CN107832937A - Financial technology Central exponent analysis method, storage medium and equipment - Google Patents
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Abstract
Financial technology Central exponent analysis method, storage medium and equipment provided by the invention, build the specific evaluation index framework for the analysis of financial technology Central exponent；Gather city ranking report data and therefrom select sample city in involved each city；Collect each sample city achievement data related to each index item in the specific evaluation index framework；Using the step analysis mode based on marking rule, city ranking report data and achievement data are analyzed, to determine the standardized score of the index weights of the target indicator item related to each key element in the ranking report data of city of specific evaluation index framework and each sample city in target indicator item；Be weighted according to index weights and standardized score and, to obtain the financial technology Central exponent value in each sample city；The present invention can precisely show each city in developing strong, the weak link of financial technology, opportunity to develop and striving direction be disclosed, so that it promotes financial technology development effort more with a definite target in view.
Description
Technical Field
The invention relates to the technical field of financial data analysis, in particular to an index analysis method, a storage medium and equipment of a financial technology center.
Background
With the increasing importance of the financial science and technology in China and China, establishing a set of complete and multi-view index system is more and more important for describing and evaluating the development condition of the financial science and technology of each city. In order to objectively, reasonably and comprehensively evaluate the degree of development of financial technologies in various cities of China at present under the compilation principle of attaching importance to representativeness and comprehensiveness, adhering to scientificity and operability and considering stability and expansibility, financial technologies (Fintech) mainly refers to financial innovation brought by technology and can create new business modes, applications, processes or products, thereby having great influence on the provision modes of financial markets, financial institutions or financial services (FSB, 2016). Financial science and technology embodies the continuous integration of finance and technology, emphasizes that the technology (such as big data, risk models, cloud computing, block chains and the like) is used as a core driving force to improve financial efficiency, control financial risks and achieve financial purposes, and specifically comprises the subdivision fields of network lending, crowd funding, third-party payment, big data credit investigation, block chain technology application and the like. Financial science and technology can effectively reduce financial transaction cost and information asymmetry, improve financial allocation resource efficiency, change organization forms and market structures of financial transactions, expand transaction possibility and enhance financial popularity. In the future, financial science and technology will bring more imagination to us, various innovative financial modes will emerge continuously, and the influence on the global economy will be increased.
In the existing financial analysis, an index analysis method related to financial science and technology does not exist; in the current analysis mode, although the weight is corrected by adopting an entropy weight method, the importance of a judgment matrix formed by manual scoring is weakened, and the expert scoring and actual data are combined to try to calculate the sub-element weight more objectively, the step of searching a large number of experts for importance scoring is still avoided, a large amount of human resources and time are needed, and the authority of the judgment matrix cannot be effectively guaranteed.
Disclosure of Invention
In view of the above-mentioned drawbacks of the prior art, it is an object of the present invention to provide a touch-pad device and an entertainment system using the same, which solve the problems of the prior art.
In order to achieve the above and other related objects, the present invention provides a method for index analysis of a financial technology center, applied to a computer device, the method comprising: constructing a specific evaluation index framework for index analysis of a financial technology center, which comprises the following steps: a plurality of index items; collecting city ranking report data and selecting sample cities from various cities involved in the city ranking report data; acquiring index data related to each index item in each sample city and the specific evaluation index frame; analyzing the city ranking report data and the index data by adopting a hierarchical analysis mode based on a scoring rule to determine the index weight of a target index item of a specific evaluation index frame, which is related to each element in the city ranking report data, and the standardized score of each sample city in the target index item; and carrying out weighted sum according to the index weight and the standardized score to obtain the index value of the financial science and technology center of each sample city.
In an embodiment of the present invention, the analyzing the city ranking report data and the index data in a hierarchical analysis manner based on a scoring rule to determine an index weight of a target index item of a specific evaluation index frame related to each element in the city ranking report data and a standardized score of each sample city in the target index item includes: calculating authority degree of each ranking report in the city ranking report data, matching degree between an index frame used by each ranking report and the specific evaluation index frame, and contribution degree of each city in each ranking report; determining the elements related to the index items in the specific evaluation index frame in each ranking report according to the calculated matching degree; calculating the importance between every two elements in each ranking report, wherein the importance is determined by the weight and the matching degree of each element in the ranking report; constructing a judgment matrix according to the calculated importance; and calculating the maximum characteristic root and the normalized characteristic vector according to the judgment matrix, carrying out consistency check, and obtaining the weight of each index item according to the characteristic vector under the condition of passing the check.
