CN117852926B - Champion challenger strategy management method and champion challenger strategy management system - Google Patents
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Abstract
The invention discloses a champion challenger strategy management method and system, comprising a user information acquisition module, a strategy information acquisition module, a data processing module, a strategy processing module and a strategy management module; the user information acquisition module is used for acquiring user data and user quantity information; the strategy information acquisition module is used for acquiring risk information and user feedback information; the data processing module is used for processing the acquired user data and acquiring user grades; processing the user quantity information to obtain key performance index parameters; processing the risk information to obtain risk parameters; and processing the user feedback information to obtain user feedback parameters. The comprehensive performance evaluation method can realize comprehensive performance evaluation of the champion challenger strategy by collecting multidimensional information such as user information, key performance indexes, risks, user feedback and the like.
Description
Technical Field
The invention relates to the field of policy management, in particular to a champion challenger policy management method and system.
Background
With the development and application of financial science and technology, champion challenger strategies are widely focused in the fields of investment, asset management and the like. This strategy emphasizes continuous optimization and tuning to accommodate market changes and improve performance. The champion challenger strategy management system is based on advanced data processing and analysis technology and comprehensive analysis of information such as user feedback, key performance indexes, risk parameters and the like, so that the strategy is comprehensively managed and optimized.
The conventional policy management system and method cannot be continuously optimized and adjusted, the direction of policy management and optimization consideration is not comprehensive enough, and large errors are caused to the evaluation of the management system and method, so that data are inaccurate, and therefore, the champion challenger policy management method and system are provided.
Disclosure of Invention
The technical problems to be solved by the invention are as follows: how to solve the problems that the conventional policy management system and method cannot be continuously optimized and adjusted, the policy management and optimization consideration direction is not comprehensive enough, and large errors are caused to the evaluation of the management system and method, so that the data is not accurate, and a champion challenger policy management method and system are provided.
The invention solves the technical problems through the following technical scheme that the system comprises a user information acquisition module, a strategy information acquisition module, a data processing module, a strategy processing module and a strategy management module;
The user information acquisition module is used for acquiring user data and user quantity information;
the strategy information acquisition module is used for acquiring risk information and user feedback information;
the data processing module is used for processing the acquired user data and acquiring user grades;
processing the user quantity information to obtain key performance index parameters;
processing the risk information to obtain risk parameters;
Processing the user feedback information to obtain user feedback parameters;
the strategy processing module is used for processing the acquired key performance index parameters, risk parameters and user feedback parameters to acquire strategy comprehensive parameters;
the policy management module is used for processing the acquired policy comprehensive parameters to acquire policy management information, wherein the policy management information comprises champion policy management information and policy replacement management information.
The method is further characterized in that: the specific process of the user grade acquisition is as follows: the user data comprises a user deposit amount marked as a1 and a user consumption amount marked as a2, and the user grade comprises a primary user, a secondary user and a tertiary user;
By the formula Calculating a user grade parameter a3, wherein k1 is a preset deposit amount, and k2 is a preset consumption amount;
when a3 is more than or equal to 2, the user grade is a first-level user;
when 2 is more than a3 and is more than or equal to 1, the user grade is a secondary user;
when 1 > a3, the user class is three-level users.
Where k1 and k2 are non-fixed values, which can be set by the administrator through specific needs.
The method is further characterized in that: the key performance index parameter acquisition process is as follows: the user quantity information comprises a first-stage user quantity L1 before strategy execution, a second-stage user quantity L2 before strategy execution, a third-stage user quantity L3 before strategy execution, a second-stage user quantity L4 after strategy execution, a second-stage user quantity L5 after strategy execution and a third-stage user quantity L6 after strategy execution;
By the formula Calculating a key performance index parameter L, wherein u1 is/>U2 is/>U3 is/>U 1> u 2> u3.
