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WO2019104867A1 - Procédé, appareil et dispositif de détermination de niveau d'alerte précoce, et support de stockage lisible - Google Patents

Procédé, appareil et dispositif de détermination de niveau d'alerte précoce, et support de stockage lisible Download PDF

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Publication number
WO2019104867A1
WO2019104867A1 PCT/CN2018/075166 CN2018075166W WO2019104867A1 WO 2019104867 A1 WO2019104867 A1 WO 2019104867A1 CN 2018075166 W CN2018075166 W CN 2018075166W WO 2019104867 A1 WO2019104867 A1 WO 2019104867A1
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Prior art keywords
information
blacklist
name
matching
matching degree
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PCT/CN2018/075166
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English (en)
Chinese (zh)
Inventor
冯跃东
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Ping An Technology Shenzhen Co Ltd
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Ping An Technology Shenzhen Co Ltd
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Publication of WO2019104867A1 publication Critical patent/WO2019104867A1/fr
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    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; 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
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0635—Risk analysis of enterprise or organisation activities
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; 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
    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes

Definitions

  • the present application mainly relates to the technical field of financial early warning systems, and in particular to a method, device, device and readable storage medium for determining an early warning level.
  • the early warning strategy is to use the method of purchasing services to match the blacklist pages.
  • the matching method is single and cannot be matched according to the degree of matching.
  • the high and low level of early warning is not conducive to business decision making based on early warning grading, the judgment is inaccurate, and the false positive rate is high.
  • the main purpose of the present application is to provide a method, device, device and readable storage medium for determining an early warning level, which aims to solve the problem that the customer warning is not classified in the prior art.
  • the present application provides an early warning level determining method, where the early warning level determining method includes the following steps:
  • the detection When the detection reaches the preset timing, acquiring registration information of the first object in the system and marking information of the second object in the blacklist, wherein the registration information includes a document type, a certificate number, and an object name;
  • the present application further provides an early warning level determining apparatus, where the early warning level determining apparatus includes:
  • An obtaining module configured to acquire registration information of the first object in the system and tag information of the second object in the blacklist when the detection reaches the preset timing, where the registration information includes a certificate type, a certificate number, and an object name;
  • a matching module configured to match the registration information and the tag information of each second object in the blacklist to determine matching degree information of each first object
  • a determining module configured to determine, according to the matching degree information, each first object alert level.
  • the present application further provides an early warning level determining device, where the early warning level determining device includes: a memory, a processor, a communication bus, and an early warning level determining program stored on the memory;
  • the communication bus is used to implement connection communication between a processor and a memory
  • the processor is configured to execute the early warning level determining program to implement the following steps:
  • the detection When the detection reaches the preset timing, acquiring registration information of the first object in the system and marking information of the second object in the blacklist, wherein the registration information includes a document type, a certificate number, and an object name;
  • the present application also provides a readable storage medium storing one or more programs, the one or more programs being executable by one or more processors Used for:
  • the detection When the detection reaches the preset timing, acquiring registration information of the first object in the system and marking information of the second object in the blacklist, wherein the registration information includes a document type, a certificate number, and an object name;
  • the apparatus for determining the warning level of the embodiment, the device, and the readable storage medium when the detection reaches the preset timing, acquiring the registration information of the first object in the system and the marking information of the second object in the blacklist, wherein the registration information includes the identification Type, document number, and object name; and matching the document type, the document number, and the object name in the registration information with the tag information of each second object in the blacklist to determine the matching degree information of each first object, thereby determining the matching degree Information to determine the customer alert level for each first object.
  • the scheme determines the first type by matching the document type, the document number and the object name in the registration information with the tag information of the second object in the blacklist, and according to the degree of matching between the registration information and the tag information.
  • Different matching degree information of the object determining different early warning levels of each first object, making the determination of the early warning level more accurate, and adopting different processing mechanisms for the first object of different early warning levels To achieve accurate business decisions based on early warning grading.
