CN113505161A

CN113505161A - Service query and verification method based on big data and cloud computing

Info

Publication number: CN113505161A
Application number: CN202110904983.1A
Authority: CN
Inventors: 何青波
Original assignee: Individual
Current assignee: Individual
Priority date: 2021-01-20
Filing date: 2021-01-20
Publication date: 2021-10-15
Also published as: CN112669163B; CN112669163A; CN113505162A

Abstract

The application provides a business query and verification method based on big data and cloud computing, and relates to the technical field of financial business management. In the present application, first, it is determined whether financial service inquiry request information sent by an inquiry apparatus belongs to legal inquiry request information. Secondly, if the financial service inquiry request information belongs to illegal inquiry request information, inquiry check information is generated. And then, sending the query verification information to the verification equipment bound by the target user. And finally, if first verification feedback information sent by the verification equipment is received, sending the financial service information corresponding to the target user to the query equipment, wherein the first verification feedback information is generated based on the verification equipment when the verification of the financial service query request information is successful. Based on the method, the problem that the service safety and the query effectiveness are difficult to be effectively considered in the existing financial service management technology can be solved.

Description

Service query and verification method based on big data and cloud computing

Technical Field

The application relates to the technical field of financial business management, in particular to a business query and verification method and system based on big data and cloud computing.

Background

The application range of random computer technology and internet technology is continuously expanded due to the continuous development of the random computer technology and the internet technology. For example, the application in financial business greatly facilitates the business operation of users. However, the inventor researches and discovers that the existing financial business management technology has the problem that the business safety and the query effectiveness are difficult to be effectively compatible particularly for the query of some financial businesses.

Disclosure of Invention

In view of this, an object of the present application is to provide a financial transaction management method and system based on big data and cloud computing, so as to solve the problem that the service security and the query validity in the existing financial transaction management technology are difficult to be considered effectively.

In order to achieve the above purpose, the embodiment of the present application adopts the following technical solutions:

a financial business management method based on big data and cloud computing comprises the following steps:

determining whether financial service query request information sent by query equipment belongs to legal query request information or not, wherein the financial service query request information is generated aiming at a target user;

if the financial service inquiry request information belongs to illegal inquiry request information, generating inquiry check information, wherein the inquiry check information carries identification information of the inquiry equipment;

sending the query verification information to verification equipment bound by the target user, wherein the verification equipment is used for verifying the financial service query request information based on the identification information;

and if first verification feedback information sent by the verification equipment is received, sending the financial service information corresponding to the target user to the query equipment, wherein the first verification feedback information is generated based on the verification equipment when the verification of the financial service query request information is successful.

In a possible embodiment, in the financial service processing method based on big data, the step of determining whether the financial service inquiry request information sent by the inquiry device belongs to legal inquiry request information includes:

acquiring financial service query request information sent by query equipment, wherein the financial service query request information is generated aiming at a target user;

based on the identification information of the query equipment, acquiring a plurality of pieces of historical financial service query request information sent by the query equipment by performing multiple query request operations on a plurality of different user objects historically;

and determining whether the financial service inquiry request information belongs to legal inquiry request information or not based on the plurality of pieces of historical financial service inquiry request information.

In a possible embodiment, in the financial transaction processing method based on big data, the step of determining whether the financial transaction query request information belongs to legal query request information based on the plurality of pieces of historical financial transaction query request information includes:

a, according to the generation time information of each piece of historical financial service query request information, sequencing the plurality of pieces of historical financial service query request information in the sequence of generation time from morning to evening to obtain a corresponding query request information sequence;

b, clustering according to the generation time information of each piece of historical financial service query request information to obtain a plurality of query request information clusters, and determining one piece of historical financial service query request information in each query request information cluster as key historical financial service query request information to obtain a plurality of pieces of key historical financial service query request information;

c, in the query request information sequence, confirming a plurality of pieces of historical financial service query request information by the quantity of preset interval information based on the historical financial service query request information between two adjacent pieces of key historical financial service query request information in the plurality of pieces of key historical financial service query request information;

d, generating the query request information screening sequence according to the plurality of pieces of historical financial service query request information and the key historical financial service query request information which are added and confirmed;