The method is further characterized in that: the risk parameter acquisition process is as follows: the risk information is the asset yield after the strategy is executed, and the variance of the asset yield after each strategy is executed is calculated;
calculating covariance among asset profitability after different strategies are executed;
combining the variances of all the assets and the covariance into a covariance matrix, wherein the covariance matrix is a symmetric matrix, the elements on the diagonal are variances of the assets, and the elements on the off-diagonal are the covariance among the different assets;
and calculating the execution risk parameters of the whole strategy by using the weights and covariance matrix of the assets.
The method is further characterized in that: the specific process for acquiring the user feedback parameters is as follows: the user feedback information comprises strategy scores fed back by the first-level user, and is marked as the first-level user scores;
the strategy scores fed back by the secondary users are marked as secondary user scores;
the strategy scores fed back by the third-level users are marked as third-level user scores;
Then calculating the average value mark of all the primary user scores as H1;
Calculating the average value of all secondary user scores to be marked as H2;
Calculating the average value of all three-level user scores to be marked as H3;
Calculating a user feedback parameter H through a formula h1×w1+h2+w2+h3×w3=h, wherein w1 is a weight of H1, w2 is a weight of H2, w3 is a weight of H3, and w1 > w2 > w3.
The method is further characterized in that: the strategy comprehensive parameter acquisition comprises the following specific steps:
Acquiring key performance index parameters once every preset time length, continuously acquiring m times, acquiring m key performance index parameters, and calculating an average value mark of the m key performance index parameters as A;
Collecting risk parameters once every preset time length, continuously collecting m times, obtaining m risk parameters, and calculating an average value of the m risk parameters to be marked as B;
Collecting user feedback parameters once every preset time length, continuously collecting m times, obtaining m user feedback parameters, and calculating an average value mark of the m user feedback parameters as C;
calculating a strategy comprehensive parameter D through a formula A, w4+B, w5+C, w6 = D, wherein w4 is the weight of A, w5 is the weight of B, w6 is the weight of C, and w4 = w5 > w6, and acquiring the strategy comprehensive parameter.
The method is further characterized in that: the specific process of acquiring the champion strategy management information is as follows: the champion strategy management information comprises champion strategy non-conforming requirements and champion strategy conforming requirements, champion strategy is analyzed, and n champion strategy comprehensive parameters are continuously acquired for n times to obtain n champion strategy comprehensive parameters;
Calculating the average value of the comprehensive parameters of n champion strategies;
calculating the variance of the comprehensive parameters of the n champion strategies;
Finally, calculating standard deviation marks of n champion strategy comprehensive parameters as Z;
When Z is greater than or equal to a preset standard deviation, generating that the champion strategy is not in accordance with the requirement;
and when Z is smaller than the preset standard deviation, generating a champion strategy meeting the requirements.
The method is further characterized in that: the specific process of the policy replacement management information acquisition is as follows: performing simulation test on the existing strategies, distributing the same customer flow to each strategy, operating each strategy, acquiring strategy comprehensive parameters of each strategy after preset time, performing comparison treatment on each strategy comprehensive parameter, acquiring a strategy comprehensive parameter maximum value, and comparing the strategy comprehensive parameter maximum value with the comprehensive parameters of the champion strategy;
when the maximum value of the comprehensive parameters of the strategies is more than or equal to the comprehensive parameters of the champion strategies, strategy replacement information is generated;
And when the maximum value of the comprehensive parameters of the strategies is smaller than the comprehensive parameters of the champion strategies, generating strategy non-replacement information.
A champion challenger policy management method comprising the steps of:
step one: collecting user data and user quantity information;
step two: collecting risk information and user feedback information;
step three: processing the acquired user data to acquire a user grade;
step four: processing the user quantity information to obtain key performance index parameters;
Step five: processing the risk information to obtain risk parameters;
Step six: processing the user feedback information to obtain user feedback parameters;
step seven: processing the acquired key performance index parameters, risk parameters and user feedback parameters to acquire strategy comprehensive parameters;
Step eight: and processing the acquired comprehensive strategy parameters to acquire strategy management information.