  • FIG. 1 is a schematic flow chart of a first embodiment of a method for determining an early warning level according to the present application
  • FIG. 2 is a schematic diagram of functional modules of a first embodiment of the early warning level determining apparatus of the present application
  • FIG. 3 is a schematic structural diagram of a device in a hardware operating environment involved in a method according to an embodiment of the present application.
  • the application provides a method for determining an early warning level.
  • FIG. 1 is a schematic flowchart of a first embodiment of a method for determining an alert level according to the present application.
  • the method for determining an alert level includes:
  • Step S10 when the detection reaches the preset timing, acquiring registration information of the first object in the system and marking information of the second object in the blacklist, wherein the registration information includes a document type, a certificate number, and an object name;
  • the pre-time is to pre-set the time required for scanning and monitoring of customers in the financial institution system.
  • the first object includes a person or institution that has business dealings with the financial institution, that is, a customer of a financial institution, such as a financial institution holding a savings card or a credit card.
  • a person or agency legal representative, and a business receiver or institution that has a business relationship with such person or organization, such as a transfer card to a person or institution, the person or institution receiving the transfer is the business receiver or mechanism.
  • the registration information of the first object is obtained, and the registration information includes but is not limited to the document type, the document number, the object name, and the like.
  • the registration information also includes the country to which the service receiving person or institution belongs, and the name of the financial institution used.
  • the second object in the blacklist also includes a person and an organization, and the tag information is information such as a document type, a certificate number, and a name or an alias involved in each person or institution as a second object in the blacklist.
  • the first object in the financial institution is updated
  • the second object in the blacklist is also updated, so that the preset timing of detection includes when a new first object appears in the financial institution and the blacklist is updated.
  • the financial institution system is initialized, a system vulnerability may occur, and the system initialization is also taken as a preset time.
  • a new first object or a blacklist update occurs in the financial institution, the document type, the certificate number, and the object name of the registration information of the first object and the tag information of the second object in the blacklist are obtained from the system. .
  • Step S20 Matching the registration information with the tag information of each second object in the blacklist to determine matching degree information of each first object
  • the first object in the financial institution and the plurality of recipients that have transactions with the first object are numerous, and after acquiring the registration information of the first object and the marking information of the second object in the blacklist, the registration information is The document type, the document number, and the object name and the tag information of the second object in the blacklist are scanned and matched, and the matching degree information of each first object is determined.
  • the preset timing is the system initialization
  • the inventory customer and the blacklist in the financial institution are scanned and matched, wherein the stock customer is the number of customers held by the financial institution in a certain period of time, that is, the financial institution has The customer is able to redevelop the customer.
  • the existing customers in the system are scanned and matched to ensure the security of existing customers.
  • the default time is for a new customer in a financial institution
  • all customers in the system are scanned and matched to ensure the security of new customers and stock customers.
  • the preset timing is blacklist update
  • the scan client and the receiver that transactions with the customer are scanned and matched against the stock customer in the system and the blacklist update date to ensure the security of the stock customer and the receiver. Since each registration information involves multiple pieces of single item information, when the matching with the tag information, the degree of matching may be inconsistent, some registration information and the tag information have a high degree of matching, while others have a low degree of matching.
  • the level of matching determined is used as the matching degree information.
  • Step S30 determining, according to the matching degree information, each first object client alert level.
  • each first object early warning registration is determined according to the matching degree information.
  • the matching degree of the matching degree information is higher, the consistency between the item existing in the registration information and the tag information of a second object in the blacklist is higher, that is, the more likely the first object is a member in the blacklist.
  • the matching degree of the matching degree information is lower, the lower the consistency between the items existing in the registration information and the marking information of the second object in the blacklist, the lower the possibility that the blacklist members are lower, thereby The alert level is determined to be a lower level.
  • the higher the degree of matching the more likely the first object is to be a member of the blacklist, the higher the alert level is determined to be the first object that is dangerous, and the early warning is performed.
