CN101470887A - Credit early-warning system and method - Google Patents
Credit early-warning system and method Download PDFInfo
- Publication number
- CN101470887A CN101470887A CNA200710301989XA CN200710301989A CN101470887A CN 101470887 A CN101470887 A CN 101470887A CN A200710301989X A CNA200710301989X A CN A200710301989XA CN 200710301989 A CN200710301989 A CN 200710301989A CN 101470887 A CN101470887 A CN 101470887A
- Authority
- CN
- China
- Prior art keywords
- user
- early warning
- loan
- information
- module
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Landscapes
- Financial Or Insurance-Related Operations Such As Payment And Settlement (AREA)
Abstract
The invention discloses an early warning method in loans, which comprises the following steps: collecting user information, associating the user information according to user numbers, then, adding into the user number, determining the risk grade of users according to the user information and the corresponding relation between the user information and the risk grade, and triggering a corresponding flow according to the risk grade of the users. The invention also discloses an early warning system in the loans. The method and the system obtain behaviors of the users in various mechanism units or systems in time, can classify and clean up, then, can adjust fractions, and can observe a state curve diagram of the users in a time section, the corresponding processing flow can be triggered in first time, working staff of a loan related party can be noticed in time, which is convenient for the loan related party to know current conditions of the users and to make various judgment and treatment.
Description
Technical field
The present invention relates to e-commerce field, relate in particular to early warning system and method in a kind of loan.
Background technology
Along with high development of social economy, the enterprises and individuals might be to bank or financial institution's apply for loan.For example, enterprise needs the import of advanced technology and equipment in order to enlarge production scale, yet these technology and equipment all need to spend a large amount of funds usually, millions of easily, up to ten million units.The personal user is for floatation of a company or buy house, also needs to spend hundreds of thousands even unit up to a million.For these enterprises and individual, one-time payment so huge fund is very difficult, and the way of solution just comprises gets a bank loan.Enterprise or personal user after bank verifies enterprise and individual's identity, sign loan agreement by to bank's apply for loan, offer loans then.
Yet in the prior art, the user is between the operating period after obtaining loan, and the credit information channel that bank obtains the associated user is few, upgrades untimelyly, can not in time notify related personnel and mechanism, and triggering risk treatment scheme, and its credit risk control ability is relatively poor.Therefore, bank can not in time get access to situation, management state, the intended use of the loan of using this loan and whether meet loan agreement, situation such as all kinds of record of bad behavior whether occurs, causes finishing back bank in the loan operating period can not regain principal and interest, causes non-performing loan.For example, enterprise is behind loan, bank can't be with cheap cost, mode gets access to its loan fund operating position, day-to-day operations situation, business finance state, sale or relevant informations such as purchase order and content, the amount of money efficiently, perhaps can't know true and comprehensive information, can't in time take corresponding remedial measures, avoid unnecessary loss this enterprise.
Summary of the invention
The problem to be solved in the present invention provides early warning system and method in a kind of loan, in time obtain the behavior that the user is made in all kinds of institutional unitses or system, and can make the mark adjustment behind the taxonomic revision, and can observe the situation curve map of user in certain time period, trigger respective handling flow process and timely call loan related side's staff in the very first time, to this user's As-Is detail knowledge, make all kinds of judgment processing with convenient loan related side.
The invention provides method for early warning in a kind of loan, may further comprise the steps:
Gather user profile according to the sign of user in database;
Determine described user's risk class according to the corresponding relation of described user profile and user profile and risk class;
Risk class according to described user triggers corresponding flow process.
Wherein, also comprise after the described collection user profile:
Described completeness of user information of verification and success status are initiated request to described user and are obtained user profile again under imperfect and status of fail.
Wherein, also comprise before the described collection user profile:
According to the early warning rule user profile is classified, and the corresponding relation with risk class of setting user information.
Wherein, the described corresponding relation that sets user information with risk class specifically comprises:
According to the early warning rule user profile is classified, obtain the variation of coding rule automatically, for every category information adds classifying and numbering;
Be divided into a plurality of grades, the corresponding mark section of each grade is for every category information is provided with corresponding fractional value.
Wherein, the channel that obtains of described user profile comprises following one or more:
National governmental agencies: comprise industry and commerce, the tax, law court, civil, financial, public security, criminal;
Vicarial unit: comprise national grid, Running-water Company, electricity consumption office, Gas Company, private detective, functions and powers of the state office, credit inquiry and appraisal agency, trade market, communication common carrier.
Wherein, the obtain manner of described user profile comprises following one or more:
Data importing, interconnected system behavior and record, third party's channel information under the line that transaction evaluation of estimating mutually between user's regular job behavior, user's loan transaction associative operation, member, being correlated with and calling information, loan transaction flow state, link integrity viability state, bank are correlated with.
