 Loan method and device, storage medium and electronic device

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
AU2009202196A1 (en) * 2009-06-01 2010-12-16 Advanced Merchant Payments Limited Loan portfolio management and automatic loan repayment method and system
KR20140134492A (en) * 2013-05-14 2014-11-24 주식회사 우리은행 Method of loaning and repaying loaned money, server performing the same and system performing the same
CN112767127A (en) * 2021-01-21 2021-05-07 中信银行股份有限公司 Loan fund monitoring method and device
CN114331683A (en) * 2021-12-29 2022-04-12 北京优品三悦科技发展有限公司 Loan method and device, storage medium and electronic device

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