e, in the query request information screening sequence, acquiring historical financial service query request information corresponding to a sequence starting position to obtain first historical financial service query request information, and acquiring historical financial service query request information corresponding to a sequence ending position to obtain second historical financial service query request information, wherein the sequence starting position is the sum of a first position and a preset position number in the query request information screening sequence, and the sum of the sequence ending position and the preset position number is a last position in the query request information screening sequence;

f, determining historical financial service query request information sets respectively corresponding to a first generation time average value and a second generation time average value on the query request information screening sequence according to the generation time information corresponding to the first historical financial service query request information and the second historical financial service query request information and the generation time span information of the query request information screening sequence;

g, obtaining a query request information representative sequence by obtaining a piece of historical financial service query request information in a historical financial service query request information set corresponding to the first generation time average value from the query request information screening sequence, and reaching the piece of historical financial service query request information in the historical financial service query request information set corresponding to the second generation time average value through the first historical financial service query request information and the second historical financial service query request information;

h, calculating a first sequence position distance between the sequence starting position and the position of the generation time average value corresponding to the query request information representative sequence, and a second sequence position distance between the position of the generation time average value and the sequence ending position;

i, calculating a third sequence position distance between the position of the first generation time average value and the position of the second generation time average value;

j, multiplying the third sequence position distance by a preset weight value to obtain a first numerical value;

k, adding the first numerical value, the first sequence position distance and the second sequence position distance to obtain a second numerical value, and judging the size of the second numerical value and a preset threshold value;

if the second value is larger than or equal to the preset threshold value, determining whether the financial service inquiry request information belongs to legal inquiry request information or not based on the historical financial service inquiry request information in the inquiry request information representative sequence.

In a possible embodiment, in the financial transaction processing method based on big data, the step of determining whether the financial transaction query request information belongs to legal query request information based on the plurality of pieces of historical financial transaction query request information further includes:

and if the second value is smaller than the preset threshold value, determining whether the financial service query request information belongs to legal query request information or not based on the historical financial service query request information in the query request information screening sequence.

if the second numerical value is smaller than the preset threshold value, clustering historical financial service query request information included in each query request information cluster to obtain at least one query request information sub-cluster;

determining a piece of historical financial service query request information in each query request information sub-cluster as key historical financial service query request information to obtain a plurality of pieces of new key historical financial service query request information;

and c, executing the step c again based on the plurality of pieces of new key historical financial service inquiry request information.

if the second value is smaller than the preset threshold value, updating the preset interval information quantity to obtain a new preset interval information quantity;

and c, executing the step c again based on the new preset interval information quantity.

if the second value is smaller than the preset threshold value, updating the number of the preset positions to obtain a new number of the preset positions;

and e, executing the step e again based on the new preset position number.

if the second value is smaller than the preset threshold value, updating the preset weight value to obtain a new preset weight value;

and j is executed again based on the new preset weight value.

according to the generation time information of each piece of historical financial service query request information, sequencing the plurality of pieces of historical financial service query request information in the sequence of generation time from morning to evening to obtain a corresponding query request information sequence;

in the query request information sequence, determining a plurality of candidate historical financial service query request information based on time span information of generation time information of the plurality of pieces of historical financial service query request information and the information quantity of the plurality of pieces of historical financial service query request information, and determining a relevant time range corresponding to each piece of candidate historical financial service query request information based on the quantity of the historical financial service query request information between two adjacent pieces of candidate historical financial service query request information, wherein the relevant time range comprises the generation time of the corresponding candidate historical financial service query request information;

for each piece of candidate historical financial service query request information, determining other historical financial service query request information corresponding to the user object having the incidence relation with the user object of the candidate historical financial service query request information in the relevant time range based on the relevant time range corresponding to the candidate historical financial service query request information, or when there is no other historical financial service inquiry request information corresponding to the user object with the association relation, determining other historical financial transaction query request information having a maximum sequence interval position from the candidate historical financial transaction query request information within the relevant time frame, and based on each set of candidate historical financial transaction query request information and other historical financial transaction query request information, historical financial service inquiry request information between the candidate historical financial service inquiry request information and the historical financial service inquiry request information to form an inquiry request information candidate set of the candidate historical financial service inquiry request information;

determining a plurality of pieces of target historical financial service query request information from each query request information candidate set according to the preset information interval number;

traversing a plurality of pieces of target historical financial service query request information corresponding to each piece of candidate historical financial service query request information to obtain a plurality of groups of two pieces of target historical financial service query request information, wherein the generation time interval between the two pieces of target historical financial service query request information is smaller than a preset time interval;