The present invention also provides early warning system in a kind of loan, comprising:
Information acquisition module is used for gathering user profile according to the user in the sign of database;
Risk class is provided with module, is used for the user is divided into a plurality of grades, and the corresponding mark section of each grade, corresponding one of each mark section triggers flow process;
Processing module is used for according to described triggering flow performing corresponding operating.
Wherein, early warning system also comprises in the loan:
The information classification module is connected with described information acquisition module, is used for the user profile classification, and the variation of obtaining coding rule automatically for every category information adds classifying and numbering, is stored user profile and its corresponding Customs Assigned Number one into customer data base.
Wherein, described processing module specifically comprises:
Trigger submodule, be used for triggering automatically corresponding notification module and flow processing module;
The notice submodule is used to be provided with notice masterplate and content, reads the contact method of respective contacts automatically, and the masterplate content is sent to corresponding contact person automatically;
The flow processing submodule is used to read user's details and exports to the result district, and with notification module and trigger module infobit state synchronized, response is also carried out the alignment processing flow process.
Wherein, described processing module also comprises:
Analyze submodule, be used for user profile with the graduation of user behavior curve, and being updated to customer data base, automatic request trigger module when reaching regular grade with the different derived curve figure of classification form.
Wherein, early warning system also comprises in the described loan:
Can expand the associated interface module, be connected with described information acquisition module, be used for obtaining automatically success status and integrality with comparison information, initiate request automatically under imperfect and status of fail, obtain again, success status sends feedback.
Wherein, early warning system also comprises in the described loan:
The manually-operated backstage is connected with the described associated interface module of expanding, and is used to set several keepers and distributes authority, and user's information is increased and editor.
Wherein, early warning system also comprises in the described loan:
Self-defined modification and expansion module are connected with described manually-operated backstage, are used for can adjusting, increase newly, delete, adjust grade and setting to the parameter inside all functions module of early warning system.
Compared with prior art, the present invention has the following advantages:
Among the present invention, enterprise is mapped to enterprise's capital management situation at the application and the management position of ecommerce, and be converted to finance and business targets, by instant data collection, the assessment of operation situation, the transmission of key elements such as economic information collection, form interaction with the borrower, and the money-lender is carried out uninterrupted on-line monitoring in 24 hours by data monitoring, by being connected with third-party cooperation and system interface, obtaining immediately of realization information, in time, analyzed, in time handle, with low cost, fast, scientific analysis, alignment processing is divided into a plurality of grades pond with the mode classification of science with the user, take corresponding processing mode at dissimilar users, realize the full maintenance and the monitoring of user library, the credit risk that reduction can be accumulated reduces bank and loan related side's cost, risk, loss.
Description of drawings
Fig. 1 is an early warning system overall network synoptic diagram in a kind of loan in the embodiment of the invention one;
Fig. 2 is an early warning system concrete structure synoptic diagram in a kind of loan in the embodiment of the invention two;
Fig. 3 is a method for early warning process flow diagram in a kind of loan in the embodiment of the invention three.
Embodiment
Among the present invention, supervisory user during providing a loan loan and the use of the every function of ecommerce is detailed and management state, E-business applications situation; The behavior of supervisory user during providing a loan includes but not limited to behavior under online operation and the line; All behaviors that the user touched are followed the tracks of, and the result that may cause bad refund is made early warning; To all kinds of early warning classification and ordination as a result, and in time notify the related side to follow up accordingly and handle; Omnibearing data aggregation is carried out in the behavior that associated user can touch, and updates to the data of this user in early warning system; Early warning system is divided into a plurality of grades, each grade has a mark section, conclude different grade the inside according to the significance level difference of various information, and according to weight each category information is done the mark standard, flexibly bonus point or subtract branch in each grade the inside; Timely and platform information data bank is carried out Data Update, and timely and banking system is carried out Data Update, allows all related sides obtain user's advanced warning grade and situation the very first time, and triggers treatment scheme.
Below in conjunction with drawings and Examples, the specific embodiment of the present invention is described in further detail:
The integrated environment that early warning system is used in the loan of the present invention comprises customer access equipment, processing platform and banking system as shown in Figure 1.Wherein, customer access equipment comprises: regular job module, with loan associative operation module, at the 3rd room behavior record module and relevant information feedback module; Processing platform comprises: early warning system and database in information gathering module, the loan; Banking system comprises: information is accepted module and is handled the feedback result module.
Information gathering module in the processing platform is obtained daily information of user and user data model information in real time or regularly from the regular job module; And pass through the first associated interface module in real time or regularly from collecting user profile in third party's behavior record module and relevant information feedback module.The information gathering module sends to early warning system in the loan with the user profile of collecting, and early warning system and is accepted module by the information that second associated interface sends to banking system by obtaining early warning information with the database interactive information in the loan.After banking system is carried out respective handling according to this early warning information to this user, result is returned to early warning system in the loan, carry out record by handling the feedback result module.