In an embodiment of the present invention, the authority is calculated by:
wherein, the Australityllevel i : ranking the authority of report i; authority institution : the authority degree of the ranking issuing organization is obtained by the scoring of experts, and the range is (0, 1); year i : rank report i year of release; currentYear: the current year; year earlist : earliest reporting year included in the collection range; α: the weight adjustment factor.
In an embodiment of the invention, the specific evaluation index framework distributes each index item according to one or more layers, and the index item at the last layer includes one or more tool variables; the calculation mode of the matching degree comprises the following steps:
wherein, matchLevel i,j : degree of match, i.e. the phase of element j in ranking report i with all index items in a particular evaluation index frameDegree of similarity; matchelement i,j : the matching number of the tool variables contained in the element j in the ranking report i and the tool variables in the specific evaluation index frame; element: the number of tool variables in a particular evaluation index framework.
In an embodiment of the present invention, the calculation method of the contribution degree includes:
wherein, contributeLevel i,city : ranking the contribution of the city in the report i; x is the number of city : the ranking reports the ranking of the city in i. α: an elasticity adjustment factor; beta: normalizing the adjustment factor; λ: a range adjustment factor.
In an embodiment of the present invention, the determining, according to the calculated matching degree, elements related to the index items in the specific evaluation index frame in each ranking report includes: judging whether the matching degree is greater than a preset value; if the number is larger than the preset value, the element is judged to be the relevant element.
In an embodiment of the invention, the importance calculating method includes:
wherein, C i,a,b : for ranking report i, the importance between element a and element b; w i,a : the weight of element a in ranking report i; w is a group of i,b : the weight of element b in ranking report i; matchLevel i,a : matching degree of the element a in the ranking report i; matchLevel i,b : the matching degree of the element b in the ranking report i; w is i,a 、W i,b The calculation method comprises the following steps: in a ranking report, taking the contribution degree of a city as Y, taking the corresponding value of the relevant elements determined according to the matching degree as X, and obtaining a coefficient W used by the Y obtained by calculating the X through a regression algorithm, wherein the coefficient W is the weight; the regression algorithm comprises the following steps: threadSexual regression, logistic regression, or polynomial regression methods.
In an embodiment of the present invention, the calculation method of the determination matrix includes:
wherein, the Australityllevel i Is the authority; c i,a,b : for rank report i, the importance between element a and element b.
In an embodiment of the present invention, in case the consistency check fails, the city ranking report data is collected again and the decision matrix is reconstructed accordingly.
In an embodiment of the invention, the types of the index of the finance and technology center include: one or more of a financial technology industry index, a financial technology experience index, a financial technology ecology index, and a composite index of any one or more of these indices.
In one embodiment of the present invention, the specific evaluation index framework distributes each index item in one or more layers, the lowest index item comprising one or more tool variables; the first-layer index items corresponding to the financial science and technology industry index comprise: any one or more of a network credit industry index item, a crowd funding industry index item, a third party payment industry index item, a big data credit industry index item and a block chain industry index item; each second-layer index item corresponding to the first-layer index item comprises: any one or more of the number of businesses, market size, capital strength, and talent supply sub-indicator terms; each of the second-layer index items includes: for quantizing one or more tool variables representing the second layer index term.
In an embodiment of the present invention, the collected index data is processed by data processing, and the data processing includes: any one or more of data cleansing, correlation, and de-dimension.
To achieve the above and other related objects, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when being executed by a processor, implements the index analysis method of a financial technology center.
To achieve the above and other related objects, the present invention provides a computer apparatus comprising: a processor and a memory; the memory is used for storing computer programs, and the processor is used for executing the computer programs stored by the memory so as to enable the computer equipment to execute the index analysis method of the financial technology center.
To achieve the above and other related objects, the present invention provides a network device, comprising: a processor, a memory, and a communicator; the communicator is connected with the user terminal through a network so as to receive an index analysis request of the financial science and technology center; the memory is used for storing a computer program; the processor is used for executing the computer program stored in the memory, so that the computer device executes the index analysis method of the financial technology center to generate a financial technology center index value and stores the index value in the memory; the processor is further configured to search a corresponding index value of the finance and technology center in the memory according to the index analysis request of the finance and technology center, and respond to the user terminal through the communicator.