for each group of the two pieces of target historical financial service query request information, determining one piece of target historical financial service query request information in the two pieces of target historical financial service query request information;

for each piece of candidate historical financial service query request information, obtaining a query request information representative set corresponding to the candidate historical financial service query request information based on a plurality of pieces of determined target historical financial service query request information corresponding to the candidate historical financial service query request information;

acquiring sequence positions of historical financial service query request information corresponding to the target user or a user object having an incidence relation with the target user in the query request information sequence to obtain at least one target sequence position;

traversing each piece of historical financial service query request information in each query request information representative set aiming at each query request information representative set to obtain historical financial service query request information closest to the target sequence position, wherein the historical financial service query request information is used as primarily selected historical financial service query request information;

determining a sequence position distance between the initial selection historical financial service query request information and the target sequence position in the query request information sequence, and judging whether the sequence position distance is smaller than a preset position spacing distance;

if the sequence position distance is smaller than or equal to the preset position spacing distance, taking a query request information representative set corresponding to the primarily selected historical financial service query request information as a target query request information representative set;

if the sequence position distance is greater than the preset position spacing distance, taking the corresponding initial selection historical financial service query request information as a target query request information representative set;

and determining whether the financial service query request information belongs to legal query request information or not based on historical financial service query request information included in each target query request information representative set.

The application also provides a financial business management system based on big data and cloud computing, which is used for:

According to the financial service management method and system based on big data and cloud computing, before financial service information corresponding to financial service query request information is sent, whether the financial service query request information is legal or not is determined, query verification information is generated when the financial service query request information is illegal, and the query verification information is sent to verification equipment bound by a target user, so that the corresponding financial service information is sent to the query equipment when verification is successful. Based on this, when the financial service management system is determined to be illegal, the verification is carried out to send the financial service information again when the verification passes, so that the service safety and the query effectiveness can be considered at the same time, and the problem that the service safety and the query effectiveness are difficult to be considered effectively in the existing financial service management technology is solved.

In order to make the aforementioned objects, features and advantages of the present application more comprehensible, preferred embodiments accompanied with figures are described in detail below.

Drawings

Fig. 1 is a block diagram of a financial transaction management system based on big data and cloud computing according to an embodiment of the present disclosure.

Fig. 2 is a schematic flowchart illustrating steps included in a financial transaction management method based on big data and cloud computing according to an embodiment of the present application.

Detailed Description

In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all the embodiments. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations.

Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

As shown in fig. 1, an embodiment of the present application provides a financial transaction management system based on big data and cloud computing. The financial transaction management system may include, among other things, a memory and a processor.

In detail, the memory and the processor are electrically connected directly or indirectly to realize data transmission or interaction. For example, they may be electrically connected to each other via one or more communication buses or signal lines. The memory can have stored therein at least one software function (computer program) which can be present in the form of software or firmware. The processor may be configured to execute the executable computer program stored in the memory, so as to implement the financial transaction management method based on big data and cloud computing provided by the embodiments (described later) of the present application.

The big data and cloud computing based financial transaction management system may be configured to:

Alternatively, the Memory may be, but is not limited to, a Random Access Memory (RAM), a Read Only Memory (ROM), a Programmable Read-Only Memory (PROM), an Erasable Read-Only Memory (EPROM), an electrically Erasable Read-Only Memory (EEPROM), and the like.

The Processor may be a general-purpose Processor, including a Central Processing Unit (CPU), a Network Processor (NP), a System on Chip (SoC), and the like; but may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components.

Also, the structure shown in fig. 1 is only an illustration, and the financial transaction management system based on big data and cloud computing may further include more or less components than those shown in fig. 1, or have a different configuration from that shown in fig. 1, for example, may include a communication unit for information interaction with other devices.

In an alternative example, the financial transaction management system based on big data and cloud computing may be a server with data processing capability.

With reference to fig. 2, an embodiment of the present application further provides a financial service management method based on big data and cloud computing, which is applicable to the financial service management system based on big data and cloud computing. The financial business management method based on big data and cloud computing can be realized by the financial business management system based on big data and cloud computing.

The specific process shown in FIG. 2 will be described in detail below.

Step S110, determining whether the financial service inquiry request information sent by the inquiry device belongs to legal inquiry request information.