Wherein, the daily information of user comprises: because the user need regularly finish uploading of data, when the user does not in time finish the required information that triggers when moving, for example the user's loan transaction associative operation uploaded; Supervise mutually between enterprise and timely evaluation information, comprise between enterprise, behavior etc. on the service platform, bank, line and under the line; User Violations information, for example loan transaction flow state, sincere viability state; Behavior trace information on the subscribers feeder, for example logical online, the enterprise's data modification of trade, transaction and relevant evaluation etc.; The third-party institution is acquired information, and for example the information of third party's channel and trend analysis curve map, user are at third-party behavior and information record etc.; The manpower follow-up information of the behavior record information in the sorts of systems in association, attendant's contact, user have taked certain action or have carried out the information of certain behavior, the channel that can relate to user behavior and information and content thereof.User behavior or interests association person investigate information, comprise the passive acceptance investigation of affiliate, inquiry of loan enterprises etc., and to the investigation of above-mentioned unit, for example user's financial information, user's performance information, user's purchase cost information.
Wherein comprise in the user data model information: member ID, loan name of product and numbering, loan began and by the time, the data completeness of corresponding loan time, behavior fitness on the subscribers feeder, the behavior of non-user's direct control, operation behavior on the subscribers feeder, sincere state is (normal, be about to renew, do not renew), third party's information, interconnected system information, the loan status completeness is (normal, be about to expire, exceed the time limit, repaying exceeds the time limit, malice is not repaid), the high-risk mark of user etc.
Add up every minute weight and by a minute numeral system according to the user data model information, mark is high more, and the treatment measures of taking are strong more.Alignment processing: mark is divided into 5 sections, and mark high-risk degree more is strong more.Set up 5 early warning ponds on the backstage, when user's mark reached early warning pond mark, user data entered corresponding early warning pond automatically.0-10 (normally), 11-30 are (in violation of rules and regulations, pay close attention to and also to notify client and bank), 31-60 (in violation of rules and regulations or be about to repay, show great attention to and put on record and notifying bank, the client drawn in high-risk), 61-80 (repays, notifying bank demands by force, special messenger's tracking), 81-100 (malice is not repaid, and bank's relevant law is handled, and network is closed down).
Wherein, normal: as not carry out any tracking and handle; In violation of rules and regulations: mail, assistant's untill further notice client and the enterprise that links, enterprise's data transmission is given bank, is labeled as low dangerous.High-risk: mail, trade are logical, note, assistant's untill further notice user and the enterprise that links to each other, remind the user to finish or handle (comprising the clarification of customer complaint etc.) associative operation as early as possible, attendant's phone begins follow-up, 1 time weekly, phone is reminded the enterprise that once links to each other, and tracking results branch numeral system recorded user data the inside, and can bonus point also can subtract branch, attendant's mark overall operation upper and lower limit is 10 minutes.Give bank with enterprise's data transmission, be labeled as high-risk.
Normally refund: mail, trade are logical, note, E-fax, assistant are notified the client and the enterprise that links; remind the user to finish or handle (comprising the clarification of customer complaint etc.) associative operation as early as possible; attendant's phone begins follow-up; 3 times weekly; phone is reminded 1 continuous enterprise; and tracking results branch numeral system recorded user data the inside, and can bonus point also can subtract branch, attendant's mark overall operation upper and lower limit is 20 minutes.Give bank with enterprise's data transmission, be labeled as follow-up immediately.
Malice is not refunded: the mail notification client and the enterprise that links, the result state (part is demanded, fully demanded, and can't demand) of mail, reception bank adds, subtracts branch to user's data.Then start the contract treatment scheme if can't demand.
Early warning system comprises as shown in Figure 2 in the loan:
Customer data base, for each user data is set up unique numbering, this is numbered system's numbering, does not show at the page; Storage user's details add related the connection to corresponding information; Respective file is that rule is set up branch's serial number with the beginning of user's unique number, and is associated with the numbering of respective user; Information classification is retrieved and is accessed, and information is pressed the field name classification and shown that system can search for generally and call by field contents; Log record, information are by each storage and access action and write log recording table; Automated back-up according to BACKUP TIME of freely setting and provisional backup request, with the preservation of compressed package, and can import the backup compressed package.
Information acquisition module is in time gathered on the information channel and seizure user profile according to user's being identified in database, will add Customs Assigned Number after the numbering association of this user profile according to the user; And verification integrality and success status, under imperfect and status of fail, initiate request automatically, obtain again to customer access equipment, success status sends feedback.
The information classification module is classified user profile according to the early warning rule, obtains the variation of coding rule automatically, for every category information adds classifying and numbering, stores user profile and its corresponding Customs Assigned Number one into customer data base.
The early warning rule module is divided into a plurality of grades (for example 5), and grade can be adjusted by the backstage; The fractional value rule, the corresponding mark section of each grade, the mark section can be adjusted by the backstage; Every category information is provided with corresponding fractional value, and fractional value can be adjusted by the backstage; Grade triggers, and every class hierarchy can the multiselect trigger condition, and condition can be selected by the backstage.