  • the method for determining the warning level of the embodiment when the detection reaches the preset timing, acquiring the registration information of the first object in the system and the marking information of the second object in the blacklist, wherein the registration information includes a document type, a certificate number, and an object name; And matching the document type, the document number, and the object name in the registration information with the tag information of each second object in the blacklist, determining the matching degree information of each first object, thereby determining the first object according to the matching degree information.
  • Customer warning level The scheme determines the first type by matching the document type, the document number and the object name in the registration information with the tag information of the second object in the blacklist, and according to the degree of matching between the registration information and the tag information.
  • Different matching degree information of the object determining different early warning levels of each first object, making the determination of the early warning level more accurate, and adopting different processing mechanisms for the first object of different early warning levels To achieve accurate business decisions based on early warning grading.
  • the registration information and the second object in the blacklist are The step of matching the tag information to determine the matching degree information of each first object.
  • Step S21 when the document type is the first preset document type, determining whether the document number is complete;
  • the first object has a plurality of types of documents, such as an ID card, a driver's license, a passport, etc., a business license, etc., and the information contained in the various documents is different.
  • the ID card is used as the first default document type.
  • the document type is the first default document type, that is, the ID card
  • Step S22 if the document number is complete, it is determined whether the marking information of each second object in the blacklist has a target document number corresponding to the document number;
  • the document number When the document number is included in the registration information, and the document number is complete, it is determined whether there is a target document number corresponding to the document number in the marking information of each second object in the blacklist, that is, whether a second object exists in the blacklist.
  • the document number of the second object is consistent with the document number of the first object.
  • the first-generation ID card number is 15
  • the second-generation ID card number is 18. Therefore, when judging the identity of the ID card number, it is compatible with the 15-digit and 18-digit ID cards.
  • the 7th and 8th digits of the 18-digit ID card number usually the year of birth
  • the last digit possibly a number may also be used.
  • step S23 when the tag information of each second object in the blacklist has a target document number corresponding to the certificate number, the object name is matched, and the matching degree information of the first object is determined.
  • the matching of the object names is further performed to determine the matching degree information of the first object.
  • the tag information does not have the tag information of the target document number that is consistent with the ID number, it means that there is no member in the blacklist that is consistent with the first object ID number, because the ID card is a certificate characterizing the uniqueness of the first object. It can be said that the first object may not be a member of the blacklist, and the degree of matching is not the highest level.
  • the steps to match the object name include:
  • step S231 the object name and the tag information of each second object in the blacklist are completely matched, and it is determined whether the object name and the tag information of each second object in the blacklist are completely matched.
  • the object name corresponding to the document number and the tag information of each second object in the blacklist are performed.
  • Exact match is to match whether the name or alias in the blacklist is exactly the same as the object name, and is compatible with spaces, capitalization, special characters, and for the foreign name, the word order is reversed. And determine whether the exact match is successful to determine the match degree information.
  • Step S232 when the object name and the tag information of each second object in the blacklist are successfully matched, the matching degree information is determined to be a first level;
  • the object name and the tag information of each second object in the blacklist are completely matched, that is, if the name or the alias in the blacklist is completely consistent with the object name, the object name is the name or alias of the member in the blacklist. . Therefore, the document number corresponding to the object name is also the ID number of the member having the name or the alias in the blacklist, that is, the object name of the first object and the ID number corresponding to the name or alias of a member in the blacklist and the ID number.
  • the object name and the corresponding document number are present in the blacklisted tag information, and the matching degree of the registration information and the tag information is high, thereby determining the matching degree information to the first level.
  • Step S233 when the object name and the tag information of each second object in the blacklist fail to be completely matched, the object name and the tag information of each second object in the blacklist are partially matched, and when the partial matching is successful, the first The matching degree information of an object is a secondary level.
  • the object name and the tag information of each second object in the blacklist fail to be completely matched, that is, when the tag name does not have a name or an alias that completely matches the object name
  • the object name and the second object in the blacklist are The tag information is partially matched.
  • the partial matching is used to determine whether there is a name or an alias in the mark information that is consistent with the object name part.
