CN108694657A - Client's identification device, method and computer readable storage medium - Google Patents
Client's identification device, method and computer readable storage medium Download PDFInfo
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- CN108694657A CN108694657A CN201810768273.9A CN201810768273A CN108694657A CN 108694657 A CN108694657 A CN 108694657A CN 201810768273 A CN201810768273 A CN 201810768273A CN 108694657 A CN108694657 A CN 108694657A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/06—Buying, selling or leasing transactions
- G06Q30/0601—Electronic shopping [e-shopping]
- G06Q30/0609—Buyer or seller confidence or verification
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
- G06Q40/02—Banking, e.g. interest calculation or account maintenance
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- 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 invention discloses a kind of client's identification device, including memory and processor, the client's recognizer that can be run on a processor is stored on memory, which realizes following steps when being executed by processor:Determine the target service system for needing to scan;The customer data table and/or trading object tables of data and blacklist list of acquisition target service system;According to the update status of data within a preset time interval, customer data table and/or trading object tables of data are matched with blacklist list, find out unusual customers;The transaction record that unusual customers are inquired from corresponding database will meet the transaction record of preset condition as abnormal transaction record;It generates unusual customers case and abnormal transaction case is sent to reset mechanism node.The present invention also proposes a kind of client's recognition methods and a kind of computer readable storage medium.The present invention improves mechanism to the recognition efficiency of suspicious client, then enhances risk control capability.
Description
Technical field
The present invention relates to field of computer technology more particularly to a kind of client's identification device, method and computer-readable deposit
Storage media.
Background technology
Some enterprises of financial industry or mechanism, such as bank need the safety to transaction to carry out management and control, judicial apparatus
The authoritative institutions such as pass, People's Bank of China can periodically issue some black list informations, and financial institution needs the transaction to mechanism
Business is monitored, and has detected whether that suspicious client may be in these blacklist lists.But do not have in existing banking system
There is the system of concentration suspicious client and transaction to be identified, mainly each operation system is adopted for the business demand of oneself
The suspicious client of blacklist management and control or even some operation systems is carried out with respective method and the identification method of transaction also rests on
The artificial discriminating level of counter service person, each operation system be required for safeguarding respective blacklist system, between system
Lack unified unusual customers criterion of identification, blacklist managerial confusion causes the recognition efficiency to suspicious client low, Jin Erzao
It is also relatively low at risk control capability.
Invention content
A kind of client's identification device of present invention offer, method and computer readable storage medium, main purpose are to carry
Height enhances risk control capability to the recognition efficiency of suspicious client.
To achieve the above object, the present invention provides a kind of client's identification device, which includes memory and processor, institute
The client's recognizer that is stored with and can run on the processor in memory is stated, client's recognizer is by the processing
Device realizes following steps when executing:
When client identifies that the time interval of operation reaches prefixed time interval, the target service system for needing to scan is determined
System;
Obtain the current customer data table of the target service system and/or trading object tables of data, and determine with it is described
The corresponding blacklist list of target service system;
According to the update status of the customer data table and/or trading object tables of data in the prefixed time interval,
The customer data table and/or trading object tables of data are matched with the blacklist list, find out unusual customers;
The transaction record that the unusual customers are inquired from the database of corresponding target service system, will meet default item
The transaction record of part is as abnormal transaction record;
Unusual customers case is generated according to the match condition of unusual customers, abnormal hand over is generated according to the abnormal transaction record
Easy case, and the unusual customers case and the abnormal transaction case are sent to reset mechanism node.
Optionally, it is described according to the customer data table and/or trading object tables of data in the prefixed time interval
Update status, the customer data table and/or trading object tables of data are matched with the blacklist list, found out
The step of unusual customers includes:
It detects the customer data table and/or whether trading object tables of data occurs more in the prefixed time interval
Newly;
If so, obtain increment customer data and/or increment trading object data, according to the matching rule by the increasing
Amount customer data and/or increment trading object data are matched with the blacklist list of full dose, find out unusual customers;
If it is not, then detecting whether the blacklist list updates in the prefixed time interval;
If so, increment blacklist list is obtained, according to the matching rule by the increment blacklist list and full dose
The customer data table and/or trading object tables of data matched, find out unusual customers.
It optionally, will be in the customer data table of full dose and/or trading object tables of data according to preset multiple items of information
User information is matched one by one with the personal information in increment blacklist list;
If the content of multiple presupposed information items is inconsistent, judge the client for normal clients;
If there is the content of presupposed information item consistent, judge the client for unusual customers.
Optionally, described the step of generating unusual customers case according to the match condition of unusual customers, includes:
The quantity of the consistent presupposed information item of content is obtained, and warning level is determined according to the quantity of acquisition;
Determine the matching field of the consistent presupposed information item of content;
Unusual customers case is generated according to the information of the unusual customers, the warning level and the matching field.
Optionally, the transaction record that the unusual customers are inquired from the database of corresponding target service system,
Include using the transaction record for meeting preset condition as the step of abnormal transaction record of the client:
The transaction record of the unusual customers is inquired from the database of corresponding target service system;
If the target service system is the first pre-set business system, by the newest transaction note of the unusual customers
Record is as abnormal transaction record;
If the target service system is the second pre-set business system, whether the unusual customers are detected in preset time
New transaction record is generated in interval;
If so, using the transaction record detected as abnormal transaction record;
If it is not, then transaction record nearest apart from current point in time in the current business term of validity of the unusual customers is made
For abnormal transaction record.