Can expand the associated interface module, obtain success status and integrality with comparison information automatically, initiate request automatically under imperfect and status of fail, obtain again, success status sends feedback; Reversible encryption and digital signature; Can increase, revise, delete its encrypted form, IP address, data source, MAC Address newly.
Grade and setting can be adjusted, be increased newly, delete, adjust to self-defined modification and expansion module to the parameter inside all functions module of early warning system.
Trigger module triggers corresponding notification module and flow processing module automatically according to the early warning rule.
Notification module is provided with notice masterplate and content, according to the grade separation of early warning rule; Automatically read the contact method of respective contacts, and the masterplate content is sent automatically, mode comprises that mail, note, trade are logical, website, E-FAX, assistant, system alert etc.
The flow processing module reads user's details and exports to the result district; With notification module and trigger module infobit state synchronized; Response is also carried out the alignment processing flow process.
Analysis module, with user profile with the different derived curve figure of classification form; According to the early warning rule user behavior curve is classified, and be updated to customer data base; Automatic request trigger module when reaching regular grade.
The manually-operated backstage can be set several keepers and distribute authority; The operator has unique number, writes down its numbering and MAC Address, IP when carrying out all operations, and records system journal; The IP segment protect can be revised its IP address, can operate in this IP section, and non-IP prompting makes mistakes; Can increase user's information and editor; Can adjust and revise all kinds of expansion modules; Can freely inquire about, derive various information and data.
The present invention also provides method for early warning in a kind of loan, as shown in Figure 3, may further comprise the steps:
Step s101 classifies user profile according to the early warning rule, and the corresponding relation with risk class of setting user information.Specifically comprise: according to the early warning rule user profile is classified, obtain the variation of coding rule automatically,, store user profile and its corresponding Customs Assigned Number one into customer data base for every category information adds classifying and numbering; Be divided into a plurality of grades, the corresponding mark section of each grade, every category information is provided with corresponding fractional value.
Step s102 gathers user profile, will add Customs Assigned Number after the numbering association of this user profile according to the user.Described completeness of user information of verification and success status are initiated request to described customer access equipment and are obtained again under imperfect and status of fail.Wherein, the channel that obtains of described user profile comprises following one or more: national governmental agencies: comprise industry and commerce, the tax, law court, civil, financial, public security, criminal; Vicarial unit: comprise national grid, Running-water Company, electricity consumption office, Gas Company, private detective, functions and powers of the state office, credit inquiry and appraisal agency, trade market, communication common carrier.The obtain manner of described user profile comprises following one or more: under the line that estimate mutually between user's regular job behavior, user's loan transaction associative operation, member, relevant transaction evaluation and calling information, loan transaction flow state, link integrity viability state, bank is relevant data import, interconnected system behavior and record, third party's channel information.
Step s103 determines described user's risk class according to the corresponding relation of described user profile and user profile and risk class.Be divided into a plurality of grades (for example 5), grade can be adjusted by the backstage; The fractional value rule, the corresponding mark section of each grade, the mark section can be adjusted by the backstage; Every category information is provided with corresponding fractional value, and fractional value can be adjusted by the backstage; Grade triggers, and every class hierarchy can the multiselect trigger condition, and condition can be selected by the backstage.
Step s104 triggers corresponding flow process according to described user's risk class.Specifically comprise: trigger corresponding notification module and flow processing module automatically according to the early warning rule.By notification module notice masterplate and content are set, grade separation according to the early warning rule, automatically read the contact method of respective contacts, and the masterplate content is sent automatically, mode comprises that mail, note, trade are logical, website, E-FAX, assistant, system alert etc.Read user's details and export to the result district by the flow processing module, and with notification module and trigger module infobit state synchronized, response alignment processing flow process.
In the loan core of early warning system be behind all related informations that can obtain with enterprise and respective user synchronously and in time trigger treatment scheme behind the scientific classification in time, can related a plurality of systems and platform, obtain all related informations with enterprise and respective user, and user's information distinguished by the notion of grade section, can realize all kinds of trickle accumulations of risks, the processing of grade section does not cause interference to the user, and system and related side are not caused realization pressure.
The user is on network after the apply for loan, timely this user of understanding is in the operating position of providing a loan between the operating period after the information acquisition of early warning system by the record of the information on the line and third party's class, whether observe this loan normal, observe the responsibility that whether normal online transaction situation, enterprise and the corporate boss of credit record, the enterprise of this user utilization of a loan, enterprise management condition, corporate boss's credit record, enterprise should fulfil, be associated with the sorts of systems that the user can touch, and its behavior and data are carried out bringing early warning system into after taxonomic revision and the collection.
The user carries out all kinds of associative operations on the net, transaction, the related side is to its evaluation of making, complain, information such as arbitration all are updated to this user's information record the inside timely, the information updating that also can admit third-party information or will manually collect comprises industry and commerce to this user's credit record the inside approach, the tax, law court, civil, finance, public security, criminal, etc. national governmental agencies, or vicarial unit, include but not limited to national grid, Running-water Company, electricity consumption office, Gas Company, the private detective, functions and powers of the state office, credit inquiry and appraisal agency, the trade market, third party focal pointes such as communication common carrier.User profile in the early warning system server has uniqueness, permanent, can obtain this user's information by interface and any system docking, manually can examine and handle its information.