Compared with the prior art, the invention has the following advantages: according to the policy management system and method, through collecting multidimensional information such as user information, key performance indexes, risks and user feedback, comprehensive performance evaluation of champion challenger policies is achieved, and the system is more worthy of popularization and use.
Drawings
FIG. 1 is a system block diagram of the present invention;
fig. 2 is a schematic diagram of the covariance matrix of the present invention.
Detailed Description
The following describes in detail the examples of the present invention, which are implemented on the premise of the technical solution of the present invention, and detailed embodiments and specific operation procedures are given, but the scope of protection of the present invention is not limited to the following examples.
As shown in fig. 1 to 2, the present embodiment provides a technical solution: a champion challenger strategy management method and system comprises a user information acquisition module, a strategy information acquisition module, a data processing module, a strategy processing module and a strategy management module;
The user information acquisition module is used for acquiring user data and user quantity information;
the strategy information acquisition module is used for acquiring risk information and user feedback information;
the data processing module is used for processing the acquired user data and acquiring user grades;
processing the user quantity information to obtain key performance index parameters;
processing the risk information to obtain risk parameters;
Processing the user feedback information to obtain user feedback parameters;
the strategy processing module is used for processing the acquired key performance index parameters, risk parameters and user feedback parameters to acquire strategy comprehensive parameters;
the policy management module is used for processing the acquired policy comprehensive parameters to acquire policy management information, wherein the policy management information comprises champion policy management information and policy replacement management information.
The specific process of the user grade acquisition is as follows: the user data comprises a user deposit amount marked as a1 and a user consumption amount marked as a2, and the user grade comprises a primary user, a secondary user and a tertiary user;
By the formula Calculating a user grade parameter a3, wherein k1 is a preset deposit amount, and k2 is a preset consumption amount;
when a3 is more than or equal to 2, the user grade is a first-level user;
when 2 is more than a3 and is more than or equal to 1, the user grade is a secondary user;
when 1 > a3, the user class is three-level users.
Where k1 and k2 are non-fixed values, which can be set by the administrator through specific needs.
The personalized division of the user grade is realized by introducing the weighted calculation of the deposit and the consumption amount of the user, so that the user grade is not only dependent on a single factor, such as the deposit amount or the consumption amount, but also comprehensively considers the deposit amount and the consumption amount, the overall contribution degree and the value of the user can be reflected, the users are divided into primary, secondary and tertiary users through formula calculation, the contribution degree and the value of different users are finely distinguished, and the enterprise is helped to more accurately formulate marketing strategies, service schemes or preferential activities aiming at different user groups.
The key performance index parameter acquisition process is as follows: the user quantity information comprises a first-stage user quantity L1 before strategy execution, a second-stage user quantity L2 before strategy execution, a third-stage user quantity L3 before strategy execution, a second-stage user quantity L4 after strategy execution, a second-stage user quantity L5 after strategy execution and a third-stage user quantity L6 after strategy execution;
By the formula Calculating a key performance index parameter L, wherein u1 is/>U2 is/>U3 is/>U 1> u 2> u3.
By comprehensively considering the changes of the number of the first-level users, the second-level users and the third-level users, the user structure changes before and after the policy execution can be more comprehensively evaluated, the user structure changes are not only focused on the user changes of a single level, but also the number changes of the users of different levels are considered, the weight u1 > u2 > u3 is introduced, and the contributions of the users of different levels can be distinguished. This helps ensure that high value users have a greater impact on key performance indicators, thereby more accurately reflecting the impact of changes in user architecture on business.
The risk parameter acquisition process is as follows: the risk information is the asset yield after the strategy is executed, and the variance of the asset yield after each strategy is executed is calculated;
calculating covariance among asset profitability after different strategies are executed;
combining the variances of all the assets and the covariance into a covariance matrix, wherein the covariance matrix is a symmetric matrix, the elements on the diagonal are variances of the assets, and the elements on the off-diagonal are the covariance among the different assets;
and calculating the execution risk parameters of the whole strategy by using the weights and covariance matrix of the assets.