In this embodiment, after receiving the financial service query request information sent by the query device, the financial service management system based on big data and cloud computing may determine whether the financial service query request information belongs to legal query request information,

wherein the financial service inquiry request information is generated aiming at the target user. And if the financial service inquiry request information belongs to legal inquiry request information, the corresponding financial service information can be sent to the inquiry equipment to complete the inquiry. If the financial service inquiry request information belongs to illegal inquiry request information, step S120 may be performed.

Step S120, generating query and check information.

In this embodiment, when it is determined that the financial transaction query request information belongs to illegal query request information based on step S110, query verification information may be generated.

Wherein, the query and check information carries the identification information of the query device.

Step S130, sending the query verification information to the verification device bound by the target user.

In this embodiment, after generating the query verification information based on step S120, the query verification information may be sent to the verification device bound by the target user.

The verification equipment is used for verifying the financial service inquiry request information based on the identification information. And, if first verification feedback information sent by the verification device is received, step S140 may be executed, where the first verification feedback information is generated based on the verification device when the verification of the financial service inquiry request information is successful. If the first verification feedback information sent by the verification device is received, the corresponding financial service information may not be sent to the query device.

Step S140, sending the financial service information corresponding to the target user to the query device.

In this embodiment, after the query verification information is sent to the verification device based on step S130 and the first verification feedback information sent by the verification device is received, the financial service information corresponding to the target user may be sent to the query device.

The financial service information may include credit investigation report information, payment bill information, collection bill information, and the like of the target user. The query device and the verification device may be terminal devices of corresponding users, and when the verification device performs verification, the verification may be performed automatically based on a pre-trained verification model (such as a neural network model) or a verification program, or may be performed based on a corresponding user, such as the operation of the target user.

Based on the method, when the financial service query request information is determined to be illegal, the corresponding financial service information is sent again through verification when the verification is passed, so that the service safety and the query effectiveness of the financial service query can be considered, and the problem that the service safety and the query effectiveness are difficult to effectively consider in the conventional financial service management technology is solved.

In the first aspect, it should be noted that, for the step S110, a specific manner for determining whether the financial service inquiry request information belongs to legal inquiry request information is not limited.

For example, in an alternative example, whether the financial service inquiry request information belongs to legal inquiry request information may be determined based on the following steps:

firstly, acquiring financial service inquiry request information sent by inquiry equipment, wherein the financial service inquiry request information is generated aiming at a target user (for example, a financial loan institution inquires a credit investigation report of the target user, so that the financial service inquiry request information needs to be generated to request the financial service management system based on big data and cloud computing to return a corresponding credit investigation report);

secondly, based on the identification information (such as an IP address, an equipment fingerprint, and the like) of the query equipment, acquiring multiple pieces of historical financial service query request information sent by the query equipment by performing multiple query request operations on multiple different user objects (the multiple different user objects may include the target user, an associated user of the target user, and a non-associated user of the target user) historically;

then, based on the plurality of pieces of historical financial service inquiry request information, whether the financial service inquiry request information belongs to legal inquiry request information is determined.

Optionally, in the above example, a specific manner of determining whether the financial service inquiry request information belongs to legal inquiry request information based on the plurality of pieces of historical financial service inquiry request information is not limited, and may be selected according to actual application requirements.

For example, in a first alternative example, the specific manner for determining whether the financial service query request information belongs to legal query request information based on the plurality of pieces of historical financial service query request information may include the following steps:

a, according to the generation time information of each piece of historical financial service query request information, sequencing the plurality of pieces of historical financial service query request information in the sequence from the early to the late of the generation time to obtain a corresponding query request information sequence (that is, in the query request information sequence, the historical financial service query request information with the earlier generation time can be positioned in front of the historical financial service query request information with the later generation time);

b, according to the generated time information of each piece of historical financial service inquiry request information, performing clustering processing (such as clustering based on a proximity algorithm or other clustering algorithms in a time dimension) to obtain a plurality of inquiry request information clusters, and determining one piece of historical financial service inquiry request information as key historical financial service inquiry request information in each inquiry request information cluster (for example, randomly determining one piece of historical financial service inquiry request information as key historical financial service inquiry request information, or using one piece of historical financial service inquiry request information of which the generated time belongs to a median value as key historical financial service inquiry request information, or using one piece of historical financial service inquiry request information corresponding to the target user or a user object in an association relationship with the target user as key historical financial service inquiry request information, or, taking a piece of historical financial service query request information corresponding to the object with the largest correlation relationship among the historical financial service query request information and the key historical financial service query request information) as key historical financial service query request information to obtain a plurality of pieces of key historical financial service query request information;