Wherein, enterprise's relevant information and the channel monitored, as shown in table 1, user behavior and related information are as shown in table 2.
Table 1: company information
Table 2: user behavior and related information:
Through the above description of the embodiments, those skilled in the art can be well understood to the present invention and can realize by the mode that software adds essential general hardware platform, can certainly pass through hardware, but the former is better embodiment under a lot of situation.Based on such understanding, the part that technical scheme of the present invention contributes to prior art in essence in other words can embody with the form of software product, this obtains the machine software product and is stored in the storage medium, comprises that some instructions are used so that the network equipment is carried out the described method of each embodiment of the present invention.
More than disclosed only be several specific embodiment of the present invention, still, the present invention is not limited thereto, any those skilled in the art can think variation all should fall into protection scope of the present invention.
Claims (13)
1, method for early warning in a kind of loan is characterized in that, may further comprise the steps:
Gather user profile according to the sign of user in database;
Determine described user's risk class according to the corresponding relation of described user profile and user profile and risk class;
Risk class according to described user triggers corresponding flow process.
2, borrow according to claim 1 in method for early warning, it is characterized in that, also comprise after the described collection user profile:
Described completeness of user information of verification and success status are initiated request to described user and are obtained user profile again under imperfect and status of fail.
3, borrow according to claim 1 in method for early warning, it is characterized in that, also comprise before the described collection user profile:
According to the early warning rule user profile is classified, and the corresponding relation with risk class of setting user information.
4, borrow according to claim 1 in method for early warning, it is characterized in that the described corresponding relation that sets user information with risk class specifically comprises:
According to the early warning rule user profile is classified, obtain the variation of coding rule automatically, for every category information adds classifying and numbering;
Be divided into a plurality of grades, the corresponding mark section of each grade is for every category information is provided with corresponding fractional value.
5, borrow according to claim 1 in method for early warning, it is characterized in that the channel that obtains of described user profile comprises following one or more:
National governmental agencies: comprise industry and commerce, the tax, law court, civil, financial, public security, criminal;
Vicarial unit: comprise national grid, Running-water Company, electricity consumption office, Gas Company, private detective, functions and powers of the state office, credit inquiry and appraisal agency, trade market, communication common carrier.
6, borrow according to claim 1 in method for early warning, it is characterized in that the obtain manner of described user profile comprises following one or more:
Data importing, interconnected system behavior and record, third party's channel information under the line that transaction evaluation of estimating mutually between user's regular job behavior, user's loan transaction associative operation, member, being correlated with and calling information, loan transaction flow state, link integrity viability state, bank are correlated with.
7, early warning system in a kind of loan is characterized in that, comprising:
Information acquisition module is used for gathering user profile according to the user in the sign of database;
Risk class is provided with module, is used for the user is divided into a plurality of grades, and the corresponding mark section of each grade, corresponding one of each mark section triggers flow process;
Processing module is used for according to described triggering flow performing corresponding operating.
8, as early warning system in the loan as described in the claim 7, it is characterized in that early warning system also comprises in the loan:
The information classification module is connected with described information acquisition module, is used for the user profile classification, and the variation of obtaining coding rule automatically for every category information adds classifying and numbering, is stored user profile and its corresponding Customs Assigned Number one into customer data base.
9, as early warning system in the loan as described in the claim 7, it is characterized in that described processing module specifically comprises:
Trigger submodule, be used for triggering automatically corresponding notification module and flow processing module;
The notice submodule is used to be provided with notice masterplate and content, reads the contact method of respective contacts automatically, and the masterplate content is sent to corresponding contact person automatically;
The flow processing submodule is used to read user's details and exports to the result district, and with notification module and trigger module infobit state synchronized, response is also carried out the alignment processing flow process.
10, as early warning system in the loan as described in the claim 9, it is characterized in that described processing module also comprises:
Analyze submodule, be used for user profile with the graduation of user behavior curve, and being updated to customer data base, automatic request trigger module when reaching regular grade with the different derived curve figure of classification form.
11, as early warning system in the loan as described in the claim 9, it is characterized in that early warning system also comprises in the described loan:
Can expand the associated interface module, be connected with described information acquisition module, be used for obtaining automatically success status and integrality with comparison information, initiate request automatically under imperfect and status of fail, obtain again, success status sends feedback.
12, as early warning system in the loan as described in the claim 9, it is characterized in that early warning system also comprises in the described loan:
The manually-operated backstage is connected with the described associated interface module of expanding, and is used to set several keepers and distributes authority, and user's information is increased and editor.