In addition, to achieve the above object, the present invention also provides a kind of client's recognition methods, this method includes:
When client identifies that the time interval of operation reaches prefixed time interval, the target service system for needing to scan is determined
System;
Obtain the current customer data table of the target service system and/or trading object tables of data, and determine with it is described
The corresponding blacklist list of target service system;
According to the update status of the customer data table and/or trading object tables of data in the prefixed time interval,
The customer data table and/or trading object tables of data are matched with the blacklist list, find out unusual customers;
The transaction record that the unusual customers are inquired from the database of corresponding target service system, will meet default item
The transaction record of part is as abnormal transaction record;
Unusual customers case is generated according to the match condition of unusual customers, abnormal hand over is generated according to the abnormal transaction record
Easy case, and the unusual customers case and the abnormal transaction case are sent to reset mechanism node.
In addition, to achieve the above object, it is described computer-readable the present invention also provides a kind of computer readable storage medium
Client's recognizer is stored on storage medium, client's recognizer can be executed by one or more processor, with reality
Now the step of client's recognition methods as described above.
Client's identification device, method and computer readable storage medium proposed by the present invention, when client identifies operation
Between interval when reaching prefixed time interval, determine and need the target service system that scans, and then obtain the target service system
Customer data table and/or trading object tables of data, and determine blacklist list to be matched.It will be objective according to preset matching rule
User data table and/or trading object tables of data are matched with blacklist list, find out unusual customers, from corresponding target industry
The transaction record that unusual customers are inquired in the database of business system will meet the transaction record of preset condition as abnormal transaction note
Record.To generate unusual customers case according to unusual customers, abnormal transaction case is generated according to abnormal transaction record, and will be abnormal
Client's case and abnormal transaction case are sent to reset mechanism node, and the present invention is by matching rule to the different of multiple operation systems
Regular guest family is identified, and generates unified unusual customers case and abnormal transaction case, improves the recognition efficiency of unusual customers,
Enhance risk control capability.
Description of the drawings
Fig. 1 is the schematic diagram of one embodiment of client's identification device of the present invention;
Fig. 2 is the program module schematic diagram of client's recognizer in one embodiment of client's identification device of the present invention;
Fig. 3 is the flow chart of one embodiment of client's recognition methods of the present invention.
The embodiments will be further described with reference to the accompanying drawings for the realization, the function and the advantages of the object of the present invention.
Specific implementation mode
It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, it is not intended to limit the present invention.
The present invention provides a kind of client's identification device.It is one embodiment of client's identification device of the present invention shown in referring to Fig.1
Schematic diagram.
In the present embodiment, client's identification device 1 can be PC (Personal Computer, PC), can also
It is the terminal devices such as smart mobile phone, tablet computer, pocket computer.
Client's identification device 1 includes at least memory 11, processor 12, communication bus 13 and network interface 14.
Wherein, memory 11 include at least a type of readable storage medium storing program for executing, the readable storage medium storing program for executing include flash memory,
Hard disk, multimedia card, card-type memory (for example, SD or DX memories etc.), magnetic storage, disk, CD etc..Memory 11
Can be the internal storage unit of client's identification device 1, such as the hard disk of client's identification device 1 in some embodiments.It deposits
Reservoir 11 can also be on the External memory equipment of client's identification device 1, such as client's identification device 1 in further embodiments
The plug-in type hard disk of outfit, intelligent memory card (Smart Media Card, SMC), secure digital (Secure Digital, SD)
Card, flash card (Flash Card) etc..Further, memory 11 can also both include the storage inside of client's identification device 1
Unit also includes External memory equipment.Memory 11 can be not only used for the application software that storage is installed on client's identification device 1
And Various types of data, such as client's recognizer 01 code etc., can be also used for temporarily storing and exported or will be defeated
The data gone out.
Processor 12 can be in some embodiments a central processing unit (Central Processing Unit,
CPU), controller, microcontroller, microprocessor or other data processing chips, the program for being stored in run memory 11
Code or processing data, such as execute client's recognizer 01 etc..
Communication bus 13 is for realizing the connection communication between these components.
Network interface 14 may include optionally standard wireline interface and wireless interface (such as WI-FI interface), be commonly used in
Communication connection is established between the device 1 and other electronic equipments.
Fig. 1 illustrates only client's identification device 1 with component 11-14 and client's recognizer 01, it should be understood that
Be, it is not required that implement all components shown, the implementation that can be substituted is more or less component.
In 1 embodiment of device shown in Fig. 1, client's recognizer 01 is stored in memory 11;Processor 12 executes
Following steps are realized when the client's recognizer 01 stored in memory 11:
When client identifies that the time interval of operation reaches prefixed time interval, the target service system for needing to scan is determined
System.
Obtain target service system current customer data table and/or trading object tables of data, and determining and target service
The corresponding blacklist list of system.
In embodiments of the present invention, user can preset the time interval for carrying out unusual customers identification operation, such as
24 hours, then client's identification device the time interval of unusual customers identification operation is monitored in real time, when reaching preset time
When interval, start unusual customers identification operation.In addition, client's identification device of the present embodiment can be simultaneously to multiple operation systems
Carry out management and control.Wherein, operation system refers to the operation system of an each independent operation of intra-company, such as insurance business system
System, stock exchange transaction system, banking system etc..User, which can pre-set, needs the operation system scanned as target
Operation system obtains target service system currently newest customer data table and/trading object tables of data.In some embodiments
In, only customer data table can be scanned, it in other embodiments can be to customer data table and these tables of data
In client trading object constitute trading object tables of data be scanned.By taking health insurance operation system as an example, Ke Hushi
Refer to list and single group insurer, the warrantee and beneficiary that dies, trading object refers to then being merchandised involved in single group to public third
Side.Wherein, include mainly the information such as name, type of credential, the passport NO. of client in customer data table, and trading object data
Include mainly the information such as name, type of credential and the passport NO. of trading object in table.