In summary, the index analysis method, the storage medium, and the device of the financial technology center provided by the present invention construct a specific evaluation index framework for index analysis of the financial technology center, and the method includes: a plurality of index items; collecting city ranking report data and selecting sample cities from various cities involved in the city ranking report data; acquiring index data related to each index item in each sample city and the specific evaluation index frame; analyzing the city ranking report data and the index data by adopting a hierarchical analysis mode based on a scoring rule to determine the index weight of a target index item of a specific evaluation index frame, which is related to each element in the city ranking report data, and the standardized score of each sample city in the target index item; carrying out weighted sum according to the index weight and the standardized score to obtain the index value of the financial science and technology center of each sample city; the invention can accurately display the strong and weak links of each city in the development of financial science and technology, and reveal the development opportunity and the effort direction so as to more purposefully promote the development work of the financial science and technology.
Drawings
Fig. 1 is a flowchart illustrating an index analysis method of a finance and technology center according to an embodiment of the present invention.
Fig. 2 is a schematic exploded flowchart illustrating a step of the index analysis method of the finance and technology center according to an embodiment of the invention.
FIG. 3a is a schematic diagram of a visualization chart formed according to the integrated index of the financial technology center according to an embodiment of the present invention.
FIG. 3b is a schematic diagram of a visualization chart formed according to the index of the financial technology industry according to an embodiment of the invention.
Detailed Description
The embodiments of the present invention are described below with reference to specific embodiments, and other advantages and effects of the present invention will be easily understood by those skilled in the art from the disclosure of the present specification. The invention is capable of other and different embodiments and of being practiced or of being carried out in various ways, and its several details are capable of modification in various respects, all without departing from the spirit and scope of the present invention. It is to be noted that the features in the following embodiments and examples may be combined with each other without conflict.
It should be noted that the drawings provided in the following embodiments are only for illustrating the basic idea of the present invention, and the components related to the present invention are only shown in the drawings rather than drawn according to the number, shape and size of the components in actual implementation, and the type, quantity and proportion of the components in actual implementation may be changed freely, and the layout of the components may be more complicated.
The invention adopts a chromatography analysis method based on scoring rule learning to make the index of the financial science and technology center. By collecting city ranking in a large number of authority reports and combining the index framework, the matching degree, the contribution degree and the authority degree of each report are calculated, and the relative importance degree between sub-indexes is judged by utilizing a machine learning (linear regression) method, so that a judgment matrix meeting consistency conditions is automatically constructed, the authority and the comprehensiveness (a large number of authority reports) of the weight are reserved, meanwhile, the influence of subjective speculation of experts is reduced, the time of scoring of the experts is saved, and the efficiency is greatly improved.
As shown in fig. 1, the index analysis method of the finance and technology center according to the embodiment of the present invention can be applied to a computer device, such as a server, a computer, a notebook computer, a smart phone, a tablet computer, etc.;
the method comprises the following steps:
step S101: constructing a specific evaluation index framework for index analysis of the financial science and technology center, wherein the specific evaluation index framework comprises the following steps: a plurality of index items.
In an embodiment of the invention, the index item is used for quantitative evaluation in combination with city data.
The specific evaluation index frame is distributed with index items according to one or more layers, and the index item at the lowest layer comprises one or more tool variables; the first-layer index items corresponding to the financial technology industry index include: any one or more of a network credit industry index item, a crowd funding industry index item, a third party payment industry index item, a big data credit industry index item and a block chain industry index item; each second-layer index item corresponding to the first-layer index item comprises: any one or more of the number of businesses, market size, capital strength, and talent supply sub-indicator terms; each of the second-layer index items includes: for quantifying one or more tool variables representing the second layer metric term.
For example, the specific evaluation index framework may be as shown in the following table:
it should be noted that, each tool variable in the table may be added or deleted, at least one of which is required, and not all of which are required; some of the data, such as "the amount of the urban network lending enterprises", is not limited to the value corresponding to "x family", and may be a value obtained by mathematically operating x, such as In (x).
As can be seen from the above table, the index item structure of the table is classified to support the existence of a plurality of financial technology indices, and specifically, the types of the financial technology center index include: the financial science and technology industry index, the financial science and technology experience index and the financial science and technology ecology index; of course, the combined index of the financial technology center can be calculated by combining the partial indexes.
Step S102: city ranking report data is collected and sample cities are selected from the cities involved therein.
In one embodiment of the present invention, the present invention is based on analyzing city ranking report data, wherein the city ranking report data is embodied as a plurality of city ranking reports; all cities involved in each city ranking report can be used as sample cities, and some free selections or screens can be performed to select the sample cities.
Step S103: and acquiring index data of each sample city related to each index item in the specific evaluation index frame.
In an embodiment of the present invention, the index data may be collected from the content of the city ranking report, or may be collected from sources such as internet data (e.g., financial technology enterprise data, city statistics data, website information data), for example, the index data is related to tool variables of a city in the table.