By calculating the variance of asset profitability, individual risk levels for each asset can be measured. Variance is an indicator of asset volatility, a larger variance generally represents a larger risk, and covariance between different assets is calculated to capture the relevance between the different assets. The covariance reflects the trend of the same-direction or opposite-direction variation among the assets, is crucial to the risk management of constructing the investment portfolio, and the weight of the assets and the covariance matrix are used for calculating the execution risk parameters of the whole strategy, so that the contribution of the weight of different assets in the investment portfolio to the whole risk can be reflected more accurately, the balance of asset configuration is facilitated, and the risk of the whole investment portfolio is reasonably distributed among different assets.
The specific process for acquiring the user feedback parameters is as follows: the user feedback information comprises strategy scores fed back by the first-level user, and is marked as the first-level user scores;
the strategy scores fed back by the secondary users are marked as secondary user scores;
the strategy scores fed back by the third-level users are marked as third-level user scores;
Then calculating the average value mark of all the primary user scores as H1;
Calculating the average value of all secondary user scores to be marked as H2;
Calculating the average value of all three-level user scores to be marked as H3;
Calculating a user feedback parameter H through a formula h1×w1+h2+w2+h3×w3=h, wherein w1 is a weight of H1, w2 is a weight of H2, w3 is a weight of H3, and w1 > w2 > w3.
By calculating the average value of the scores of the first-level user, the second-level user and the third-level user, the overall user feedback is formed, the enterprise can more comprehensively know the user satisfaction degree and the overall acceptance degree of the strategy, the introduction of the weight can more accurately reflect the influence of different user levels, the opinion and the expectation of the high-level user can be more effectively reflected by giving the higher weight to the enterprise, the loyalty of the high-level user to the enterprise is higher, so that the feedback of the high-level user is more focused to help improve the participation degree of the enterprise, and the user loyalty is enhanced by focusing on the demands of the high-level user.
The strategy comprehensive parameter acquisition comprises the following specific steps:
Acquiring key performance index parameters once every preset time length, continuously acquiring m times, acquiring m key performance index parameters, and calculating an average value mark of the m key performance index parameters as A;
Collecting risk parameters once every preset time length, continuously collecting m times, obtaining m risk parameters, and calculating an average value of the m risk parameters to be marked as B;
Collecting user feedback parameters once every preset time length, continuously collecting m times, obtaining m user feedback parameters, and calculating an average value mark of the m user feedback parameters as C;
calculating a strategy comprehensive parameter D through a formula A, w4+B, w5+C, w6 = D, wherein w4 is the weight of A, w5 is the weight of B, w6 is the weight of C, and w4 = w5 > w6, and acquiring the strategy comprehensive parameter.
By collecting the key performance index, the risk parameter and the user feedback parameter, the advantages and disadvantages of the strategy can be comprehensively evaluated, and different weights can be given to the contributions of the key performance index, the risk parameter and the user feedback parameter by introducing the weight. This helps to ensure that the impact of the different dimension indicators on the overall parameters is balanced, and by continuously collecting the key performance indicators, risk parameters and user feedback parameters multiple times, an average value is calculated, which helps to take into account the volatility of the business in a certain time sequence. This may more robustly reflect the overall performance of the policy.
The specific process of acquiring the champion strategy management information is as follows: the champion strategy management information comprises champion strategy non-conforming requirements and champion strategy conforming requirements, champion strategy is analyzed, and n champion strategy comprehensive parameters are continuously acquired for n times to obtain n champion strategy comprehensive parameters;
Calculating the average value of the comprehensive parameters of n champion strategies;
calculating the variance of the comprehensive parameters of the n champion strategies;
Finally, calculating standard deviation marks of n champion strategy comprehensive parameters as Z;
When Z is greater than or equal to a preset standard deviation, generating that the champion strategy is not in accordance with the requirement;
and when Z is smaller than the preset standard deviation, generating a champion strategy meeting the requirements.
