CN113077339A - Method for constructing intelligent fund routing model - Google Patents
Method for constructing intelligent fund routing model Download PDFInfo
- Publication number
- CN113077339A CN113077339A CN202110621959.7A CN202110621959A CN113077339A CN 113077339 A CN113077339 A CN 113077339A CN 202110621959 A CN202110621959 A CN 202110621959A CN 113077339 A CN113077339 A CN 113077339A
- Authority
- CN
- China
- Prior art keywords
- loan
- daily
- transaction
- cooperation
- cooperative
- 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
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
- G06Q40/03—Credit; Loans; Processing thereof
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Data Mining & Analysis (AREA)
- Business, Economics & Management (AREA)
- Theoretical Computer Science (AREA)
- Finance (AREA)
- Accounting & Taxation (AREA)
- Mathematical Physics (AREA)
- Pure & Applied Mathematics (AREA)
- Mathematical Optimization (AREA)
- Mathematical Analysis (AREA)
- Computational Mathematics (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Probability & Statistics with Applications (AREA)
- Bioinformatics & Computational Biology (AREA)
- General Business, Economics & Management (AREA)
- Technology Law (AREA)
- Evolutionary Biology (AREA)
- Strategic Management (AREA)
- Marketing (AREA)
- Operations Research (AREA)
- Life Sciences & Earth Sciences (AREA)
- Economics (AREA)
- Algebra (AREA)
- Development Economics (AREA)
- Databases & Information Systems (AREA)
- Software Systems (AREA)
- General Engineering & Computer Science (AREA)
- Financial Or Insurance-Related Operations Such As Payment And Settlement (AREA)
Abstract
The invention relates to the field of joint loan, in particular to a method for solving the routing of joint loan funds based on the Internet. The method is mainly characterized in that a fund routing data model is built, a dynamic routing configuration rule is generated, fusing and current limiting of system interaction of the cooperative mechanism are automatically carried out, the complexity of system maintenance is reduced, and fund use income of the cooperative mechanism is improved. The main scheme comprises the following steps: dynamically loading intelligent fund routing rules stored in a database by the joint loan management system node; step 2: the combined loan management system reads the intelligent fund routing rule data in the database and obtains a specific execution rule after analysis, and the combined loan management system sends a loan request of the property platform to the cooperative institution system according to the execution rule.
Description
Technical Field
The invention relates to the field of joint loan, in particular to a method for solving the routing of joint loan funds based on the Internet.
Background
At present, internet banks develop online loan businesses and can be docked with a large number of asset platforms and cooperation institutions. The property platform mainly refers to head internet platforms which can provide client traffic and can guide loan application requirements of online clients to financial institutions. When the demand of the loan application (namely, property) of a client is large, the financial institution is required to provide funds with other cooperative institutions for joint loan due to the bottleneck of the property scale of one financial institution. As the financial institution undertakes the tasks of client drainage, preposed wind control and the like in the joint loan business, the financial institution and each cooperative institution separately agree the service rate of each loan business, and the income and the sharing risk of the financial institution are increased by charging the service fee of the business to the cooperative institution. In order to reasonably match assets and funds to develop joint loan service to earn more profits and share risks, a joint loan management system needs to be built to bear the functions of cooperative institution management, agreement management, intelligent fund routing rule management and the like. The cooperative organization management comprises management functions of cooperative organization type configuration, asset platform admission configuration capable of cooperation, cooperative organization fund account configuration and the like. The agreement management refers to agreement management signed by a cooperative institution, and mainly comprises agreement validity period management, agreement limit management and the like. The intelligent fund routing rule is that assets guided by each Internet platform are distributed to each cooperation institution for joint loan through weight configuration and a random number screening function. With the increase of a large number of collaborators, the method of manually adjusting the weight by an operator causes the maintenance cost of the system to be increased, and the aim of optimally utilizing the funds of the collaborators to obtain the maximum profit is difficult to achieve. In addition, because the system of the cooperative mechanism is unstable, the situation that the system is unavailable often occurs, and at this time, an operator needs to adjust the weight urgently to shunt the service traffic of the unavailable cooperative mechanism.
