Method for identifying cheating in use of online car-hailing order coupons

Abstract

The invention discloses an online car-hailing order coupon use cheating identification method, which comprises the following steps: S1, starting to screen orders completed on the current day; s2, further judging whether the order uses the coupon or not, if not, ending the process, and if so, entering the next judgment; s3, judging whether the order belongs to the first order of the new user, and if so, recording the new user equipment imei, the mobile phone number, the coupon source and the order amount; s4, further judging the number of accounts corresponding to the user equipment imei, automatically identifying and checking whether the use of the order coupon is abnormal or not, improving the security defense capability of the platform coupon method, and fighting against the scene and behavior of cheating by using the coupon; the platform is helped to reduce loss and improve activity roi; the identified abnormal order and abnormal user can be used for a new data source for platform risk management and control, and can help to improve the recall rate and accuracy of platform risk control orders.

Description

Technical Field

[0001] The present invention belongs to the technical field of online car-hailing platforms, and specifically relates to a method for identifying cheating in the use of coupons for online car-hailing orders. Background Art

[0002] In online ride-hailing orders, the issuance and use of coupons is an important factor in promoting users to place orders. Some large coupons are often obtained and used by many black industries or abnormal users through abnormal means. There are even cases where orders are bought and sold based on the coupon discount amount.

[0003] The current platform is not capable of identifying fraudulent use of coupons and is unable to effectively identify fraudulent use of coupons. It lacks the ability to systematically identify whether there are any anomalies in the use of coupons in orders.

[0004] To this end, the present invention designs a method for identifying cheating in the use of coupons for online ride-hailing orders. Summary of the invention

[0005] The purpose of the present invention is to provide a method for identifying cheating in the use of coupons for online ride-hailing orders, so as to solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above-mentioned purpose, the present invention provides the following technical solution: a method for identifying cheating in the use of coupons for online car-hailing orders, the specific steps comprising: S1: start, filter the orders completed on the day;

[0007] S2: further determine whether the order uses the coupon. If not, end the process. If so, proceed to the next step.

[0008] S3: Determine whether this order is the first order of a new user. If so, record the new user's device IMEI, mobile phone number, coupon source, and order amount;

[0009] S4: further determine the number of accounts corresponding to the IMEI of the user device. If it is greater than a, it is directly determined that there is abnormal use of the order coupon; if it is less than a, proceed to the next step;

[0010] S5: Determine whether the coupon discount ratio exceeds threshold b, and the estimated ratio [actual amount / estimated amount] exceeds threshold c. If so, it is determined that the order has been used to make a profit by using coupons, and it is determined that the order coupon has been used abnormally; if not, proceed to the next step;

[0011] S6: Determine whether the proportion of the driver's coupon orders on the day is above the threshold d; if so, further determine whether the driver has a risk control record within 30 days. If so, determine that there is abnormal use of coupons; if not, end the determination;

[0012] S7: According to step S3, if the order belongs to an old user, the driver information, order amount, and coupon ratio are recorded;

[0013] S8: Determine whether the user's coupon fee ratio is greater than or equal to the threshold value e, and the average amount of the orders in the past n days is greater than m. If so, it is considered that the coupon fee ratio is high, and it is determined that there is abnormal use of coupons; if not, the process ends;

[0014] S9: Filter out orders with abnormal order coupons and further enter the risk control process.

[0015] Preferably, in step S4, a is a threshold value, which can be set manually according to the platform conditions.

[0016] Preferably, in step S5, the threshold b can be set manually according to the platform conditions, and the threshold c can also be set manually according to the platform conditions.

[0017] Preferably, in step S6, the threshold d can be set according to the platform conditions.

[0018] Preferably, in step S8, the threshold e can be set according to the platform conditions, and m can also be set according to the platform conditions.