13, as early warning system in the loan as described in the claim 12, it is characterized in that early warning system also comprises in the described loan:
Self-defined modification and expansion module are connected with described manually-operated backstage, are used for can adjusting, increase newly, delete, adjust grade and setting to the parameter inside all functions module of early warning system.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CNA200710301989XA CN101470887A (en) | 2007-12-24 | 2007-12-24 | Credit early-warning system and method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CNA200710301989XA CN101470887A (en) | 2007-12-24 | 2007-12-24 | Credit early-warning system and method |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN101470887A true CN101470887A (en) | 2009-07-01 |
Family
ID=40828341
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CNA200710301989XA Pending CN101470887A (en) | 2007-12-24 | 2007-12-24 | Credit early-warning system and method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN101470887A (en) |
Cited By (34)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103020268A (en) * | 2012-12-26 | 2013-04-03 | 大唐软件技术股份有限公司 | Serial number applying method and system of relational database |
| CN103123712A (en) * | 2011-11-17 | 2013-05-29 | 阿里巴巴集团控股有限公司 | Method and system for monitoring network behavior data |
| CN103218742A (en) * | 2013-01-30 | 2013-07-24 | 北京税恒科技有限公司 | Enterprise tax risk early warning platform |
| CN104680415A (en) * | 2013-11-28 | 2015-06-03 | 富士通株式会社 | Apparatus, method and system |
| CN104992264A (en) * | 2015-06-01 | 2015-10-21 | 康玉龙 | Enterprise operation condition real time monitoring system |
| CN105447754A (en) * | 2015-12-10 | 2016-03-30 | 四川长虹电器股份有限公司 | Secure encryption protection-based lending system and method in social form |
| CN105740434A (en) * | 2016-02-01 | 2016-07-06 | 腾讯科技（深圳）有限公司 | Network information scoring method and device |
| CN105976236A (en) * | 2016-04-28 | 2016-09-28 | 中国建设银行股份有限公司 | Loan transaction monitoring early warning method and apparatus thereof |
| CN106101092A (en) * | 2016-06-07 | 2016-11-09 | 腾讯科技（深圳）有限公司 | A kind of information evaluation processing method and first instance |
| CN106339942A (en) * | 2016-08-31 | 2017-01-18 | 国信优易数据有限公司 | Financial information processing method and system |
| CN106910078A (en) * | 2015-12-22 | 2017-06-30 | 阿里巴巴集团控股有限公司 | Risk identification method and device |
| CN107169860A (en) * | 2016-12-30 | 2017-09-15 | 中国建设银行股份有限公司 | A kind of method for prewarning risk and device |
| CN107230152A (en) * | 2016-03-24 | 2017-10-03 | 平安科技（深圳）有限公司 | Declaration form renews the based reminding method and device of charge |
| CN107240020A (en) * | 2016-03-28 | 2017-10-10 | 平安科技（深圳）有限公司 | Insurance accepts the risk monitoring and control method and apparatus of information |
| CN107886207A (en) * | 2016-09-28 | 2018-04-06 | 陈艮珍 | A kind of business finance monitoring system and its monitoring method |
| CN108305163A (en) * | 2017-12-20 | 2018-07-20 | 上海财安金融服务集团股份有限公司 | The credit method for early warning and system in feature based library |
| CN108416506A (en) * | 2018-02-07 | 2018-08-17 | 平安科技（深圳）有限公司 | Customer risk level management approach, server and computer readable storage medium |
| CN108805391A (en) * | 2018-04-12 | 2018-11-13 | 阿里巴巴集团控股有限公司 | Determine the method and device of high risk user |
| CN108876597A (en) * | 2018-06-20 | 2018-11-23 | 上海量斗物联网科技有限公司 | Financial integration application platform based on Beidou and the safe Internet of Things of quantum |
| CN109003117A (en) * | 2018-06-14 | 2018-12-14 | 万翼科技有限公司 | Generation method, device and the computer readable storage medium of questionnaire |
| CN109003182A (en) * | 2018-06-05 | 2018-12-14 | 东方银谷（北京）投资管理有限公司 | Data processing method and device for risk assessment |
| CN109034995A (en) * | 2017-06-08 | 2018-12-18 | 张文 | The method and apparatus for carrying out finance activities using Internet service platform |
| CN109190954A (en) * | 2018-08-22 | 2019-01-11 | 深圳合纵能源技术有限公司 | Method based on real-time electricity consumption data assessment enterprise production and operation management risk |
| CN109190917A (en) * | 2018-08-09 | 2019-01-11 | 厦门市七星通联科技有限公司 | A kind of risk control method and system of fiduciary loan |
| CN109214908A (en) * | 2018-07-06 | 2019-01-15 | 深圳市买买提信息科技有限公司 | A kind of monitoring method and relevant apparatus |
| CN109214917A (en) * | 2018-11-07 | 2019-01-15 | 深圳行知聚能科技发展有限公司 | A kind of credit risk real-time monitoring system and method |