c, in the query request information sequence, based on historical financial service query request information between two adjacent pieces of key historical financial service query request information in the plurality of pieces of key historical financial service query request information, confirming the plurality of pieces of historical financial service query request information by a preset interval information quantity (the preset interval information quantity can be generated based on configuration operation performed by a user according to an actual application scene);

d, generating the query request information screening sequence (or sequencing from morning to evening based on the generation time information) according to the confirmed plurality of pieces of historical financial service query request information and the key historical financial service query request information;

e, in the query request information screening sequence, obtaining historical financial service query request information corresponding to a sequence starting position to obtain first historical financial service query request information, and obtaining historical financial service query request information corresponding to a sequence ending position to obtain second historical financial service query request information, wherein the sequence starting position is the sum of a first position (the position of the first historical financial service query request information is the position where a piece of historical financial service query request information with the earliest generation time is located) and a preset position number (the specific value of the preset position number can be generated based on configuration operation performed by a user according to an actual application scene) in the query request information screening sequence, and the sum of the sequence ending position and the preset position number is the last position (the position where the last piece of historical financial service query request information is located) in the query request information screening sequence, the position of a piece of historical financial service inquiry request information with the latest generation time);

f, according to the generation time information corresponding to the first historical financial service inquiry request information and the second historical financial service inquiry request information and the generation time span information of the inquiry request information screening sequence (the time period between the generation time information of the historical financial service inquiry request information corresponding to the first position and the generation time information of the historical financial service inquiry request information corresponding to the last position), determining a first generation time average value (the average value of the generation time information of the first historical financial service inquiry request information and the generation time information of the historical financial service inquiry request information corresponding to the first position) and a second generation time average value (the average value of the generation time information of the second historical financial service inquiry request information and the generation time information of the historical financial service inquiry request information corresponding to the last position) on the inquiry request information screening sequence Value) respectively corresponding historical financial service query request information sets (the difference value between the generation time of each piece of historical financial service query request information in the historical financial service query request information set and the corresponding generation time average value is less than a preset threshold value, and the first historical financial service query request information and the second historical financial service query request information are not included, wherein the specific numerical value of the preset threshold value can be generated based on configuration operation performed by a user according to an actual application scene);

g, obtaining a piece of historical financial service query request information in the historical financial service query request information set corresponding to the first generation time average value on the query request information screening sequence (where the historical financial service query request information is historical financial service query request information corresponding to a user object in the historical financial service query request information set having an association relationship with the target user, or, when the historical financial service query request information corresponding to a user object not having an association relationship is obtained, a piece of historical financial service query request information may be determined according to other rules or randomly), and reaching a piece of historical financial service query request information in the historical financial service query request information set corresponding to the second generation time average value through the first historical financial service query request information and the second historical financial service query request information (which may refer to the first generation time average value) A determination mode of one piece of historical financial service query request information in the corresponding historical financial service query request information set) to obtain a query request information representative sequence (or, sorting the query request information in the order from morning to evening based on the generation time information);

h, calculating a first sequence position distance (namely the number of historical financial service query request information spaced between the sequence starting position and the position of the generation time average value) between the sequence starting position and the position of the generation time average value corresponding to the query request information representative sequence (namely the average value of the generation time of all historical financial service query request information included in the query request information representative sequence), and a second sequence position distance (namely the number of historical financial service query request information spaced between the sequence ending position and the position of the generation time average value) between the position of the generation time average value and the position of the sequence ending position;

i, calculating a third sequence position distance between the position of the first generation time average value and the position of the second generation time average value (namely the quantity of historical financial service query request information at intervals between the position of the first generation time average value and the position of the second generation time average value);

j, multiplying the third sequence position distance by a preset weight value (the preset weight value may be a coincidence coefficient generated based on configuration operation performed by a user according to an actual application scene, or a coefficient used for representing coincidence of the third sequence position distance and the second sequence position distance on a sequence and determined based on certain historical data) to obtain a first numerical value;

k, adding the first numerical value, the first sequence position distance and the second sequence position distance (namely adding the first numerical value, the first sequence position distance and the second sequence position distance) to obtain a second numerical value, and judging the size of the second numerical value and a preset threshold (the preset threshold can be generated based on configuration operation performed by a user according to an actual application scene);