The average value, variance and standard deviation of the comprehensive parameters of the champion strategy are calculated through continuously collecting the comprehensive parameters, so that the monitoring of the fluctuation of the strategy performance is facilitated. The standard deviation is an index for measuring the fluctuation of the data, the fluctuation of the strategy is monitored to help to know the stability of the strategy, whether the champion strategy meets the requirements can be judged according to the standard deviation obtained through calculation by setting a preset standard deviation threshold, if the standard deviation is larger than or equal to the preset standard deviation, the strategy is generated to be not met, and otherwise, the strategy is generated to be met.
The specific process of the policy replacement management information acquisition is as follows: performing simulation test on the existing strategies, distributing the same customer flow to each strategy, operating each strategy, acquiring strategy comprehensive parameters of each strategy after preset time, performing comparison treatment on each strategy comprehensive parameter, acquiring a strategy comprehensive parameter maximum value, and comparing the strategy comprehensive parameter maximum value with the comprehensive parameters of the champion strategy;
when the maximum value of the comprehensive parameters of the strategies is more than or equal to the comprehensive parameters of the champion strategies, strategy replacement information is generated;
And when the maximum value of the comprehensive parameters of the strategies is smaller than the comprehensive parameters of the champion strategies, generating strategy non-replacement information.
The method comprises the steps of obtaining the strategy comprehensive parameters of each strategy through simulation test on the existing strategy, realizing the evaluation of different strategy performances, and judging whether more excellent strategies need to replace the current champion strategies or not through comparing the comprehensive parameters of different strategies, particularly comparing the maximum comprehensive parameters with the comprehensive parameters of champion strategies.
A champion challenger policy management method comprising the steps of:
step one: collecting user data and user quantity information;
step two: collecting risk information and user feedback information;
step three: processing the acquired user data to acquire a user grade;
step four: processing the user quantity information to obtain key performance index parameters;
Step five: processing the risk information to obtain risk parameters;
Step six: processing the user feedback information to obtain user feedback parameters;
step seven: processing the acquired key performance index parameters, risk parameters and user feedback parameters to acquire strategy comprehensive parameters;
Step eight: and processing the acquired comprehensive strategy parameters to acquire strategy management information.
In summary, when the method is used, the comprehensive performance evaluation of the champion challenger strategy is realized by collecting multidimensional information such as user information, key performance indexes, risks, user feedback and the like.
Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include at least one such feature. In the description of the present invention, the meaning of "plurality" means at least two, for example, two, three, etc., unless specifically defined otherwise.
In the description of the present specification, a description referring to terms "one embodiment," "some embodiments," "examples," "specific examples," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms are not necessarily directed to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, the different embodiments or examples described in this specification and the features of the different embodiments or examples may be combined and combined by those skilled in the art without contradiction.
While embodiments of the present invention have been shown and described above, it will be understood that the above embodiments are illustrative and not to be construed as limiting the invention, and that variations, modifications, alternatives and variations may be made to the above embodiments by one of ordinary skill in the art within the scope of the invention.