Blacklist list in this present embodiment is closed, can pre-set and multiple come from what different agency nodes issued
Blacklist list.Suspicious client's list that such as judicial authority, authoritative institution of People's Bank of China issue.For a business system
For system, can be matched with one or more in preset blacklist list, user can pre-set operation system with
Corresponding relationship between the blacklist list in each source.
According to the update status of customer data table and/or trading object tables of data within a preset time interval, by client's number
It is matched with blacklist list according to table and/or trading object tables of data, finds out unusual customers.
For operation system, all can may there is new client to be traded daily, for example, withdrawal, purchase insurance,
Purchase investment product etc. or some frequent customers also have some new trading objects, therefore, are carrying out client's identification
When, need the update for considering customer data table and/or trading object tables of data.Moreover, the blacklist list that authoritative institution issues
There is also newer possibility occurs in prefixed time interval, such as deletes, increases some personal informations to blacklist list
On, or have modified the personal information etc. in blacklist list.Therefore unusual customers are accurately identified in order to realize, it needs every
Certain interval of time re-executes client and identifies operation according to the update status of above-mentioned data.
Specifically, the update status according to customer data table and/or trading object tables of data within a preset time interval, will
The step of customer data table and/or trading object tables of data are matched with blacklist list, find out unusual customers can wrap
Include following refinement step:Whether detection customer data table and/or trading object tables of data update within a preset time interval;
If so, obtain increment customer data and/or increment trading object data, according to matching rule by increment customer data and/or
Increment trading object data are matched with the blacklist list of full dose, find out unusual customers;If it is not, then detecting blacklist row
Whether table updates within a preset time interval;If so, increment blacklist list is obtained, it is according to matching rule that increment is black
List list is matched with the customer data table of full dose and/or trading object tables of data, finds out unusual customers.
In above-mentioned steps, had occurred in customer data table and/or trading object tables of data it is newer, no matter black name
Whether single-row table updates, and can arrange the blacklist of the trading object data and full dose of the customer data of increment and/or increment
Table is matched.Do not updated in customer data table and/or trading object tables of data, and blacklist list have occurred it is newer
In the case of, the customer data table of full dose and/or trading object tables of data are matched with increment blacklist data, found out different
Regular guest family.If it is understood that within a preset time interval, if customer data table and/or trading object data do not occur more
Newly, blacklist list does not also update, then this recognition result may be identical as last time, therefore can be scanned,
Obtain the recognition result of last time.It or in other examples, can be by the customer data table and/or trading object number of full dose
It is matched again with full dose blacklist data according to table, to find out unusual customers.Specifically, when being matched, if client
Information is consistent with the personal information in blacklist list, then judges that for unusual customers, the information of the client is recorded as by the client
Unusual customers.
Further, according to matching rule by the customer data table and/or transaction of the increment blacklist list and full dose
The step of object data table is matched, finds out unusual customers include:According to preset multiple items of information, by the client of full dose
User information in tables of data and/or trading object tables of data and the personal information in increment blacklist list carry out one by one
Match;If the content of multiple presupposed information items is inconsistent, judge the client for normal clients;If there is the content of presupposed information item
Unanimously, then judge the client for unusual customers.Specifically, presupposed information item includes mainly type of credential, passport NO. and client
Three items of information of name.Obtain type of credential, passport NO. and the customer name in customer information, the above- mentioned information that will be got
Item is matched according to preset order with the data in blacklist one by one, and sends out correspondence according to the match condition of above three item of information
The warning information of rank.Wherein, user can pre-set the corresponding warning level of different match conditions.If for example, certificate
Number is identical and the accurate successful match of name, is level-one early warning;If passport NO. is identical, name fuzzy matching success is two level
If early warning is three-level early warning without passport NO. and/or type of credential information and the accurate successful match of name;If without passport NO.
And/or type of credential information and name fuzzy matching success, be level Four early warning.
After judgement client is unusual customers, the quantity of the consistent presupposed information item of content is obtained, and according to acquisition
Quantity determines warning level;Determine the matching field of the consistent presupposed information item of content;According to the information of unusual customers, early warning grade
Not and matching field generates unusual customers case.
The transaction record that unusual customers are inquired from the database of corresponding target service system, will meet preset condition
Transaction record is as abnormal transaction record.
Unusual customers case is generated according to unusual customers, abnormal transaction case is generated according to abnormal transaction record, and will be different
Regular guest family case and abnormal transaction case are sent to reset mechanism node.
If target service system has multiple, after finding unusual customers, the corresponding target of these customer informations is determined
Operation system.The transaction record of the customer information is inquired from the database of target service system.Filter out qualified friendship
Easily record is as abnormal transaction record.Specifically, the friendship of unusual customers is inquired from the database of corresponding target service system
Easily record;If target service system is the first pre-set business system, using the newest transaction record of unusual customers as different
Normal transaction record;If target service system is the second pre-set business system, whether unusual customers are detected in prefixed time interval
It is interior to generate new transaction record;If so, using the transaction record detected as abnormal transaction record;If it is not, then will be abnormal objective
The transaction record nearest apart from current point in time is as abnormal transaction record in the current business term of validity at family.
As an implementation, above-mentioned first pre-set business system can be the operation systems such as security, letter guarantor, can obtain
Take the newest transaction record of client as abnormal transaction record.By taking the second pre-set business system is insurance business system as an example,
If the unusual customers do not have transaction record within a preset time interval, obtain in the current Effective Period of Insurance of the customer information
Transaction record is as abnormal transaction record.Further, if no deal records in Effective Period of Insurance, historical transaction record is obtained
The middle transaction record nearest apart from current point in time is as abnormal transaction record.