For another example, in a second alternative example, a specific manner of determining whether the financial service query request information belongs to legal query request information based on the plurality of pieces of historical financial service query request information may include the following steps:

the first step, according to the generation time information of each piece of historical financial service query request information, sequencing the plurality of pieces of historical financial service query request information according to the sequence of the generation time from morning to evening to obtain a corresponding query request information sequence (as described above);

a second step of determining a plurality of candidate historical financial service query request information (e.g., determining a sampling value based on the time span information and the information quantity, and then performing sampling based on the sampling value to obtain candidate historical financial service query request information, wherein the sampling value may be larger when the time span information and the information quantity are larger), based on the time span information of the time information generated by the plurality of pieces of historical financial service query request information (as described above) and the information quantity of the plurality of pieces of historical financial service query request information, in the query request information sequence, and determining a relevant time range corresponding to each piece of candidate historical financial service query request information (e.g., centering on each piece of candidate historical financial service query request information) based on the quantity of the historical financial service query request information between two adjacent pieces of candidate historical financial service query request information, half of the number is an extended value, such that a corresponding information set can be formed, and then a corresponding relevant time range is generated based on the corresponding generation time information), wherein the relevant time range comprises the generation time of the corresponding candidate historical financial service query request information;

a third step of determining, for each of the candidate historical financial service inquiry request information, based on a relevant time range corresponding to the candidate historical financial service inquiry request information, other historical financial service inquiry request information corresponding to a user object having an association relationship with a user object of the candidate historical financial service inquiry request information within the relevant time range, or determining, when there is no other historical financial service inquiry request information corresponding to a user object having an association relationship, other historical financial service inquiry request information having a maximum sequence interval position with the candidate historical financial service inquiry request information within the relevant time range (generating other historical financial service inquiry request information having a maximum time difference), and based on each set of the candidate historical financial service inquiry request information and the other historical financial service inquiry request information, historical financial service inquiry request information between the candidate historical financial service inquiry request information and the historical financial service inquiry request information to form an inquiry request information candidate set of the candidate historical financial service inquiry request information;

step four, determining a plurality of pieces of target historical financial service query request information from each query request information candidate set according to a preset information interval number (the information interval number can be generated based on configuration operation of a user according to an actual application scene) (namely sampling is performed according to the information interval number, so that the plurality of pieces of target historical financial service query request information are determined);

step five, for a plurality of pieces of target historical financial service query request information corresponding to each piece of candidate historical financial service query request information, traversing the plurality of pieces of target historical financial service query request information to obtain a plurality of groups of two pieces of target historical financial service query request information, wherein the generation time interval between the groups of two pieces of target historical financial service query request information is smaller than a preset time interval (the preset time interval can be generated based on configuration operation performed by a user according to an actual application scene) (thus, a plurality of groups of target historical financial service query request information can be formed, and each group of target historical financial service query request information comprises two pieces of target historical financial service query request information);

sixthly, aiming at each group of two pieces of target historical financial service query request information, determining one piece of target historical financial service query request information (one piece of target historical financial service query request information which is associated with the target user can be selected, or one piece of target historical financial service query request information which is generated at a later time can be selected, or one piece of target historical financial service query request information can be determined at will, and the three modes can be carried out in sequence);

seventhly, aiming at each piece of candidate historical financial service query request information, obtaining a query request information representative set corresponding to the candidate historical financial service query request information based on a plurality of pieces of determined target historical financial service query request information corresponding to the candidate historical financial service query request information (namely, the target historical financial service query request information determined in the sixth step forms a corresponding query request information representative set according to the corresponding candidate historical financial service query request information);

eighthly, acquiring the sequence position of the historical financial service query request information corresponding to the target user or the user object having the incidence relation with the target user in the query request information sequence to obtain at least one target sequence position;

a ninth step of traversing each piece of historical financial service query request information in each query request information representative set to obtain historical financial service query request information closest to the target sequence position (when there are a plurality of pieces of historical financial service query request information closest to the target sequence position, one piece of historical financial service query request information can be determined arbitrarily) as initially selected historical financial service query request information;