  • the preset value is uniformly set for the part, and when the consistent part is greater than the preset value, the part is determined. The match was successful.
  • the partial matching of the embodiment is for a foreign language name whose number of words in the name is greater than 3, and the number of words is a word that removes a high hit ratio and does not contribute much to the matching accuracy, such as in, At, on, with, for, by, about, to, of, for, from, under, an, the, and, or Company, LIMITED, LTD, CHINA, Hong, Kong, group, TRADING, OVERSEA, INTERNATIONAL, PTE, HOLDING, HK, IMPORT, EXPORT Co et al.
  • the preset value is a value set in advance according to the requirement. If the value is set to be equal to 3, when it is determined that at least 3 or more foreign words in the name are the same, it may be determined that the partial matching is successful, otherwise the partial matching fails.
  • the document number corresponding to the object name is determined to be the target document number of the person with the name or alias in the blacklist flag information, and the object name is corresponding to the name of the document number in the tag information.
  • the alias parts are the same, so that the matching degree information can be determined to be a second level below the first level.
  • the partial matching fails, the name or alias corresponding to the target document number in the blacklist marking information is inconsistent with the object name corresponding to the first object identification number, and the second level matching fails.
  • a third embodiment of the present application is proposed.
  • the third embodiment when the document type is the first preset document type, the certificate is judged. After the steps are complete, the steps include:
  • Step S24 If the ID number is incomplete, the object name and the tag information of each second object in the blacklist are completely matched, and it is determined whether the object name and the tag information of each second object in the blacklist are completely matched. ;
  • the matching of the ID numbers in the registration information cannot be performed, and the object names in the registration information are matched.
  • the object name and the tag information of each second object in the blacklist are completely matched, and it is determined whether the exact match is successful, to determine the matching degree information of the first object.
  • step S25 when the object name and the tag information of each second object in the blacklist are successfully matched, the matching degree information of the first object is determined to be three levels;
  • the object name and the tag information of each second object in the blacklist are completely matched, that is, if the name or the alias of the object name is completely in the tag information of the blacklist, the object name is a member of the blacklist. Name or alias.
  • the ID number corresponding to the object name is not the ID number of the person with the name or alias in the tag information, the matching degree of the registration information and the tag information is low, so that the matching degree information is determined to be three levels below the second level. .
  • Step S26 When the object name and the tag information of each second object in the blacklist fail to be completely matched, the object name and the tag information of each second object in the blacklist are partially matched, and when the partial matching is successful, the first The matching degree information of an object is four levels.
  • the object name and the tag information of each second object in the blacklist fail to be completely matched, that is, when the name or the alias of the object name does not exist in the tag information of the blacklist, the object name and the blacklist are respectively
  • the tag information of the two objects is partially matched to determine whether there is a name or an alias in the tag information that is consistent with the object name portion.
  • the determination part matches successfully, there is a name or an alias in the mark information that is consistent with the object name part, but the document number corresponding to the object name is not the target document number of the person with the name or alias in the tag information, and the object name is The same as the name or the alias portion in the tag information, so that the matching degree information can be determined to be four levels below the third level.
  • the partial matching fails, it indicates that neither the object name nor the document number exists in the tag information, and the degree of matching of the four levels is determined to fail.
  • the registration information and the marking information of each second object in the blacklist are The steps of performing matching and determining the matching degree information of each first object.
  • Step S27 when the document type is the second preset document type, determining whether the date of birth is included in the registration information;
  • the other types of documents other than the identity are used as the second default document type, because the information contained in the other documents is not as versatile as the information contained in the identity card, and the information is not as comprehensive as the information may not include. date of birth. Therefore, when the document type is other than the ID card, that is, the second preset document type, it is determined whether the registration date includes the date of birth, so as to determine the matching degree information of each first object according to the date of birth. .
  • Step S28 if the date of birth is included in the registration information, it is determined whether the marking information of each second object in the blacklist has a target document number corresponding to the document number;
  • the registration information includes the date of birth
  • the matching degree information is determined by matching the object name.