Include in the unusual customers case of generation in customer information with matched field and warning level in blacklist
Etc. information, these message reflections go out the intensity of anomaly of client.And in abnormal case of merchandising include then the abnormal transaction got
Record, reflects the abnormal trading situation of unusual customers.Above-mentioned case is sent at preset agency node, it is possible to understand that
It is that the blacklist list of separate sources corresponds to different agency nodes, it therefore, can be according to being matched to when generating case
The corresponding blacklist of unusual customers generate multiple case tables, and be sent to corresponding agency node.
Client's identification device that above example proposes identifies that the time interval of operation reaches prefixed time interval in client
When, determine the target service system for needing to scan, and then obtain the customer data table and/or trading object of the target service system
Tables of data, and determine blacklist list to be matched.According to preset matching rule by customer data table and/or trading object number
It is matched with blacklist list according to table, finds out unusual customers, inquired from the database of corresponding target service system different
The transaction record at regular guest family will meet the transaction record of preset condition as abnormal transaction record.To be given birth to according to unusual customers
At unusual customers case, abnormal transaction case is generated according to abnormal transaction record, and by unusual customers case and abnormal transaction case
Example is sent to reset mechanism node, and the present invention is identified the unusual customers of multiple operation systems by matching rule, generates
Unified unusual customers case and abnormal transaction case, improve the recognition efficiency of unusual customers, enhance risk control capability.
Optionally, in other examples, client's recognizer can also be divided into one or more module, and one
A or multiple modules are stored in memory 11, and are held by one or more processors (the present embodiment is by processor 12)
For row to complete the present invention, the so-called module of the present invention is the series of computation machine program instruction section for referring to complete specific function,
For describing implementation procedure of client's recognizer in client's identification device.
It is the program mould of client's recognizer in one embodiment of client's identification device of the present invention shown in Fig. 2
Block schematic diagram, in the embodiment, client's recognizer can be divided into the first determining module 10, the second determining module 20, visitor
Family matching module 30, Transaction Inquiries module 40 and case generation module 50, illustratively:
First determining module 10 is used for:When client identifies that the time interval of operation reaches prefixed time interval, determining needs
The target service system to be scanned;
Second determining module 20 is used for:Obtain the current customer data table of the target service system and/or trading object
Tables of data, and determine blacklist list corresponding with the target service system;
Client's matching module 30 is used for:According to the customer data table and/or trading object tables of data when described default
Between update status in interval, the customer data table and/or trading object tables of data and the blacklist list are carried out
Match, finds out unusual customers;
Transaction Inquiries module 40 is used for:The friendship of the unusual customers is inquired from the database of corresponding target service system
Easily record will meet the transaction record of preset condition as abnormal transaction record;
Case generation module 50 is used for:Unusual customers case is generated according to the match condition of unusual customers, according to described different
Normal transaction record generates abnormal transaction case, and the unusual customers case and the abnormal transaction case are sent to default machine
Structure node.
Above-mentioned first determining module 10, the second determining module 20, client's matching module 30, Transaction Inquiries module 40 and case
The program modules such as generation module 50 are performed realized functions or operations step and are substantially the same with above-described embodiment, herein not
It repeats again.
In addition, the present invention also provides a kind of client's recognition methods.It is client's recognition methods one of the present invention with reference to shown in Fig. 3
The flow chart of embodiment.This method can be executed by a device, which can be by software and or hardware realization.
In the present embodiment, client's recognition methods includes:
Step S10 determines the target for needing to scan when client identifies that the time interval of operation reaches prefixed time interval
Operation system.
Step S20 obtains the current customer data table and/or trading object tables of data of target service system, and determine with
The corresponding blacklist list of target service system.
In embodiments of the present invention, user can preset the time interval for carrying out unusual customers identification operation, such as
24 hours.Then when the time interval of objective unusual customers identification operation reaches prefixed time interval, start unusual customers identification behaviour
Make.In addition, the present embodiment can carry out management and control to multiple operation systems simultaneously.Wherein, operation system refers to an intra-company
Operation system of each independent operation, such as insurance business system, stock exchange transaction system, banking system etc..User can
To pre-set the operation system for needing to scan as target service system, target service system currently newest client is obtained
Tables of data and/trading object tables of data.In some embodiments, only customer data table can be scanned, in other
The trading object tables of data that can be constituted to the trading object of the client in customer data table and these tables of data in embodiment is equal
It is scanned.By taking health insurance operation system as an example, client refers to list and single group insurer, the warrantee and beneficiary that dies, and is handed over
Easy object refers to then being merchandised involved in single group to public third party.Wherein, include mainly name, the card of client in customer data table
The information such as part type, passport NO., and mainly include name, type of credential and the certificate of trading object in trading object tables of data
The information such as number.
Blacklist list in this present embodiment is closed, can pre-set and multiple come from what different agency nodes issued
Blacklist list.Suspicious client's list that such as judicial authority, authoritative institution of People's Bank of China issue.For a business system
For system, can be matched with one or more in preset blacklist list, user can pre-set operation system with
Corresponding relationship between the blacklist list in each source.
Step S30, according to the update status of customer data table and/or trading object tables of data within a preset time interval,
Customer data table and/or trading object tables of data are matched with blacklist list, find out unusual customers.