tenth, determining a sequence position distance between the primarily selected historical financial service query request information and the target sequence position in the query request information sequence, and determining whether the sequence position distance is smaller than a preset position interval distance (the preset position interval distance may be generated based on configuration operation performed by a user according to an actual application scene);

step ten, if the sequence position distance is less than or equal to the preset position spacing distance, taking a query request information representative set corresponding to the primarily selected historical financial service query request information as a target query request information representative set;

a twelfth step of, if the sequence position distance is greater than the preset position interval distance, using the corresponding initial historical financial transaction query request information as a target query request information representative set (that is, in this case, the target query request information representative set only includes the initial historical financial transaction query request information);

and step thirteen, determining whether the financial service inquiry request information belongs to legal inquiry request information or not based on historical financial service inquiry request information included in each target inquiry request information representative set.

For another example, in particular, in a third alternative example, a specific manner of determining whether the financial service inquiry request information belongs to legal inquiry request information based on the plurality of pieces of historical financial service inquiry request information may include the following steps:

the method comprises the steps that firstly, based on whether user objects corresponding to historical financial service inquiry request information are the same or not or whether the user objects corresponding to the historical financial service inquiry request information are related, a plurality of pieces of historical financial service inquiry request information which are the same or related to the user objects are divided into the same request information set to obtain a plurality of request information sets (namely, the user objects corresponding to the historical financial service inquiry request information in different request information sets are different or do not have an association relationship, wherein the association relationship can mean that financial service transactions such as borrowing and the like exist among different user objects);

secondly, determining a request information set with the largest quantity of historical financial service inquiry request information in the plurality of request information sets as a target request information set;

thirdly, determining the duration of time (i.e. the difference between the time of starting to perform the query and the time of finishing the query, such as the generation time of the historical financial service query request information and the time of sending the corresponding financial service information to the target device or the time of determining that the verification is unsuccessful) corresponding to each piece of the historical financial service query request information in the target request information set, and the request start time (i.e. the time of starting to perform the query) and the request end time (i.e. the time of finishing the query) of each duration of time;

fourthly, determining a plurality of pieces of historical financial service query request information in the target request information set, a time duration corresponding to each piece of historical financial service query request information, and a request start time and a request end time of the time duration as a data set to be processed, and determining a current position (the current position may be one or more) of the historical financial service query request information corresponding to a user object which is the same as or associated with the target user in the data set to be processed;

fifthly, obtaining a target screening time period according to the time duration of the historical financial service query request information of the (each) current position (the target screening time period can be the time for starting to perform query and the time for finishing query based on the historical financial service query request information);

sixthly, determining historical financial service query request information intersected with the target screening time period based on the corresponding request starting time and request ending time in each piece of historical financial service query request information to obtain to-be-processed historical financial service query request information;

seventhly, determining at least one piece of historical financial service query request information to be processed, and taking the position of the at least one piece of historical financial service query request information to be processed in the target request information set as a target position;

eighthly, obtaining a new target screening time period according to the time duration of the historical financial service inquiry request information of each target position;

ninthly, determining historical financial service query request information intersected with the new target screening time period based on the corresponding request starting time and request ending time in each piece of historical financial service query request information to obtain to-be-processed historical financial service query request information;

and step ten, determining whether the financial service inquiry request information belongs to legal inquiry request information or not based on each piece of the historical financial service inquiry request information to be processed.

It can be understood that, in the above three examples, the specific manner for determining whether the financial service inquiry request information belongs to the legal inquiry request information based on the obtained historical financial service inquiry request information is not limited, and may be determined according to the actual application requirements.

For example, in an alternative example, a corresponding query frequency may be obtained based on the last obtained historical financial service query request information and corresponding generation time information, and then, based on the query frequency and a preset frequency threshold (which may be generated based on a configuration operation of a user), it is determined whether the financial service query request information belongs to legal query request information.

For another example, in another alternative example, whether the financial service query request information belongs to legal query request information may be determined based on the number of the last obtained historical financial service query request information and a preset number threshold (which may be generated based on a configuration operation of a user).

It is understood that, in the first example, if it is determined based on step k that the second value is smaller than the preset threshold, the specific processing manner is not limited.