The operator can manually configure the weight proportion according to expert experience rule strategies according to comprehensive consideration of daily fund plans provided by cooperative institutions, daily asset plans provided by asset platforms, loan approval passing rates of the cooperative institutions and capital cost of the cooperative institutions, so that the assets are randomly distributed to the cooperative institutions, and the ultimate aim is to realize maximization of capital income.
Disclosure of Invention
The technical problem to be solved by the proposal is as follows:
in view of this, an object of the present invention is to provide a method and a system for implementing intelligent fund routing, which construct a fund routing data model, generate a dynamic routing configuration rule, and automatically perform fusing and current limiting for system interaction of a partner mechanism, so as to reduce the complexity of system maintenance and improve the fund use benefit of the partner mechanism.
The invention adopts the following technical scheme for realizing the purpose:
an intelligent funds routing method comprising the steps of:
step 1: dynamically loading intelligent fund routing rules stored in a database by the joint loan management system node;
step 2: the combined loan management system reads the intelligent fund routing rule data in the database and obtains a specific execution rule after analysis, and the combined loan management system sends a loan request of the property platform to the cooperative institution system according to the execution rule.
In the above technical solution, step 1 specifically includes the following steps:
step 1.1: data acquisition: when the combined loan management system performs data interaction with the cooperation institution system, the system records loan application information sent to the cooperation institution system by the combined loan management system and loan approval result information returned by the cooperation institution system into a database to obtain an original data set, wherein the information comprises processing time of each loan approval application by each cooperation institution, interval time of callback of the approval result, callback of approval result and rejection reason;
step 1.2: data preprocessing: after the original data set in the database is subjected to missing value processing, abnormal value processing and variable type processing, grouping processing is carried out according to each cooperation institution, the total daily transaction number, the daily approval passing number, the daily approval refusal number and the daily overtime transaction number of each cooperation institution are counted, and the daily loan application number and the daily loan total amount pushed by each home asset platform are counted;
step 1.3: counting the passing rate of each cooperation mechanism in each time period according to an original data set, wherein the daily transaction passing rate of each cooperation mechanism = daily approval passing stroke/total daily transaction stroke, and counting the daily transaction passing rate of each cooperation mechanism asset platform in a nearly one week in a weighted average manner;
step 1.4: the method comprises the following steps of counting average amount of loan transactions of each cooperative property platform according to an original data set, wherein the average amount of loan transactions per day = total amount of loan per day/number of loan applications per day, counting the average amount of loan transactions of a week in a weighted average mode, and obtaining estimated transaction number per day according to a daily release plan of the property platform, wherein the specific formula is as follows: the daily estimated transaction number = daily total loan amount/daily average loan amount;
step 1.5: using a detection program, regularly counting the system throughput TPS of each cooperation mechanism, wherein the upper limit of the daily distribution volume of the fund routing can not exceed the TPS, and ensuring the stable operation of the system;
step 1.6: according to daily fund plan, each cooperative institutionService ratesMeasuring and calculating a daily release plan;
step 1.7: calculating the weight ratio according to the daily transaction passing rate, the average amount of money, the daily estimated transaction number of strokes and the daily release plan;
step 1.8: monitoring the system running condition of the cooperative mechanisms in real time, if the credit application transaction of one cooperative mechanism is overtime or the approval result is not returned, and the number ratio exceeds a preset threshold value, judging that the system of the other side is abnormal, automatically carrying out fusing current limiting operation by the system, and excluding the related cooperative mechanisms from routing configuration; the system sends a detection application transaction to the opposite side system at regular time, if the transaction returns normally, the opposite side system is judged to be recovered to be normal, the corresponding cooperation mechanism is added into the route again, and if the transaction is abnormal, the fusing state is continuously kept.