In an embodiment of the invention, the collected index data is processed by data processing, and the data processing includes: any one or more of data cleansing, correlation, and de-dimension.
Step S104: and analyzing the city ranking report data and the index data by adopting a hierarchical analysis mode based on a scoring rule to determine the index weight of a target index item of a specific evaluation index frame, which is related to each element in the city ranking report data, and the standardized score of each sample city in the target index item.
Referring to fig. 2, a specific process of step S104 in an embodiment is shown, which includes:
step S201: and calculating the authority degree of each ranking report in the city ranking report data, the matching degree between the index frame used by each ranking report and the specific evaluation index frame, and the contribution degree of each city in each ranking report.
In an embodiment of the invention, the authority degree is a score for evaluating the authority degree of each collected ranking report, and the score is composed of the authority degree of a release mechanism, the release year and the time from the present and other factors; the authority calculation mode comprises the following steps:
wherein, the Australityllevel i : ranking the authority of report i; authority institution : the authority degree of the ranking issuing organization is obtained by the scoring of experts, and the range is (0, 1); year i : rank report i year of release; currentYear: the current year;year earlist : the earliest ranked report year that was included in the collection range; α: the weight adjustment factor.
In an embodiment of the present invention, the matching degree is a score of the similarity degree between the index frame used for evaluating each rank and the specific evaluation index frame used for the index; the calculation mode of the matching degree comprises the following steps:
wherein, matchLevel i,j : matching degree, namely the similarity degree of the element j in the ranking report i and all index items in a specific evaluation index frame; matchelement i,j : the matching number of the tool variables contained in the element j in the ranking report i and the tool variables in the specific evaluation index frame; element: the number of tool variables in a particular evaluation index framework.
In an embodiment of the present invention, the contribution degree is a score for evaluating the ranking order or score of each city appearing in each ranking, and is composed of the ranking order, the score and other factors; the calculation mode of the contribution degree comprises the following steps:
wherein, the ContributeLevel i,city : ranking the contribution of the city in the report i; x is a radical of a fluorine atom city : the ranking reports the ranking of the city in i. α: an elasticity adjustment factor; beta: normalizing the adjustment factor; λ: a range adjustment factor.
Step S202: and determining the elements related to the index items in the specific evaluation index frame in each ranking report according to the calculated matching degree.
In an embodiment of the present invention, the determining, according to the calculated matching degree, elements related to the index items in the specific evaluation index frame in each ranking report includes: judging whether the matching degree is greater than a preset value; if the number is larger than the preset number, judging the element to be a related element; preferably, the preset value is 0; it is easily understood that if the matching degree is greater than 0, the description is about; if the matching degree is equal to 0, the description is irrelevant, but it is not limited thereto.
Step S203: and calculating the importance between every two elements in each ranking report, wherein the importance is determined by the weight and the matching degree of each element in the ranking report.
In an embodiment of the present invention, the importance calculating method includes:
wherein, C i,a,b : for rank report i, importance between element a and element b; w i,a : the weight of element a in ranking report i; w i,b : the weight of element b in rank report i; matchLevel i,a : the matching degree of the element a in the ranking report i; matchLevel i,b : the degree of match of element b in rank report i.
The weight W i,a 、W i,b The calculation method comprises the following steps: in a ranking report, taking the contribution degree of a city as Y, taking the corresponding value of the relevant elements determined according to the matching degree as X, and obtaining a coefficient W used by the Y obtained by calculating the X through a regression algorithm, wherein the coefficient W is the weight; the regression algorithm comprises the following steps: linear regression, logistic regression, or polynomial regression; the value of the element X may be obtained from city basic data, and may be obtained from index data of a tool variable of a related index item.
Step S204: and constructing a judgment matrix according to the calculated importance.
In an embodiment of the present invention, the judgment matrix is a judgment given to the relative importance of each element of each layer, and the judgment result is expressed in a matrix form. We use the importance of all ranking reports between two elements to carry out weighted average by using a pairwise comparison method, and the weighted weight is the authorityAuthorityLevel i Obtaining a judgment matrix C = C a,b 。
The calculation mode of the judgment matrix comprises the following steps:
wherein, the Australityllevel i Is the authority; c i,a,b : for rank report i, the importance between element a and element b.
Step S205: and calculating the maximum characteristic root and the normalized characteristic vector according to the judgment matrix, carrying out consistency check, and obtaining the weight of each index item according to the characteristic vector under the condition of passing the check.