For operation system, all can may there is new client to be traded daily, for example, withdrawal, purchase insurance,
Purchase investment product etc. or some frequent customers also have some new trading objects, therefore, are carrying out client's identification
When, need the update for considering customer data table and/or trading object tables of data.Moreover, the blacklist list that authoritative institution issues
There is also newer possibility occurs in prefixed time interval, such as deletes, increases some personal informations to blacklist list
On, or have modified the personal information etc. in blacklist list.Therefore unusual customers are accurately identified in order to realize, it needs every
Certain interval of time re-executes client and identifies operation according to the update status of above-mentioned data.
Specifically, the update status according to customer data table and/or trading object tables of data within a preset time interval, will
The step of customer data table and/or trading object tables of data are matched with blacklist list, find out unusual customers can wrap
Include following refinement step:Whether detection customer data table and/or trading object tables of data update within a preset time interval;
If so, obtain increment customer data and/or increment trading object data, according to matching rule by increment customer data and/or
Increment trading object data are matched with the blacklist list of full dose, find out unusual customers;If it is not, then detecting blacklist row
Whether table updates within a preset time interval;If so, increment blacklist list is obtained, it is according to matching rule that increment is black
List list is matched with the customer data table of full dose and/or trading object tables of data, finds out unusual customers.
In above-mentioned steps, had occurred in customer data table and/or trading object tables of data it is newer, no matter black name
Whether single-row table updates, and can arrange the blacklist of the trading object data and full dose of the customer data of increment and/or increment
Table is matched.Do not updated in customer data table and/or trading object tables of data, and blacklist list have occurred it is newer
In the case of, the customer data table of full dose and/or trading object tables of data are matched with increment blacklist data, found out different
Regular guest family.If it is understood that within a preset time interval, if customer data table and/or trading object data do not occur more
Newly, blacklist list does not also update, then this recognition result may be identical as last time, therefore can be scanned,
Obtain the recognition result of last time.It or in other examples, can be by the customer data table and/or trading object number of full dose
It is matched again with full dose blacklist data according to table, to find out unusual customers.Specifically, when being matched, if client
Information is consistent with the personal information in blacklist list, then judges that for unusual customers, the information of the client is recorded as by the client
Unusual customers.
Further, according to matching rule by the customer data table and/or transaction of the increment blacklist list and full dose
The step of object data table is matched, finds out unusual customers include:According to preset multiple items of information, by the client of full dose
User information in tables of data and/or trading object tables of data and the personal information in increment blacklist list carry out one by one
Match;If the content of multiple presupposed information items is inconsistent, judge the client for normal clients;If there is the content of presupposed information item
Unanimously, then judge the client for unusual customers.Specifically, presupposed information item includes mainly type of credential, passport NO. and client
Three items of information of name.Obtain type of credential, passport NO. and the customer name in customer information, the above- mentioned information that will be got
Item is matched according to preset order with the data in blacklist one by one, and sends out correspondence according to the match condition of above three item of information
The warning information of rank.Wherein, user can pre-set the corresponding warning level of different match conditions.If for example, certificate
Number is identical and the accurate successful match of name, is level-one early warning;If passport NO. is identical, name fuzzy matching success is two level
If early warning is three-level early warning without passport NO. and/or type of credential information and the accurate successful match of name;If without passport NO.
And/or type of credential information and name fuzzy matching success, be level Four early warning.
After judgement client is unusual customers, the quantity of the consistent presupposed information item of content is obtained, and according to acquisition
Quantity determines warning level;Determine the matching field of the consistent presupposed information item of content;According to the information of unusual customers, early warning grade
Not and matching field generates unusual customers case.
Step S40 inquires the transaction record of unusual customers from the database of corresponding target service system, will meet pre-
If the transaction record of condition is as abnormal transaction record.
Step S50 generates unusual customers case according to unusual customers, and abnormal transaction case is generated according to abnormal transaction record
Example, and unusual customers case and abnormal transaction case are sent to reset mechanism node.
If target service system has multiple, after finding unusual customers, the corresponding target of these customer informations is determined
Operation system.The transaction record of the customer information is inquired from the database of target service system.Filter out qualified friendship
Easily record is as abnormal transaction record.Specifically, the friendship of unusual customers is inquired from the database of corresponding target service system
Easily record;If target service system is the first pre-set business system, using the newest transaction record of unusual customers as different
Normal transaction record;If target service system is the second pre-set business system, whether unusual customers are detected in prefixed time interval
It is interior to generate new transaction record;If so, using the transaction record detected as abnormal transaction record;If it is not, then will be abnormal objective
The transaction record nearest apart from current point in time is as abnormal transaction record in the current business term of validity at family.
As an implementation, above-mentioned first pre-set business system can be the operation systems such as security, letter guarantor, can obtain
Take the newest transaction record of client as abnormal transaction record.By taking the second pre-set business system is insurance business system as an example,
If the unusual customers do not have transaction record within a preset time interval, obtain in the current Effective Period of Insurance of the customer information
Transaction record is as abnormal transaction record.Further, if no deal records in Effective Period of Insurance, historical transaction record is obtained
The middle transaction record nearest apart from current point in time is as abnormal transaction record.
Include in the unusual customers case of generation in customer information with matched field and warning level in blacklist
Etc. information, these message reflections go out the intensity of anomaly of client.And in abnormal case of merchandising include then the abnormal transaction got
Record, reflects the abnormal trading situation of unusual customers.Above-mentioned case is sent at preset agency node, it is possible to understand that
It is that the blacklist list of separate sources corresponds to different agency nodes, it therefore, can be according to being matched to when generating case
The corresponding blacklist of unusual customers generate multiple case tables, and be sent to corresponding agency node.