| CN109214915A (en) * | 2018-09-06 | 2019-01-15 | 江西汉辰金融科技集团有限公司 | Borrow risk methods of marking, system and computer readable storage medium |
| CN109409900A (en) * | 2018-01-26 | 2019-03-01 | 深圳市买买提信息科技有限公司 | A kind of trade company's checking method and server |
| CN110019547A (en) * | 2017-11-10 | 2019-07-16 | 平安普惠企业管理有限公司 | Obtain method, apparatus, equipment and the medium of the incidence relation between client |
| CN111861716A (en) * | 2020-07-23 | 2020-10-30 | 北京睿知图远科技有限公司 | Method for generating monitoring early warning level in credit based on software system |
| CN112150270A (en) * | 2020-09-18 | 2020-12-29 | 中国建设银行股份有限公司 | Method, device, equipment and computer readable medium for monitoring vehicle information |
| CN112419008A (en) * | 2020-12-09 | 2021-02-26 | 中国建设银行股份有限公司 | Automatic grading early warning method and device, electronic equipment and storage medium |
| CN113450200A (en) * | 2020-03-25 | 2021-09-28 | 上海欧冶金融信息服务股份有限公司 | Multi-level interactive risk early warning system |
| CN113822679A (en) * | 2021-11-24 | 2021-12-21 | 四川新网银行股份有限公司 | Intelligent anti-fraud loan management system and method with automatic decision making function |
-
2007
- 2007-12-24 CN CNA200710301989XA patent/CN101470887A/en active Pending
Cited By (37)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107103548A (en) * | 2011-11-17 | 2017-08-29 | 阿里巴巴集团控股有限公司 | The monitoring method and system and risk monitoring and control method and system of network behavior data |
| CN103123712A (en) * | 2011-11-17 | 2013-05-29 | 阿里巴巴集团控股有限公司 | Method and system for monitoring network behavior data |
| CN103020268B (en) * | 2012-12-26 | 2016-05-04 | 大唐软件技术股份有限公司 | Relevant database sequence number application process and system |
| CN103020268A (en) * | 2012-12-26 | 2013-04-03 | 大唐软件技术股份有限公司 | Serial number applying method and system of relational database |
| CN103218742A (en) * | 2013-01-30 | 2013-07-24 | 北京税恒科技有限公司 | Enterprise tax risk early warning platform |
| CN104680415A (en) * | 2013-11-28 | 2015-06-03 | 富士通株式会社 | Apparatus, method and system |
| CN104992264A (en) * | 2015-06-01 | 2015-10-21 | 康玉龙 | Enterprise operation condition real time monitoring system |
| CN105447754A (en) * | 2015-12-10 | 2016-03-30 | 四川长虹电器股份有限公司 | Secure encryption protection-based lending system and method in social form |
| CN106910078A (en) * | 2015-12-22 | 2017-06-30 | 阿里巴巴集团控股有限公司 | Risk identification method and device |
| CN105740434A (en) * | 2016-02-01 | 2016-07-06 | 腾讯科技（深圳）有限公司 | Network information scoring method and device |
| CN105740434B (en) * | 2016-02-01 | 2019-05-28 | 腾讯科技（深圳）有限公司 | Network information methods of marking and device |
| CN107230152A (en) * | 2016-03-24 | 2017-10-03 | 平安科技（深圳）有限公司 | Declaration form renews the based reminding method and device of charge |
| CN107240020A (en) * | 2016-03-28 | 2017-10-10 | 平安科技（深圳）有限公司 | Insurance accepts the risk monitoring and control method and apparatus of information |
| CN105976236A (en) * | 2016-04-28 | 2016-09-28 | 中国建设银行股份有限公司 | Loan transaction monitoring early warning method and apparatus thereof |
| CN106101092A (en) * | 2016-06-07 | 2016-11-09 | 腾讯科技（深圳）有限公司 | A kind of information evaluation processing method and first instance |
| CN106339942A (en) * | 2016-08-31 | 2017-01-18 | 国信优易数据有限公司 | Financial information processing method and system |
| CN107886207A (en) * | 2016-09-28 | 2018-04-06 | 陈艮珍 | A kind of business finance monitoring system and its monitoring method |
| CN107169860A (en) * | 2016-12-30 | 2017-09-15 | 中国建设银行股份有限公司 | A kind of method for prewarning risk and device |
| CN109034995A (en) * | 2017-06-08 | 2018-12-18 | 张文 | The method and apparatus for carrying out finance activities using Internet service platform |
| CN110019547A (en) * | 2017-11-10 | 2019-07-16 | 平安普惠企业管理有限公司 | Obtain method, apparatus, equipment and the medium of the incidence relation between client |
| CN108305163A (en) * | 2017-12-20 | 2018-07-20 | 上海财安金融服务集团股份有限公司 | The credit method for early warning and system in feature based library |
| CN109409900A (en) * | 2018-01-26 | 2019-03-01 | 深圳市买买提信息科技有限公司 | A kind of trade company's checking method and server |
| CN108416506A (en) * | 2018-02-07 | 2018-08-17 | 平安科技（深圳）有限公司 | Customer risk level management approach, server and computer readable storage medium |
| CN108805391A (en) * | 2018-04-12 | 2018-11-13 | 阿里巴巴集团控股有限公司 | Determine the method and device of high risk user |
| CN109003182A (en) * | 2018-06-05 | 2018-12-14 | 东方银谷（北京）投资管理有限公司 | Data processing method and device for risk assessment |