In a first example, the step of determining whether the financial service inquiry request information belongs to legal inquiry request information based on the plurality of pieces of historical financial service inquiry request information includes:

In a second example, the step of determining whether the financial service inquiry request information belongs to legal inquiry request information based on the plurality of pieces of historical financial service inquiry request information includes:

if the second numerical value is smaller than the preset threshold value, clustering historical financial service query request information included in each query request information cluster to obtain at least one query request information sub-cluster; determining a piece of historical financial service query request information in each query request information sub-cluster as key historical financial service query request information to obtain a plurality of pieces of new key historical financial service query request information; based on the plurality of pieces of new key historical financial transaction query request information, step c in the first alternative example described above is performed again.

In a third example, the step of determining whether the financial service inquiry request information belongs to legal inquiry request information based on the plurality of pieces of historical financial service inquiry request information includes:

if the second value is smaller than the preset threshold, performing update processing on the preset interval information quantity (for example, reducing the preset interval information quantity, wherein the preset interval information quantity can be gradually reduced according to a certain gradient when multiple updates are required) to obtain a new preset interval information quantity; based on the new preset interval information amount, step c in the first alternative example described above is performed again.

In a fourth example, the step of determining whether the financial service inquiry request information belongs to legal inquiry request information based on the plurality of pieces of historical financial service inquiry request information includes:

if the second value is smaller than the preset threshold, performing update processing on the preset position number (for example, reducing the preset position number, wherein the preset position number may be gradually reduced according to a certain gradient when multiple updates are required) to obtain a new preset position number; based on the new number of preset positions, step e of the first alternative example described above is performed again.

In a fifth example, the step of determining whether the financial service inquiry request information belongs to legal inquiry request information based on the plurality of pieces of historical financial service inquiry request information includes:

if the second value is smaller than the preset threshold, performing update processing on the preset weight value (if the preset weight value is increased, the preset weight value may be gradually increased according to a certain gradient when multiple updates are required) to obtain a new preset weight value; based on the new preset weight value, step j in the first alternative example is executed again.

In summary, the financial service management method and system based on big data and cloud computing provided by the application determine whether the financial service query request information is legal before sending the financial service information corresponding to the financial service query request information, and when the financial service query request information is illegal, generate query verification information and send the query verification information to the verification device bound by the target user, so as to send the corresponding financial service information to the query device when the verification is successful. Based on this, when the financial service management system is determined to be illegal, the verification is carried out to send the financial service information again when the verification passes, so that both the service safety and the query effectiveness can be considered, the problem that both the service safety and the query effectiveness are difficult to be considered effectively in the existing financial service management technology is solved, and the system has high practical value.

In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method can be implemented in other ways. The apparatus and method embodiments described above are illustrative only, as the flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

In addition, functional modules in the embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.

The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, an electronic device, or a network device) to perform all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes. It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.

The above description is only a preferred embodiment of the present application and is not intended to limit the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A business query checking method based on big data and cloud computing is characterized by comprising the following steps:

if the financial service inquiry request information belongs to legal inquiry request information, sending the corresponding financial service information to the inquiry equipment;

2. The big data and cloud computing based business query verification method according to claim 1, wherein the step of determining whether the financial business query request information sent by the query device belongs to legal query request information comprises:

3. The big data and cloud computing based business query verification method according to claim 2, wherein the step of determining whether the financial business query request information belongs to legal query request information based on the plurality of pieces of historical financial business query request information comprises:

4. The big data and cloud computing based business query verification method according to claim 3, wherein the step of determining whether the financial business query request information belongs to legal query request information based on the plurality of pieces of historical financial business query request information further comprises:

5. The big data and cloud computing based business query verification method according to claim 3, wherein the step of determining whether the financial business query request information belongs to legal query request information based on the plurality of pieces of historical financial business query request information further comprises:

6. The big data and cloud computing based business query verification method according to claim 3, wherein the step of determining whether the financial business query request information belongs to legal query request information based on the plurality of pieces of historical financial business query request information further comprises:

7. The big data and cloud computing based business query verification method according to claim 3, wherein the step of determining whether the financial business query request information belongs to legal query request information based on the plurality of pieces of historical financial business query request information further comprises:

and e, executing the step e again based on the new preset position number.

8. The big data and cloud computing based business query verification method according to claim 3, wherein the step of determining whether the financial business query request information belongs to legal query request information based on the plurality of pieces of historical financial business query request information further comprises:

and j is executed again based on the new preset weight value.