Client's recognition methods that above example proposes identifies that the time interval of operation reaches prefixed time interval in client
When, determine the target service system for needing to scan, and then obtain the customer data table and/or trading object of the target service system
Tables of data, and determine blacklist list to be matched.According to preset matching rule by customer data table and/or trading object number
It is matched with blacklist list according to table, finds out unusual customers, inquired from the database of corresponding target service system different
The transaction record at regular guest family will meet the transaction record of preset condition as abnormal transaction record.To be given birth to according to unusual customers
At unusual customers case, abnormal transaction case is generated according to abnormal transaction record, and by unusual customers case and abnormal transaction case
Example is sent to reset mechanism node, and the present invention is identified the unusual customers of multiple operation systems by matching rule, generates
Unified unusual customers case and abnormal transaction case, improve the recognition efficiency of unusual customers, enhance risk control capability.
In addition, the embodiment of the present invention also proposes a kind of computer readable storage medium, the computer readable storage medium
On be stored with client's recognizer, client's recognizer can be executed by one or more processors, to realize following operation:
When client identifies that the time interval of operation reaches prefixed time interval, the target service system for needing to scan is determined
System;
Obtain the current customer data table of the target service system and/or trading object tables of data, and determine with it is described
The corresponding blacklist list of target service system;
According to the update status of the customer data table and/or trading object tables of data in the prefixed time interval,
The customer data table and/or trading object tables of data are matched with the blacklist list, find out unusual customers;
The transaction record that the unusual customers are inquired from the database of corresponding target service system, will meet default item
The transaction record of part is as abnormal transaction record;
Unusual customers case is generated according to the match condition of unusual customers, abnormal hand over is generated according to the abnormal transaction record
Easy case, and the unusual customers case and the abnormal transaction case are sent to reset mechanism node.Computer of the present invention
Readable storage medium storing program for executing specific implementation mode and above-mentioned client's identification device and each embodiment of method are essentially identical, do not make to tire out herein
It states.
It should be noted that the embodiments of the present invention are for illustration only, can not represent the quality of embodiment.And
The terms "include", "comprise" herein or any other variant thereof is intended to cover non-exclusive inclusion, so that packet
Process, device, article or the method for including a series of elements include not only those elements, but also include being not explicitly listed
Other element, or further include for this process, device, article or the intrinsic element of method.Do not limiting more
In the case of, the element that is limited by sentence "including a ...", it is not excluded that in the process including the element, device, article
Or there is also other identical elements in method.
Through the above description of the embodiments, those skilled in the art can be understood that above-described embodiment side
Method can add the mode of required general hardware platform to realize by software, naturally it is also possible to by hardware, but in many cases
The former is more preferably embodiment.Based on this understanding, technical scheme of the present invention substantially in other words does the prior art
Going out the part of contribution can be expressed in the form of software products, which is stored in one as described above
In storage medium (such as ROM/RAM, magnetic disc, CD), including some instructions use so that a station terminal equipment (can be mobile phone,
Computer, server or network equipment etc.) execute method described in each embodiment of the present invention.
It these are only the preferred embodiment of the present invention, be not intended to limit the scope of the invention, it is every to utilize this hair
Equivalent structure or equivalent flow shift made by bright specification and accompanying drawing content is applied directly or indirectly in other relevant skills
Art field, is included within the scope of the present invention.
Claims (10)
1. a kind of client's identification device, which is characterized in that described device includes memory and processor, is stored on the memory
There is the client's recognizer that can be run on the processor, is realized such as when client's recognizer is executed by the processor
Lower step:
When client identifies that the time interval of operation reaches prefixed time interval, the target service system for needing to scan is determined;
The current customer data table of the target service system and/or trading object tables of data are obtained, and is determined and the target
The corresponding blacklist list of operation system;
According to the update status of the customer data table and/or trading object tables of data in the prefixed time interval, by institute
It states customer data table and/or trading object tables of data is matched with the blacklist list, find out unusual customers;
The transaction record that the unusual customers are inquired from the database of corresponding target service system, will meet preset condition
Transaction record is as abnormal transaction record;
Unusual customers case is generated according to the match condition of unusual customers, abnormal transaction case is generated according to the abnormal transaction record
Example, and the unusual customers case and the abnormal transaction case are sent to reset mechanism node.
2. client's identification device as described in claim 1, which is characterized in that described according to the customer data table and/or friendship
Easy update status of the object data table in the prefixed time interval, by the customer data table and/or trading object data
The step of table is matched with the blacklist list, finds out unusual customers include:
It detects the customer data table and/or whether trading object tables of data updates in the prefixed time interval;
If so, increment customer data and/or increment trading object data are obtained, it is according to the matching rule that the increment is objective
User data and/or increment trading object data are matched with the blacklist list of full dose, find out unusual customers;
If it is not, then detecting whether the blacklist list updates in the prefixed time interval;
If so, increment blacklist list is obtained, according to the matching rule by the institute of the increment blacklist list and full dose
It states customer data table and/or trading object tables of data is matched, find out unusual customers.
3. client's identification device as claimed in claim 2, which is characterized in that according to the matching rule by the black name of the increment
The step of single-row table is matched with the customer data table and/or trading object tables of data of full dose, finds out unusual customers
Including:
According to preset multiple items of information, by the customer data table of full dose and/or trading object tables of data user information with
Personal information in increment blacklist list is matched one by one;
If the content of multiple presupposed information items is inconsistent, judge the client for normal clients;
If there is the content of presupposed information item consistent, judge the client for unusual customers.
4. client's identification device as claimed in claim 3, which is characterized in that described to be generated according to the match condition of unusual customers
The step of unusual customers case includes:
The quantity of the consistent presupposed information item of content is obtained, and warning level is determined according to the quantity of acquisition;
Determine the matching field of the consistent presupposed information item of content;
Unusual customers case is generated according to the information of the unusual customers, the warning level and the matching field.