Claims (2)
1. The champion challenger strategy management system is characterized by comprising a user information acquisition module, a strategy information acquisition module, a data processing module, a strategy processing module and a strategy management module;
The user information acquisition module is used for acquiring user data and user quantity information;
the strategy information acquisition module is used for acquiring risk information and user feedback information;
the data processing module is used for processing the acquired user data and acquiring user grades;
processing the user quantity information to obtain key performance index parameters;
processing the risk information to obtain risk parameters;
Processing the user feedback information to obtain user feedback parameters;
the strategy processing module is used for processing the acquired key performance index parameters, risk parameters and user feedback parameters to acquire strategy comprehensive parameters;
the policy management module is used for processing the acquired policy comprehensive parameters to acquire policy management information, wherein the policy management information comprises champion policy management information and policy replacement management information;
The specific process of the user grade acquisition is as follows: the user data comprises a user deposit amount marked as a1 and a user consumption amount marked as a2, and the user grade comprises a primary user, a secondary user and a tertiary user;
By the formula 3, Calculating a user grade parameter a3, wherein k1 is a preset deposit amount, and k2 is a preset consumption amount;
when a3 is more than or equal to 2, the user grade is a first-level user;
when 2 is more than a3 and is more than or equal to 1, the user grade is a secondary user;
when 1 is more than a3, the user grade is three-grade user;
The key performance index parameter acquisition process is as follows: the user quantity information comprises a first-stage user quantity L1 before strategy execution, a second-stage user quantity L2 before strategy execution, a third-stage user quantity L3 before strategy execution, a second-stage user quantity L4 after strategy execution, a second-stage user quantity L5 after strategy execution and a third-stage user quantity L6 after strategy execution;
By the formula Calculating a key performance index parameter L, wherein u1 is/>U2 is/>U3 is/>U 1> u 2> u3;
The risk parameter acquisition process is as follows: the risk information is the asset yield after the strategy is executed, and the variance of the asset yield after each strategy is executed is calculated;
calculating covariance among asset profitability after different strategies are executed;
combining the variances of all the assets and the covariance into a covariance matrix, wherein the covariance matrix is a symmetric matrix, the elements on the diagonal are variances of the assets, and the elements on the off-diagonal are the covariance among the different assets;
Calculating an execution risk parameter of the whole strategy by using the weight and covariance matrix of the asset;
The specific process for acquiring the user feedback parameters is as follows: the user feedback information comprises strategy scores fed back by the first-level user, and is marked as the first-level user scores;
the strategy scores fed back by the secondary users are marked as secondary user scores;
the strategy scores fed back by the third-level users are marked as third-level user scores;
Then calculating the average value mark of all the primary user scores as H1;
Calculating the average value of all secondary user scores to be marked as H2;
Calculating the average value of all three-level user scores to be marked as H3;
calculating a user feedback parameter H through a formula h1×w1+h2×w2+h3×w3=h, wherein w1 is a weight of H1, w2 is a weight of H2, w3 is a weight of H3, and w1 > w2 > w3;
the strategy comprehensive parameter acquisition comprises the following specific steps:
Acquiring key performance index parameters once every preset time length, continuously acquiring m times, acquiring m key performance index parameters, and calculating an average value mark of the m key performance index parameters as A;
Collecting risk parameters once every preset time length, continuously collecting m times, obtaining m risk parameters, and calculating an average value of the m risk parameters to be marked as B;
Collecting user feedback parameters once every preset time length, continuously collecting m times, obtaining m user feedback parameters, and calculating an average value mark of the m user feedback parameters as C;
calculating a strategy comprehensive parameter D through a formula A, w4+B, w5+C, w6 = D, wherein w4 is the weight of A, w5 is the weight of B, w6 is the weight of C, and w4 = w5 > w6, and acquiring the strategy comprehensive parameter;
the specific process of acquiring the champion strategy management information is as follows: the champion strategy management information comprises champion strategy non-conforming requirements and champion strategy conforming requirements, champion strategy is analyzed, and n champion strategy comprehensive parameters are continuously acquired for n times to obtain n champion strategy comprehensive parameters;
Calculating the average value of the comprehensive parameters of n champion strategies;
calculating the variance of the comprehensive parameters of the n champion strategies;
Finally, calculating standard deviation marks of n champion strategy comprehensive parameters as Z;
When Z is greater than or equal to a preset standard deviation, generating that the champion strategy is not in accordance with the requirement;
when Z is smaller than a preset standard deviation, generating a champion strategy meeting the requirements;
the specific process of the policy replacement management information acquisition is as follows: performing simulation test on the existing strategies, distributing the same customer flow to each strategy, operating each strategy, acquiring strategy comprehensive parameters of each strategy after preset time, performing comparison treatment on each strategy comprehensive parameter, acquiring a strategy comprehensive parameter maximum value, and comparing the strategy comprehensive parameter maximum value with the comprehensive parameters of the champion strategy;
when the maximum value of the comprehensive parameters of the strategies is more than or equal to the comprehensive parameters of the champion strategies, strategy replacement information is generated;
And when the maximum value of the comprehensive parameters of the strategies is smaller than the comprehensive parameters of the champion strategies, generating strategy non-replacement information.