In the above technical solution, step 2 specifically includes the following steps:
step 2.1: when the asset platform sends a credit application to the combined loan management system, the system screens out a cooperative institution list for distribution according to the weight matching table;
step 2.2: the system generates a random number random [1, s ], the generated random number contains 1 or s, s is equal to the weight sum of the cooperation mechanism list, and the integer is k; taking out a corresponding result according to the value of k, and routing to a corresponding cooperation mechanism;
step 2.3: removing the cooperation mechanism list from the cooperation mechanisms screened in the step 2.2, and repeating the step 2.2 until all the cooperation mechanisms are screened;
step 2.4: interacting with the cooperation mechanism system in sequence according to the screened cooperation mechanism list, and sending loan application transaction;
step 2.5: if the loan approval of a certain cooperative institution is rejected, continuously screening according to the rule, and skipping to the step 2.1;
step 2.6: and when the service data occurs in the abnormal period of the cooperation mechanism system, the system caches the data and restarts the system after the other side system recovers.
Because the invention adopts the technical scheme, the invention has the following beneficial effects:
the invention is a method based on constructing an intelligent fund routing model, and is based on the characteristics of models such as logistic regression and the like, and the indexes of various influence factors are sorted and fused, so that the accuracy of the fund routing model and the robustness of the system are improved. The finally obtained model can be trained and optimized based on historical data, and has good expansibility. The invention automatically performs fusing and current limiting of system interaction of the cooperative mechanism, and aims to reduce the complexity of system maintenance and improve the fund use benefit of the cooperative mechanism.
Detailed Description
In order to facilitate the technical solutions of the present application to be better understood by those skilled in the art, the following detailed description is given with reference to specific examples.
The invention provides an intelligent fund routing method, which comprises the following steps:
step 1: dynamically loading intelligent fund routing rules by the joint loan management system node;
step 2: the system sends a loan request of the property platform to the cooperation institution system according to the rules;
the step 1 specifically comprises the following steps:
step 1.1: data acquisition: collecting relevant data required by a fund route, and generating an original data set, wherein the data comprises processing time of each loan approval application by each cooperation institution, interval time of callback of approval result, callback of approval result and rejection reason;
step 1.2: data preprocessing: after the original data set is subjected to missing value processing, abnormal value processing and variable type processing, grouping processing is carried out according to each cooperation institution, the total daily transaction number, the daily approval passing number, the daily approval refusal number and the daily overtime transaction number of each cooperation institution are counted, and the daily loan application number and the daily loan total amount pushed by each capital and property platform are counted;
step 1.3: counting the passing rate of each cooperation mechanism in each time period according to an original data set, wherein the daily transaction passing rate of each cooperation mechanism = daily approved pass number/total daily transaction number, and counting the daily transaction passing rate of each cooperation mechanism in the last week in a weighted average manner, wherein the passing rate is shown in the following table;
| collaboration framework 1 | Collaboration framework 2 | Collaboration framework 3 | Collaboration framework 4 | |
| Asset platform 1 | 95% | 90% | 81% | 82% |
| Asset platform 2 | 92% | 60% | 26% | 80% |
| Asset platform 3 | 72% | 33% | 80% | 60% |
| Asset platform 4 | 95% | 99% | 95% | 72% |
Step 1.4: the method comprises the following steps of counting average amount of loan transactions of each cooperative property platform according to an original data set, wherein the average amount of loan transactions per day = total amount of loan per day/number of loan applications per day, counting the average amount of loan transactions of a week in a weighted average mode, and obtaining estimated transaction number per day according to a daily release plan of the property platform, wherein the specific formula is as follows: the daily estimated transaction number = daily total loan amount/daily average loan amount;