5. client's identification device as described in any one of Claims 1-4, which is characterized in that described from corresponding target
The transaction record that the unusual customers are inquired in the database of operation system will meet the transaction record of preset condition as the visitor
The step of abnormal transaction record at family includes:
The transaction record of the unusual customers is inquired from the database of corresponding target service system;
If the target service system is the first pre-set business system, the newest transaction record of the unusual customers is made
For abnormal transaction record;
If the target service system is the second pre-set business system, whether the unusual customers are detected in prefixed time interval
It is interior to generate new transaction record;
If so, using the transaction record detected as abnormal transaction record;
If it is not, then using transaction record nearest apart from current point in time in the current business term of validity of the unusual customers as different
Normal transaction record.
6. a kind of client's recognition methods, which is characterized in that the method includes:
When client identifies that the time interval of operation reaches prefixed time interval, the target service system for needing to scan is determined;
The current customer data table of the target service system and/or trading object tables of data are obtained, and is determined and the target
The corresponding blacklist list of operation system;
According to the update status of the customer data table and/or trading object tables of data in the prefixed time interval, by institute
It states customer data table and/or trading object tables of data is matched with the blacklist list, find out unusual customers;
The transaction record that the unusual customers are inquired from the database of corresponding target service system, will meet preset condition
Transaction record is as abnormal transaction record;
Unusual customers case is generated according to the match condition of unusual customers, abnormal transaction case is generated according to the abnormal transaction record
Example, and the unusual customers case and the abnormal transaction case are sent to reset mechanism node.
7. client's recognition methods as claimed in claim 6, which is characterized in that described according to the customer data table and/or friendship
Easy update status of the object data table in the prefixed time interval, by the customer data table and/or trading object data
The step of table is matched with the blacklist list, finds out unusual customers include:
It detects the customer data table and/or whether trading object tables of data updates in the prefixed time interval;
If so, increment customer data and/or increment trading object data are obtained, it is according to the matching rule that the increment is objective
User data and/or increment trading object data are matched with the blacklist list of full dose, find out unusual customers;
If it is not, then detecting whether the blacklist list updates in the prefixed time interval;
If so, increment blacklist list is obtained, according to the matching rule by the institute of the increment blacklist list and full dose
It states customer data table and/or trading object tables of data is matched, find out unusual customers.
8. client's recognition methods as claimed in claim 7, which is characterized in that according to the matching rule by the black name of the increment
The step of single-row table is matched with the customer data table and/or trading object tables of data of full dose, finds out unusual customers
Including:
According to preset multiple items of information, by the customer data table of full dose and/or trading object tables of data user information with
Personal information in increment blacklist list is matched one by one;
If the content of multiple presupposed information items is inconsistent, judge the client for normal clients;
If there is the content of presupposed information item consistent, judge the client for unusual customers.
9. client's recognition methods as described in any one of claim 6 to 8, which is characterized in that described from corresponding target industry
The transaction record that the unusual customers are inquired in the database of business system will meet the transaction record of preset condition as the client
Abnormal transaction record the step of include:
The transaction record of the unusual customers is inquired from the database of corresponding target service system;
If the target service system is the first pre-set business system, the newest transaction record of the unusual customers is made
For abnormal transaction record;
If the target service system is the second pre-set business system, whether the unusual customers are detected in prefixed time interval
It is interior to generate new transaction record;
If so, using the transaction record detected as abnormal transaction record;
If it is not, then using transaction record nearest apart from current point in time in the current business term of validity of the unusual customers as different
Normal transaction record.
10. a kind of computer readable storage medium, which is characterized in that be stored with client's knowledge on the computer readable storage medium
Other program, client's recognizer can be executed by one or more processor, to realize as any in claim 6 to 9
Described in client's recognition methods the step of.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810768273.9A CN108694657B (en) | 2018-07-13 | 2018-07-13 | Client identification apparatus, method and computer-readable storage medium |
| PCT/CN2018/107720 WO2020010714A1 (en) | 2018-07-13 | 2018-09-26 | Client identification apparatus and method, and computer-readable storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810768273.9A CN108694657B (en) | 2018-07-13 | 2018-07-13 | Client identification apparatus, method and computer-readable storage medium |
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| CN108694657A true CN108694657A (en) | 2018-10-23 |