  • the specific matching manner is the same as that in the third embodiment, and details are not described herein. Therefore, the document type is other than the ID card as the first default document type, such as a driver's license or a passport, so in judging, it is necessary to first determine whether the document type exists in the tag information, and the corresponding document number. .
  • the certificate type matches the tag type in the tag information
  • whether the tag information of each second object in the blacklist has a judgment of the target document number corresponding to the certificate number of the registration information is performed.
  • the document number in the registration information is read, and the document number of the tag information of each second object in the blacklist is compared one by one to determine whether there is a target document number corresponding to the document number in the tag information.
  • step S29-1 when the tag information of each second object in the blacklist has a target document number corresponding to the certificate number, the object name is matched, and the matching degree information of the first object is determined.
  • the matching of the object names is further performed to determine the matching degree information of the first object.
  • the steps of matching the object names are the same as those of the second embodiment, and are not described herein.
  • Step S29-2 when the tag information of each second object in the blacklist does not have the target document number corresponding to the certificate number, the object name, the date of birth, and the tag information of each second object in the blacklist are completely matched. And when the exact match is successful, it is determined that the matching degree information of the first object is an intermediate degree between the second level and the third level.
  • the tag information exists in the same manner as the object name and the date of birth, and the consistent object name and date of birth are the same member in the blacklist, it can be determined that the exact match is successful, otherwise the exact match fails.
  • the exact match is successful, the match involves the object name and the date of birth, and the certificate number is not involved, and the second level is successfully determined by the matching of the document number and the object name part, and the third match is determined by the object name exact match, so that the object The match between the name and the date of birth is determined by the degree of matching between the second and third levels.
  • the step of matching the object name to determine the matching degree information includes:
  • Step q1 determining whether the font type of the object name and the name font type of the mark information of each second object in the blacklist are consistent;
  • the main characters in mainland China are mainly simplified characters, while the Hong Kong, Macao and Taiwan regions are mainly based on traditional Chinese characters, resulting in the names of objects in financial institutions being simplified characters and published in the blacklist.
  • the name or alias is a traditional Chinese character, or the object name in the financial institution is a traditional Chinese character, and the name or alias in the published blacklist is a simplified Chinese character.
  • the object name and the font type of the name or alias in the blacklist are inconsistent. If the scan matching is performed on this basis, the matching success rate will be lowered, which will affect the judgment of the warning level. Therefore, the present embodiment is provided with a font type conversion mechanism, and determines whether the font type of the object name and the name font type of the mark information of each second object in the blacklist are consistent, so as to determine whether font type conversion is required according to the judgment result.
  • step q2 when the font type of the object name and the name font type of the mark information of each second object in the blacklist match, the object name matching is performed, and the matching degree information of the first object is determined;
  • Step q3 when the font type of the object name and the name font type of the mark information of each second object in the blacklist are inconsistent, the font type of the object name and the name font type of the mark information of the second object in the blacklist are converted, And after the conversion, the object name is matched, and the matching degree information of the first object is determined.
  • the font type conversion is required, and the font type of the object name is converted into the second object in the blacklist.
  • the name of the tag information is the same as the font type, or the name font type of the tag information of the second object in the blacklist is converted to match the font type of the object name, so that the font types of the two converted versions are the same.
  • a font library may be set, and when a conversion is needed, a font corresponding to the font type to be converted is searched from the font library to implement conversion of the font type. After the font type operation is converted, the matching of the object names is performed, and the matching degree information of the first object is determined to avoid the determination of the warning level due to the difference in the font type.
  • the step of determining the first object early warning level according to the matching degree information includes:
  • the matching degree information of the first object is a level one level, determining that the first object warning level is a first level warning;
  • the matching degree information of the first object is three levels, determining that the first object warning level is a three-level warning;
  • the matching degree information of the first object is four levels, it is determined that the first object warning level is a four-level warning.
  • the customer early warning level is divided into a first-level early warning, a second-level early warning, a third-level early warning, and a fourth-level early warning.