step 1.5: using a detection program, regularly counting the system throughput TPS of each cooperation mechanism, wherein the upper limit of the daily distribution volume of the fund routing can not exceed the TPS, and ensuring the stable operation of the system;
step 1.6: and (3) calculating a daily release plan according to the daily fund plan and the service rates of all the cooperative organizations, wherein plan examples are shown in the following table:
| delivery total | Collaboration framework 1 | Collaboration framework 2 | Collaboration framework 3 | Collaboration framework 4 | |
| Asset platform 1 | 1000 | 200 | 50 | 500 | 20 |
| Asset platform 2 | 5000 | 3000 | 250 | 0 | 1000 |
| Asset platform 3 | 2000 | 300 | 500 | 90 | 1200 |
| Asset platform 4 | 3500 | 800 | 890 | 2420 |
Step 1.7: the weight ratio is measured and calculated according to the daily transaction passing rate, average amount of money, estimated daily transaction number of strokes and daily release plan, and the sample is shown in the following table:
| collaboration framework 1 | Collaboration framework 2 | Collaboration framework 3 | Collaboration framework 4 | |
| Asset platform 1 | 20% | 90% | 1% | 0% |
| Asset platform 2 | 30% | 0% | 1% | 80% |
| Asset platform 3 | 50% | 0% | 80% | 0% |
| Asset platform 4 | 0% | 10% | 18% | 20% |
Step 1.6: monitoring the system operation condition of the cooperative mechanisms in real time, if the credit application transaction of one cooperative mechanism is overtime or the number of rounds of the approval result is not recalled and the percentage of the number of rounds exceeds a preset threshold (20%) within a specified time (10 minutes), judging that the opposite system is abnormal, automatically carrying out fusing current limiting operation by the system, and excluding the related cooperative mechanisms from route configuration; the system sends a detection application transaction to the opposite side system at regular time (every hour), if the transaction returns normally, the opposite side system is judged to be recovered to be normal, the corresponding cooperation mechanism is added into the route again, and if the transaction is abnormal, the fusing state is continuously kept;
the step 2 specifically comprises the following steps:
step 2.1: when the asset platform sends a credit application to the combined loan management system, the system screens out a cooperative institution list for distribution according to the weight matching table;
step 2.2: the system generates a random number random [1, s ] (the generated random number contains 1 or s, s is equal to the weight sum of the cooperation mechanism list), and the integer is k; taking out a corresponding result according to the value of k, and routing to a corresponding cooperation mechanism;
step 2.3: removing the list of the cooperation mechanisms from the cooperation mechanisms screened in the last step, and repeating the step 2.2 until all the cooperation mechanisms are screened;
step 2.4: interacting with the cooperation mechanism system in sequence according to the screened cooperation mechanism list, and sending loan application transaction;
step 2.5: if the loan approval of a certain cooperative institution is rejected, continuously screening according to the rule, and skipping to the step 2.1;
step 2.6: and when the service data occurs in the abnormal period of the cooperation mechanism system, the system caches the data and restarts the system after the other side system recovers.
Claims (3)
1. A method of constructing an intelligent funds routing model, comprising the steps of:
step 1: dynamically loading intelligent fund routing rules stored in a database by the joint loan management system node;
step 2: the combined loan management system reads the intelligent fund routing rule data in the database and obtains a specific execution rule after analysis, and the combined loan management system sends a loan request of the property platform to the cooperative institution system according to the execution rule.
2. The method for constructing an intelligent fund routing model according to claim 1, wherein step 1 comprises the following steps:
step 1.1: data acquisition: when the combined loan management system performs data interaction with the cooperation mechanism system, the loan application information sent to the cooperation mechanism system by the combined loan management system and the loan approval result information returned by the cooperation mechanism system are recorded in a database to obtain an original data set, wherein the information comprises the processing time of each loan approval application by each cooperation mechanism, the interval time for callback of the approval result, the callback of the approval result and the reason for refusal;