[0019] Compared with the prior art, the beneficial effects of the present invention are: automatically identifying and verifying whether there are any abnormal situations in the use of order coupons, improving the security defense capabilities of the platform's coupon method, and combating scenarios and behaviors of cheating with coupons; helping the platform reduce losses and improve activity ROI; the identified abnormal orders and abnormal users can be used as a new data source for platform risk management, which can help improve the recall rate and accuracy of the platform's risk control orders. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a schematic diagram of the process of the present invention. DETAILED DESCRIPTION

[0021] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0022] See also Figure 1 ,The present invention provides a technical solution: a method for identifying cheating in the use of coupons for online car-hailing orders, the specific steps include: S1: start, filter the orders completed on the day;

[0023] S2: further determine whether the order uses the coupon. If not, end the process. If so, proceed to the next step.

[0024] S3: Determine whether this order is the first order of a new user. If so, record the new user's device IMEI, mobile phone number, coupon source, and order amount;

[0025] S4: further determine the number of accounts corresponding to the IMEI of the user device. If it is greater than 3, it is directly determined that there is abnormal use of the order coupon; if it is less than 3, proceed to the next step;

[0026] S5: Determine whether the coupon discount ratio exceeds 30% and the estimated ratio [actual amount / estimated amount] exceeds 2. If so, it is determined that the order has been used to make a small amount of money, and it is determined that the order coupon has been used abnormally; if not, proceed to the next step;

[0027] S6: Determine whether the driver's coupon orders account for more than 90% of the day; if so, further determine whether the driver has a risk control record within 30 days. If so, it is determined that there is abnormal use of coupons. If not, end the judgment;

[0028] S7: According to step S3, if the order belongs to an old user, the driver information, order amount, coupon ratio, etc. are recorded;

[0029] S8: Determine whether the user's coupon fee ratio is greater than or equal to 25% and the average amount of the last n days is greater than m. If so, it is considered that the coupon fee ratio is high and the coupon fee is abnormally used. If not, the process ends.

[0030] S9: Filter out orders with abnormal order coupons and further enter the risk control process.

[0031] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for identifying cheating in the use of coupons for online ride-hailing orders, characterized by: The specific steps include: S1: Start, filter the orders completed on the day; S2: further determine whether the order uses the coupon. If not, end the process. If so, proceed to the next step. S3: Determine whether this order is the first order of a new user. If so, record the new user's device IMEI, mobile phone number, coupon source, and order amount; S4: further determine the number of accounts corresponding to the IMEI of the user device. If it is greater than a, it is directly determined that there is abnormal use of the order coupon; if it is less than a, proceed to the next step; S5: Determine whether the coupon discount ratio exceeds threshold b, and the estimated ratio [actual amount / estimated amount] exceeds threshold c. If so, it is determined that the order has been used to make a profit by using coupons, and it is determined that the order coupon has been used abnormally; if not, proceed to the next step; S6: Determine whether the proportion of the driver's coupon orders on the day is above the threshold d; if so, further determine whether the driver has a risk control record within 30 days. If so, determine that there is abnormal use of coupons; if not, end the determination; S7: According to step S3, if the order belongs to an old user, the driver information, order amount, and coupon ratio are recorded; S8: Determine whether the user's coupon fee ratio is greater than or equal to the threshold value e, and the average amount of the orders in the past n days is greater than m. If so, it is considered that the coupon fee ratio is high, and it is determined that there is abnormal use of coupons; if not, the process ends; S9: Filter out orders with abnormal order coupons and further enter the risk control process.

2. A method for identifying cheating in the use of coupons for online ride-hailing orders according to claim 1, characterized in that: In step S4, a is a threshold value, which can be set manually according to the platform conditions.

3. A method for identifying cheating in the use of coupons for online ride-hailing orders according to claim 1, characterized in that: In step S5, the threshold b can be set manually according to the platform conditions, and the threshold c can also be set manually according to the platform conditions.

4. A method for identifying cheating in the use of online car-hailing order coupons according to claim 1, characterized in that: In step S6, the threshold d can be set according to the platform conditions.

5. A method for identifying cheating in the use of online car-hailing order coupons according to claim 1, characterized in that: In step S8, the threshold e can be set according to the platform conditions, and m can also be set according to the platform conditions.

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