  • the matching degree information of the first object is a level one level, determining that the first object warning level is a first level warning; when the matching degree information of the first object is a level two level, determining that the first object warning level is a second level warning;
  • the matching degree information of the first object is three levels
  • the first object early warning level is determined to be a three-level early warning; when the first object matching degree information is four levels, the first object early warning level is determined to be a four-level early warning.
  • the order of matching from high to low is the first level, the second level, the third level and the fourth level, so the order of the corresponding early warning levels from high to low is also the first level warning, the second level warning, and the third level warning. And four levels of warning.
  • the first-level warning is that the ID number and the name are completely matched
  • the second-level warning is the matching of the ID number and the name part
  • the third-level warning is the name matching
  • the fourth-level warning is the name part matching
  • the first-level warning is the highest severity
  • the fourth-level warning is the highest.
  • the first object and the corresponding early warning level may be reported to adopt different processing mechanisms according to different first warning levels, such as taking funds for the first object of the first level warning level.
  • the present application is also provided with a mechanism for directly performing one-to-four-level warning level matching or one-to-second level warning level matching, and cannot perform early warning level matching. Specifically, when the first object is a person in a preset list, the first-to-four-level warning level is matched; when the first object is a second-level preset list, the first-to-second level warning level is matched. .
  • One of the default lists includes: 1044-Chinese government list (English), 44-UN (United Nations list) - asset freeze, 1064-UN (United Nations list) - restricted travel, 1152-FATF/GAFI, -9001-Chinese government List (Chinese), -9002 - Chinese name of the Chinese company in the global sanctions list (listable ID in the extension information is '1044', '44', '1064', '1152', '33', '0', '1072 'etc.', 33-EU list (EU), 0-US overseas asset management signature (OFAC), 1072 OFAC enhanced list, etc.
  • the second type of pre-selected list includes: 1020 PEP (Global Political List), -9004 PEP (Chinese Political List), 1021 PEP (American politician list) and so on.
  • a type of preset list and a second type of preset list are set in advance according to requirements, and are not limited to the above list.
  • the present application provides an early warning level determining apparatus.
  • the early warning level determining apparatus includes:
  • the obtaining module 10 is configured to acquire registration information of the first object in the system and tag information of the second object in the blacklist when the detection reaches the preset timing, where the registration information includes a certificate type, a certificate number, and an object name;
  • the matching module 20 is configured to match the registration information and the tag information of each second object in the blacklist to determine matching degree information of each first object;
  • the determining module 30 is configured to determine, according to the matching degree information, each first object client alert level.
  • the obtaining module 10 acquires the registration information of the first object in the system and the marking information of the second object in the blacklist, wherein the registration information includes a document type, a certificate number, and The object name is matched by the matching module 20 to match the document type, the document number, and the object name of the second object in the registration information, and the matching degree information of each first object is determined, so that the determining module 30 is determined.
  • the customer alert level of each first object is determined according to the matching degree information.
  • the scheme determines the first type by matching the document type, the document number and the object name in the registration information with the tag information of the second object in the blacklist, and according to the degree of matching between the registration information and the tag information.
  • Different matching degree information of the object according to the different matching degree information, determining different early warning levels of each first object, making the determination of the early warning level more accurate, and adopting different processing mechanisms for the first object of different early warning levels To achieve accurate business decisions based on early warning grading.
  • the above-mentioned storage medium may be a read only memory, a magnetic disk or an optical disk or the like.
  • FIG. 3 is a schematic structural diagram of a device involved in a hardware operating environment according to an embodiment of the present application.
  • the early warning level determining device in the embodiment of the present application may be a PC, or may be a terminal device such as a smart phone, a tablet computer, an e-book reader, or a portable computer.
  • the early warning level determining device may include a processor 1001, such as a CPU, a memory 1005, and a communication bus 1002.
  • the communication bus 1002 is used to implement connection communication between the processor 1001 and the memory 1005.