step 1.2: data preprocessing: after the original data set in the database is subjected to missing value processing, abnormal value processing and variable type processing, grouping processing is carried out according to each cooperation institution, the total daily transaction number, the daily approval passing number, the daily approval refusal number and the daily overtime transaction number of each cooperation institution are counted, and the daily loan application number and the daily loan total amount pushed by each home asset platform are counted;
step 1.3: counting the passing rate of each cooperation mechanism in each time period according to an original data set, wherein the daily transaction passing rate of each cooperation mechanism = daily approval passing stroke/total daily transaction stroke, and counting the daily transaction passing rate of each cooperation mechanism asset platform in a nearly one week in a weighted average manner;
step 1.4: the method comprises the following steps of counting average amount of loan transactions of each cooperative property platform according to an original data set, wherein the average amount of loan transactions per day = total amount of loan per day/number of loan applications per day, counting the average amount of loan transactions of a week in a weighted average mode, and obtaining estimated transaction number per day according to a daily release plan of the property platform, wherein the specific formula is as follows: the daily estimated transaction number = daily total loan amount/daily average loan amount;
step 1.5: using a detection program, regularly counting the system throughput TPS of each cooperation mechanism, wherein the upper limit of the daily distribution volume of the fund routing can not exceed the TPS, and ensuring the stable operation of the system;
step 1.6: calculating a daily release plan according to the daily fund plan and the service rates of all the cooperative institutions;
step 1.7: calculating the weight ratio according to the daily transaction passing rate, the average amount of money, the daily estimated transaction number of strokes and the daily release plan;
step 1.8: monitoring the system running condition of the cooperative mechanisms in real time, if the credit application transaction of one cooperative mechanism is overtime or the approval result is not returned, and the number ratio exceeds a preset threshold value, judging that the system of the other side is abnormal, automatically carrying out fusing current limiting operation by the system, and excluding the related cooperative mechanisms from routing configuration; the system sends a detection application transaction to the opposite side system at regular time, if the transaction returns normally, the opposite side system is judged to be recovered to be normal, the corresponding cooperation mechanism is added into the route again, and if the transaction is abnormal, the fusing state is continuously kept.
3. The method for constructing an intelligent fund routing model according to claim 1, wherein step 2 comprises the following steps:
step 2.1: when the asset platform sends a credit application to the combined loan management system, the system screens out a cooperative institution list for distribution according to the weight matching table;
step 2.2: the system generates a random number random [1, s ], the generated random number contains 1 or s, s is equal to the weight sum of the cooperation mechanism list, and the integer is k; taking out a corresponding result according to the value of k, and routing to a corresponding cooperation mechanism;
step 2.3: removing the cooperation mechanism list from the cooperation mechanisms screened in the step 2.2, and repeating the step 2.2 until all the cooperation mechanisms are screened;
step 2.4: interacting with the cooperation mechanism system in sequence according to the screened cooperation mechanism list, and sending loan application transaction;
step 2.5: if the loan approval of a certain cooperative institution is rejected, continuously screening according to the rule, and skipping to the step 2.1;
step 2.6: and when the service data occurs in the abnormal period of the cooperation mechanism system, the system caches the data and restarts the system after the other side system recovers.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110621959.7A CN113077339A (en) | 2021-06-04 | 2021-06-04 | Method for constructing intelligent fund routing model |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110621959.7A CN113077339A (en) | 2021-06-04 | 2021-06-04 | Method for constructing intelligent fund routing model |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113077339A true CN113077339A (en) | 2021-07-06 |
Family
ID=76616978
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110621959.7A Pending CN113077339A (en) | 2021-06-04 | 2021-06-04 | Method for constructing intelligent fund routing model |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113077339A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113807956A (en) * | 2021-11-19 | 2021-12-17 | 北京宇信科技集团股份有限公司 | Data processing method, medium, equipment and system for joint loan |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101097625A (en) * | 2006-06-29 | 2008-01-02 | 中国银联股份有限公司 | Method for enhancing bank card transaction processing system RAS performance and system |