| CN108694657B CN108694657B (en) | 2023-04-18 |
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|---|---|---|---|
| CN201810768273.9A Active CN108694657B (en) | 2018-07-13 | 2018-07-13 | Client identification apparatus, method and computer-readable storage medium |
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| WO (1) | WO2020010714A1 (en) |
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109840316A (en) * | 2018-12-21 | 2019-06-04 | 上海诺悦智能科技有限公司 | A kind of customer information sanction list matching system |
| CN109902747A (en) * | 2019-03-01 | 2019-06-18 | 成都农村商业银行股份有限公司 | A kind of personal identification method, device, equipment and computer readable storage medium |
| CN109918408A (en) * | 2019-03-01 | 2019-06-21 | 成都农村商业银行股份有限公司 | A kind of blacklist update method, device, equipment and computer readable storage medium |
| CN110070445A (en) * | 2019-04-28 | 2019-07-30 | 深圳前海微众银行股份有限公司 | A kind of transaction processing method and device based on block catenary system |
| CN110335069A (en) * | 2019-06-19 | 2019-10-15 | 中国平安财产保险股份有限公司 | A kind of method, apparatus, computer equipment and storage medium counting first degree of dragging on |
| CN111212073A (en) * | 2020-01-02 | 2020-05-29 | 中国银行股份有限公司 | Public cloud-based blacklist account sharing method and device |
| WO2020253348A1 (en) * | 2019-06-17 | 2020-12-24 | 深圳壹账通智能科技有限公司 | Abnormality information identification method and apparatus, computer device and storage medium |
| CN112486964A (en) * | 2020-11-26 | 2021-03-12 | 中国人寿保险股份有限公司 | Target identification method and device |
| CN114549193A (en) * | 2021-12-21 | 2022-05-27 | 上海金仕达软件科技有限公司 | List screening method, apparatus, device, storage medium and program product |
| CN116809652A (en) * | 2023-03-28 | 2023-09-29 | 材谷金带(佛山)金属复合材料有限公司 | Abnormality analysis method and system for hot rolling mill control system |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20130212680A1 (en) * | 2012-01-12 | 2013-08-15 | Arxceo Corporation | Methods and systems for protecting network devices from intrusion |
| WO2017152765A1 (en) * | 2016-03-10 | 2017-09-14 | 阿里巴巴集团控股有限公司 | Automatic fusing-based message sending method, device and system |
| CN107993006A (en) * | 2017-11-30 | 2018-05-04 | 平安科技（深圳）有限公司 | Warning grade determines method, apparatus, equipment and readable storage medium storing program for executing |
Family Cites Families (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102270334A (en) * | 2011-09-08 | 2011-12-07 | 成都讯业科技有限公司 | Safety management method and system for financial service |
| CN106649845A (en) * | 2016-12-30 | 2017-05-10 | 上海富聪金融信息服务有限公司 | Transaction information service platform and information processing method thereof |
| CN106920170B (en) * | 2017-03-02 | 2021-07-27 | 北京小米移动软件有限公司 | Transaction reminding method and device |
| CN107437179A (en) * | 2017-08-09 | 2017-12-05 | 中国银行股份有限公司 | A kind of banking channels system that risk monitoring and control and special service are provided |
| CN107767021A (en) * | 2017-09-12 | 2018-03-06 | 阿里巴巴集团控股有限公司 | A kind of risk control method and equipment |
-
2018
- 2018-07-13 CN CN201810768273.9A patent/CN108694657B/en active Active
- 2018-09-26 WO PCT/CN2018/107720 patent/WO2020010714A1/en active Application Filing
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20130212680A1 (en) * | 2012-01-12 | 2013-08-15 | Arxceo Corporation | Methods and systems for protecting network devices from intrusion |
| WO2017152765A1 (en) * | 2016-03-10 | 2017-09-14 | 阿里巴巴集团控股有限公司 | Automatic fusing-based message sending method, device and system |
| CN107993006A (en) * | 2017-11-30 | 2018-05-04 | 平安科技（深圳）有限公司 | Warning grade determines method, apparatus, equipment and readable storage medium storing program for executing |
Cited By (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109840316A (en) * | 2018-12-21 | 2019-06-04 | 上海诺悦智能科技有限公司 | A kind of customer information sanction list matching system |
| CN109902747A (en) * | 2019-03-01 | 2019-06-18 | 成都农村商业银行股份有限公司 | A kind of personal identification method, device, equipment and computer readable storage medium |
| CN109918408A (en) * | 2019-03-01 | 2019-06-21 | 成都农村商业银行股份有限公司 | A kind of blacklist update method, device, equipment and computer readable storage medium |
| CN109902747B (en) * | 2019-03-01 | 2023-08-29 | 成都农村商业银行股份有限公司 | Identity recognition method, device, equipment and computer readable storage medium |
| CN110070445A (en) * | 2019-04-28 | 2019-07-30 | 深圳前海微众银行股份有限公司 | A kind of transaction processing method and device based on block catenary system |
| CN110070445B (en) * | 2019-04-28 | 2024-03-01 | 深圳前海微众银行股份有限公司 | Transaction processing method and device based on blockchain system |
| WO2020253348A1 (en) * | 2019-06-17 | 2020-12-24 | 深圳壹账通智能科技有限公司 | Abnormality information identification method and apparatus, computer device and storage medium |
| CN110335069A (en) * | 2019-06-19 | 2019-10-15 | 中国平安财产保险股份有限公司 | A kind of method, apparatus, computer equipment and storage medium counting first degree of dragging on |
| CN111212073B (en) * | 2020-01-02 | 2022-07-05 | 中国银行股份有限公司 | Public cloud-based blacklist account sharing method and device |
| CN111212073A (en) * | 2020-01-02 | 2020-05-29 | 中国银行股份有限公司 | Public cloud-based blacklist account sharing method and device |
| CN112486964A (en) * | 2020-11-26 | 2021-03-12 | 中国人寿保险股份有限公司 | Target identification method and device |
| CN112486964B (en) * | 2020-11-26 | 2024-04-26 | 中国人寿保险股份有限公司 | Target identification method and device |
| CN114549193A (en) * | 2021-12-21 | 2022-05-27 | 上海金仕达软件科技有限公司 | List screening method, apparatus, device, storage medium and program product |
| CN116809652A (en) * | 2023-03-28 | 2023-09-29 | 材谷金带(佛山)金属复合材料有限公司 | Abnormality analysis method and system for hot rolling mill control system |
| CN116809652B (en) * | 2023-03-28 | 2024-04-26 | 材谷金带(佛山)金属复合材料有限公司 | Abnormality analysis method and system for hot rolling mill control system |
Also Published As
| Publication number | Publication date |
|---|---|
| CN108694657B (en) | 2023-04-18 |
| WO2020010714A1 (en) | 2020-01-16 |
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