| CN109003117A (en) * | 2018-06-14 | 2018-12-14 | 万翼科技有限公司 | Generation method, device and the computer readable storage medium of questionnaire |
| CN108876597A (en) * | 2018-06-20 | 2018-11-23 | 上海量斗物联网科技有限公司 | Financial integration application platform based on Beidou and the safe Internet of Things of quantum |
| CN109214908A (en) * | 2018-07-06 | 2019-01-15 | 深圳市买买提信息科技有限公司 | A kind of monitoring method and relevant apparatus |
| CN109190917A (en) * | 2018-08-09 | 2019-01-11 | 厦门市七星通联科技有限公司 | A kind of risk control method and system of fiduciary loan |
| CN109190954A (en) * | 2018-08-22 | 2019-01-11 | 深圳合纵能源技术有限公司 | Method based on real-time electricity consumption data assessment enterprise production and operation management risk |
| CN109214915A (en) * | 2018-09-06 | 2019-01-15 | 江西汉辰金融科技集团有限公司 | Borrow risk methods of marking, system and computer readable storage medium |
| CN109214917A (en) * | 2018-11-07 | 2019-01-15 | 深圳行知聚能科技发展有限公司 | A kind of credit risk real-time monitoring system and method |
| CN113450200A (en) * | 2020-03-25 | 2021-09-28 | 上海欧冶金融信息服务股份有限公司 | Multi-level interactive risk early warning system |
| CN111861716A (en) * | 2020-07-23 | 2020-10-30 | 北京睿知图远科技有限公司 | Method for generating monitoring early warning level in credit based on software system |
| CN112150270A (en) * | 2020-09-18 | 2020-12-29 | 中国建设银行股份有限公司 | Method, device, equipment and computer readable medium for monitoring vehicle information |
| CN112419008A (en) * | 2020-12-09 | 2021-02-26 | 中国建设银行股份有限公司 | Automatic grading early warning method and device, electronic equipment and storage medium |
| CN113822679A (en) * | 2021-11-24 | 2021-12-21 | 四川新网银行股份有限公司 | Intelligent anti-fraud loan management system and method with automatic decision making function |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN101470887A (en) | Credit early-warning system and method | |
| CN112241924B (en) | Wisdom gas system | |
| Kuhn et al. | Learning from WorldCom: Implications for fraud detection through continuous assurance | |
| US8504456B2 (en) | Behavioral baseline scoring and risk scoring | |
| US20070226095A1 (en) | Method for generating predictive models for a business problem via supervised learning | |
| CN104408575A (en) | Enterprise operation data management system and method | |
| CN111415067A (en) | Enterprise and personal credit rating system | |
| KR101730474B1 (en) | System for Private Property Management Application | |
| CN109919667A (en) | A kind of method and apparatus of the IP of enterprise for identification | |
| CN203414995U (en) | Land use tax payment checking managing system | |
| CN116991839A (en) | Cross-region financial cloud processing method based on enterprise operation layout | |
| KR20210155501A (en) | Receivable recovery support system for medium-small enterprise account receivable bond decrease and bad debt prevention based on big data | |
| Xie et al. | A big data technique for internet financial risk control | |
| CN103164753A (en) | Customer transaction data management system | |
| CN110245814A (en) | Risk Supervision method, apparatus, storage medium and electronic equipment | |
| CN115442677A (en) | Water affair marketing wisdom management system | |
| CN115131117A (en) | Tax inspection case analysis and early warning method and system by analyzing tax data | |
| CN114358439A (en) | Wisdom supervisory systems | |
| CN114254908A (en) | Risk perception and supervision platform for regional financial non-bank financial institution | |
| CN111626703A (en) | Event-recording accounting counting project management system based on item form | |
| Ibrahim et al. | Fraud management system in detecting fraud in cellular telephone networks | |
| CN117474640B (en) | Deposit-free leasing device and method | |
| CN102044048A (en) | Comprehensive credit granting business treatment method based on credit checking and granting business system | |
| CN102081785A (en) | Credit reporting and providing service system based service processing method after credit providing | |
| CN112396426A (en) | Cross-bank payment limit monitoring method, system and computer storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| REG | Reference to a national code |
Ref country code: HK Ref legal event code: DE Ref document number: 1132073 Country of ref document: HK |
|
| C12 | Rejection of a patent application after its publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20090701 |
|
| REG | Reference to a national code |
Ref country code: HK Ref legal event code: WD Ref document number: 1132073 Country of ref document: HK |