| CN108389123A (en) * | 2018-02-12 | 2018-08-10 | 中科柏诚科技（北京）股份有限公司 | A kind of internet syndicated loan system and method |
| CN109559011A (en) * | 2018-10-16 | 2019-04-02 | 平安普惠企业管理有限公司 | Loan balance control method, device, medium and equipment in syndicated loan |
| CN110197429A (en) * | 2019-06-06 | 2019-09-03 | 苏宁消费金融有限公司 | A kind of consumer finance syndicated loan method for intelligently routing and system |
| CN110675242A (en) * | 2019-08-29 | 2020-01-10 | 北京三快在线科技有限公司 | Credit request processing method and device |
| CN112000720A (en) * | 2019-05-27 | 2020-11-27 | 北京京东尚科信息技术有限公司 | Management method and management system for database connection and database connection pool |
-
2021
- 2021-06-04 CN CN202110621959.7A patent/CN113077339A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101097625A (en) * | 2006-06-29 | 2008-01-02 | 中国银联股份有限公司 | Method for enhancing bank card transaction processing system RAS performance and system |
| CN108389123A (en) * | 2018-02-12 | 2018-08-10 | 中科柏诚科技（北京）股份有限公司 | A kind of internet syndicated loan system and method |
| CN109559011A (en) * | 2018-10-16 | 2019-04-02 | 平安普惠企业管理有限公司 | Loan balance control method, device, medium and equipment in syndicated loan |
| CN112000720A (en) * | 2019-05-27 | 2020-11-27 | 北京京东尚科信息技术有限公司 | Management method and management system for database connection and database connection pool |
| CN110197429A (en) * | 2019-06-06 | 2019-09-03 | 苏宁消费金融有限公司 | A kind of consumer finance syndicated loan method for intelligently routing and system |
| CN110675242A (en) * | 2019-08-29 | 2020-01-10 | 北京三快在线科技有限公司 | Credit request processing method and device |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113807956A (en) * | 2021-11-19 | 2021-12-17 | 北京宇信科技集团股份有限公司 | Data processing method, medium, equipment and system for joint loan |
| CN113807956B (en) * | 2021-11-19 | 2022-02-25 | 北京宇信科技集团股份有限公司 | Data processing method, medium, equipment and system for joint loan |
| CN114549170A (en) * | 2021-11-19 | 2022-05-27 | 北京宇信科技集团股份有限公司 | Data processing method, medium, equipment and system for joint loan |
| CN114549170B (en) * | 2021-11-19 | 2022-11-22 | 北京宇信科技集团股份有限公司 | Data processing method, medium, equipment and system for joint loan |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US8352342B1 (en) | Method and system for determining fees for deposits allocated over a plurality of deposit institutions | |
| Loayza et al. | Economic reform and progress in Latin America and the Caribbean | |
| CN101236638A (en) | Web based bank card risk monitoring method and system | |
| CN101996381A (en) | Method and system for calculating retail asset risk | |
| JP2017049673A (en) | Information processing apparatus and information processing method | |
| CN113706295A (en) | Data analysis-based collection case distribution method, device, equipment and medium | |
| CN112598225A (en) | Evaluation index determination method and apparatus, storage medium, and electronic apparatus | |
| Koont | The digital banking revolution: Effects on competition and stability | |
| CN113077339A (en) | Method for constructing intelligent fund routing model | |
| CN115564549A (en) | Enterprise intelligent tax meter payment declaration method and system | |
| CN112365143B (en) | Middle platform system applied to financial enterprises | |
| US20090259596A1 (en) | Automated Risk Monitoring Method and System | |
| Shahnazarian et al. | FORECASTING AND ANALYSING CORPORATE TAX REVENUES IN SWEDEN USING BAYESIAN VAR MODELS. | |
| CN111626861A (en) | Information display method and device, storage medium and electronic device | |
| CN116361542A (en) | Product recommendation method, device, computer equipment and storage medium | |
| US20120123966A1 (en) | Multidirectional distributed recursive portfolio allocation | |
| US20200372571A1 (en) | Computing system for sharing networks providing dynamic reserving features and related methods | |
| KR101954132B1 (en) | A delinquent disposal system | |
| JP2017050004A (en) | Information processing apparatus | |
| KR102566466B1 (en) | Alternative Credit Rating System for Evaluating Personal Credit | |
| Venslavienė et al. | Forecasting crowdfunding platform revenues using ARIMA model | |
| KR102424423B1 (en) | Method and apparatus of management a secured loan of valuable securities | |
| KR101954133B1 (en) | Real time sart query service system | |
| CN113538157B (en) | Annuity cost management method and annuity cost management device | |
| AU2014224081A1 (en) | Auditing rules optimizer |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20210706 |
|
| RJ01 | Rejection of invention patent application after publication |