  • the memory 1005 may be a high speed RAM memory or a stable memory (non-volatile) Memory), such as disk storage.
  • the memory 1005 can also optionally be a storage device independent of the aforementioned processor 1001.
  • the warning level determining device may further include a user interface, a network interface, a camera, and an RF (Radio) Frequency, RF) circuits, sensors, audio circuits, WiFi modules, and more.
  • the user interface may include a display, an input unit such as a keyboard, and the optional user interface may also include a standard wired interface, a wireless interface.
  • the network interface can optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).
  • warning level determining device does not constitute a limitation of the warning level determining device, and may include more or less components than those illustrated, or combine some components, or different. Parts layout.
  • an operating system may be included in the memory 1005 as a computer storage medium.
  • the operating system is a program that manages and controls the level of alerting to determine the hardware and software resources of the device, and supports the operation of the alert level determining program and other software and/or programs.
  • the network communication module is used to implement communication between components within the memory 1005 and to communicate with other hardware and software in the alert level determining device.
  • the processor 1001 is configured to execute an early warning level determining program stored in the memory 1005 to implement the above-described early warning level determining method.
  • the specific implementation manners of the early warning level determining device of the present application are basically the same as the foregoing embodiments of the foregoing early warning level determining method, and details are not described herein again.
  • the present application provides a readable storage medium storing one or more programs, the one or more programs being further executable by one or more processors for implementing the aforementioned alert level Determine the method.
  • the specific embodiment of the readable storage medium of the present application is substantially the same as the embodiment of the method for determining the early warning level, and details are not described herein again.
  • the technical solution of the present application which is essential or contributes to the prior art, may be embodied in the form of a software product stored in a storage medium (such as ROM/RAM as described above). , a disk, an optical disk, including a number of instructions for causing a terminal device (which may be a mobile phone, a computer, a server, or a network device, etc.) to perform the methods described in the various embodiments of the present application.
  • a terminal device which may be a mobile phone, a computer, a server, or a network device, etc.

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Abstract

L'invention concerne un procédé, un appareil et un dispositif de détermination de niveau d'alerte précoce, ainsi qu'un support de stockage lisible. Le procédé comprend les étapes suivantes : lorsqu'il est détecté qu'une temporisation prédéfinie est atteinte, obtenir des informations d'enregistrement de premiers objets dans un système et des informations de balisage de seconds objets dans une liste noire, les informations d'enregistrement comprenant un type de document, un numéro de document et un nom d'objet; mettre en correspondance les informations d'enregistrement avec les informations de balisage de chaque second objet dans la liste noire afin de déterminer des informations de degré de correspondance de chaque premier objet; et déterminer un niveau d'alerte précoce de chaque premier objet en fonction des informations de degré de correspondance. Au moyen d'une correspondance multidimensionnelle entre les informations d'enregistrement et les informations de balisage, de la détermination de différentes informations de degré de correspondance selon différents degrés de correspondance entre celles-ci, et de la détermination de différents niveaux d'alerte précoce selon les différentes informations de degré de correspondance, un niveau d'alerte précoce peut être déterminé plus précisément, et différents mécanismes de traitement peuvent être adoptés pour des premiers objets de différents niveaux d'alerte précoce, ce qui permet de mettre en œuvre une décision de service précise en fonction du niveau d'alerte précoce.
PCT/CN2018/075166 2017-11-30 2018-02-02 Procédé, appareil et dispositif de détermination de niveau d'alerte précoce, et support de stockage lisible Ceased WO2019104867A1 (fr)

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CN201711247487.3A CN107993006A (zh) 2017-11-30 2017-11-30 预警等级确定方法、装置、设备及可读存储介质

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CN108694657B (zh) * 2018-07-13 2023-04-18 平安科技（深圳）有限公司 客户识别装置、方法及计算机可读存储介质
CN112183973A (zh) * 2020-09-17 2021-01-05 北京中兵智航软件技术有限公司 航班数据的处理方法、装置、存储介质和处理器

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