2. A champion challenger policy management method based on the management system of claim 1, characterized by: the method comprises the following steps:
step one: collecting user data and user quantity information;
step two: collecting risk information and user feedback information;
step three: processing the acquired user data to acquire a user grade;
step four: processing the user quantity information to obtain key performance index parameters;
Step five: processing the risk information to obtain risk parameters;
Step six: processing the user feedback information to obtain user feedback parameters;
step seven: processing the acquired key performance index parameters, risk parameters and user feedback parameters to acquire strategy comprehensive parameters;
Step eight: and processing the acquired comprehensive strategy parameters to acquire strategy management information.
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Citations (18)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2006164257A (en) * | 2004-11-15 | 2006-06-22 | Sbi Holdings Inc | Scoring model evaluation method using credit authorization, scoring model evaluation apparatus, authorization system, and scoring model evaluation program |
| JP2007004828A (en) * | 2004-11-15 | 2007-01-11 | Sbi Holdings Inc | Scoring model evaluation device utilizing credit administration, and administration system |
| CN104573071A (en) * | 2015-01-26 | 2015-04-29 | 湖南大学 | Intelligent school situation analysis system and method based on megadata technology |
| CN109146662A (en) * | 2018-07-16 | 2019-01-04 | 蜜小蜂智慧（北京）科技有限公司 | A kind of risk control method and device |
| US10262271B1 (en) * | 2018-02-14 | 2019-04-16 | DataTron Technologies Inc. | Systems and methods for modeling machine learning and data analytics |
| CN109767255A (en) * | 2018-12-06 | 2019-05-17 | 东莞团贷网互联网科技服务有限公司 | A method of it is modeled by big data and realizes intelligence operation and precision marketing |
| CN110097459A (en) * | 2019-05-08 | 2019-08-06 | 重庆斐耐科技有限公司 | A kind of financial risks appraisal procedure and system based on big data technology |
| CN110837963A (en) * | 2019-11-06 | 2020-02-25 | 浪潮卓数大数据产业发展有限公司 | Risk control platform construction method based on data, model and strategy |
| CN112365265A (en) * | 2020-10-26 | 2021-02-12 | 建投数据科技（山东）有限公司 | Internet financial intelligent wind control system |
| CN113919934A (en) * | 2021-08-25 | 2022-01-11 | 北京睿知图远科技有限公司 | Bank loan service scoring strategy iteration method |
| CN114331167A (en) * | 2021-12-31 | 2022-04-12 | 北京宇信科技集团股份有限公司 | Champion challenger strategy management method, system, medium and equipment |
| CN114723481A (en) * | 2022-03-29 | 2022-07-08 | 中国建设银行股份有限公司 | Data processing method and device, electronic equipment and storage medium |
| CN114757637A (en) * | 2022-03-22 | 2022-07-15 | 深圳壹账通智能科技有限公司 | Credit approval method, credit approval device, credit approval equipment and credit approval storage medium based on decision engine |
| CN116167861A (en) * | 2021-11-24 | 2023-05-26 | 北京中关村科金技术有限公司 | Automatic asset configuration strategy generation method and device |
| CN116468540A (en) * | 2023-04-13 | 2023-07-21 | 苏银凯基消费金融有限公司 | Consumption finance guest group risk identification system and method based on big data |
| CN116757827A (en) * | 2023-06-08 | 2023-09-15 | 重庆富民银行股份有限公司 | Wind control strategy management system and method based on champion challenger strategy |
| CN117009937A (en) * | 2023-08-14 | 2023-11-07 | 江西卓尔咨询集团有限公司 | Customer information management system based on data analysis |
| CN117522607A (en) * | 2023-11-10 | 2024-02-06 | 北京英政科技有限公司 | Enterprise financial management system |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2009006448A1 (en) * | 2007-06-28 | 2009-01-08 | Cashedge, Inc. | Global risk administration method and system |
| US20230186385A1 (en) * | 2021-12-13 | 2023-06-15 | Prometics, Inc. | Computer-implemented system and method of facilitating artificial intelligence based lending strategies and business revenue management |
-
2024
- 2024-03-04 CN CN202410243622.0A patent/CN117852926B/en active Active
Patent Citations (18)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2006164257A (en) * | 2004-11-15 | 2006-06-22 | Sbi Holdings Inc | Scoring model evaluation method using credit authorization, scoring model evaluation apparatus, authorization system, and scoring model evaluation program |
| JP2007004828A (en) * | 2004-11-15 | 2007-01-11 | Sbi Holdings Inc | Scoring model evaluation device utilizing credit administration, and administration system |
| CN104573071A (en) * | 2015-01-26 | 2015-04-29 | 湖南大学 | Intelligent school situation analysis system and method based on megadata technology |
| US10262271B1 (en) * | 2018-02-14 | 2019-04-16 | DataTron Technologies Inc. | Systems and methods for modeling machine learning and data analytics |
| CN109146662A (en) * | 2018-07-16 | 2019-01-04 | 蜜小蜂智慧（北京）科技有限公司 | A kind of risk control method and device |
| CN109767255A (en) * | 2018-12-06 | 2019-05-17 | 东莞团贷网互联网科技服务有限公司 | A method of it is modeled by big data and realizes intelligence operation and precision marketing |
| CN110097459A (en) * | 2019-05-08 | 2019-08-06 | 重庆斐耐科技有限公司 | A kind of financial risks appraisal procedure and system based on big data technology |
| CN110837963A (en) * | 2019-11-06 | 2020-02-25 | 浪潮卓数大数据产业发展有限公司 | Risk control platform construction method based on data, model and strategy |
| CN112365265A (en) * | 2020-10-26 | 2021-02-12 | 建投数据科技（山东）有限公司 | Internet financial intelligent wind control system |
| CN113919934A (en) * | 2021-08-25 | 2022-01-11 | 北京睿知图远科技有限公司 | Bank loan service scoring strategy iteration method |
| CN116167861A (en) * | 2021-11-24 | 2023-05-26 | 北京中关村科金技术有限公司 | Automatic asset configuration strategy generation method and device |
| CN114331167A (en) * | 2021-12-31 | 2022-04-12 | 北京宇信科技集团股份有限公司 | Champion challenger strategy management method, system, medium and equipment |
| CN114757637A (en) * | 2022-03-22 | 2022-07-15 | 深圳壹账通智能科技有限公司 | Credit approval method, credit approval device, credit approval equipment and credit approval storage medium based on decision engine |
| CN114723481A (en) * | 2022-03-29 | 2022-07-08 | 中国建设银行股份有限公司 | Data processing method and device, electronic equipment and storage medium |
| CN116468540A (en) * | 2023-04-13 | 2023-07-21 | 苏银凯基消费金融有限公司 | Consumption finance guest group risk identification system and method based on big data |
| CN116757827A (en) * | 2023-06-08 | 2023-09-15 | 重庆富民银行股份有限公司 | Wind control strategy management system and method based on champion challenger strategy |
| CN117009937A (en) * | 2023-08-14 | 2023-11-07 | 江西卓尔咨询集团有限公司 | Customer information management system based on data analysis |
| CN117522607A (en) * | 2023-11-10 | 2024-02-06 | 北京英政科技有限公司 | Enterprise financial management system |
Non-Patent Citations (2)
| Title |
|---|
| Cybersecurity blue team strategies:uncover the secrets of blue teams to combat cyber threats in your organization;Kunal sehgal等;IEEE ixplore;20231231;第1-10页 * |
| 基于数据资产理论的科学数据管控架构及实践研究;曾群;屈窈;虞逸飞;;图书馆学研究;20200225(04);第50-60页 * |
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