In an embodiment of the present invention, according to the hierarchical analysis theory, the maximum feature root λ is calculated for the judgment matrix max (C) And corresponding feature vectors, and performing consistency check by using the consistency index, the random consistency index and the consistency ratio. If the test is passed, the normalized feature vector is the weight vector (i.e. the weight of each required element): if not, the city ranking report data is collected again, the step S104 is repeated to reconstruct the judgment matrix and the judgment is carried out until the judgment is passed, so that the index weight of the index item is obtained.
Wherein, the index CI formula of the inconsistency degree is as follows:
the random consensus indicator ratio CR is given by the following formula:
require CR&And lt, 0.1 indicates that the consistency is acceptable, otherwise, the check is not passed.
Step S105: and carrying out weighted sum according to the index weight and the standardized score to obtain the index value of the financial science and technology center of each sample city.
As mentioned above, in one embodiment, the financial industry index, the financial experience index, the financial ecology index, and the combined index of the index may be generated according to the foregoing table.
After obtaining the value of the finance and technology index of each sample city, the value can be displayed by means of a visual chart, and an index analysis report can be generated according to the value.
As shown in fig. 3a, a graph form of the integrated indices of the finance and technology centers of multiple cities in China obtained by the index analysis method of the present invention is shown.
As can be seen, in the overall ranking, the top five are listed in Beijing, shanghai, shenzhen, hangzhou and Guangzhou. Except Hangzhou, the rest are traditional front-line cities, and the higher correlation between the economic and financial strength and the financial technology industry can be seen. Hangzhou, as the only one entering the first five non-first-line cities, is spreading its own vitality and competitiveness in the field of financial technology and is gradually becoming the national center of financial technology. Chengdu, wuhan, nanjing, chongqing, tianjin and Xian are respectively the 6 th to 10 th names. The development situation of the financial science and technology is good, and the financial science and technology has various characteristics and is expected to gradually take the era of regional financial science and technology centers in southwest, china, east China, north China and northwest China. Qingdao, jinan, chongqing, zhengzhou, changsha, ningbo, fertilizer combination, mansion, dalian and Guiyang are ranked from 11 th to 20 th, and have great promotion space and development potential, for example, guiyang which is known as 'the capital of big data' is currently 20 th across the nation through the differentiated development strategy financial technology, and is expected to realize further breakthrough in the fields of big data and cloud computing.
As shown in fig. 3b, a chart form of the index of the financial technology industry of multiple cities in China is shown according to the index analysis method of the present invention.
It can be seen that the top ten cities in the industry index are in turn: beijing, shanghai, shenzhen, hangzhou, guangzhou, chengdu, qingdao, nanjing, tianjin and Jinnan. The cities ranked 11-20 are in order: ningbo, xian, wuhan, chongqing, zhengzhou, changsha, hefei, xiamen, guiyang and Dalian. The inter-city industry index ranking echelon sense is obvious, and can be divided into three echelons: beijing, shanghai, shenzhen, hangzhou, guangzhou and Chengzhou are in the first platoon, the development of each financial technology industry in cities is relatively rich, and the comprehensive level is in the front of China; qingdao, nanjing and Tianjin are in the second echelon, the development level of the financial and technology industry is middle, and at least 2 of the five industries have slow development; the rest cities are in the third echelon, and have larger difference compared with the cities of the first and second echelons.
To achieve the above and other related objects, embodiments of the present invention may also provide a computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, implements a financial technology center index analysis method such as that in the embodiment of fig. 1; the storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.
To achieve the above and other related objects, the present invention provides, in one embodiment, a computer apparatus including: a processor and a memory; the memory is configured to store a computer program, and the processor is configured to execute the computer program stored in the memory to cause the computer device to perform a financial technology center index analysis method such as that in the embodiment of fig. 1. The computer device may be a server, a computer, a notebook computer, a smart phone, a tablet computer, or the like.
In one embodiment, the computer device may be a network device, which is connected to the user terminal through a communicator network to receive the index analysis request from the finance and technology center; the memory is used for storing a computer program; the processor is used for executing the computer program stored in the memory, so that the computer equipment executes the index analysis method of the financial science and technology center to generate a financial science and technology center index value and stores the financial science and technology center index value in the memory; the processor is further configured to search a corresponding index value of the finance and technology center in the memory according to the index analysis request of the finance and technology center, and respond to the user terminal through the communicator.
The network device and the user terminal may be in a C/S architecture or a B/S architecture, the network device provides a service of index analysis of the financial technology center to the user terminal through network communication, and may display, for example, the graphs of fig. 3a and fig. 3B to the user terminal according to a request.
The processor may be a general-purpose processor, and includes a Central Processing Unit (CPU), a Network Processor (NP), and the like; the device can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware component; the memory may include a Random Access Memory (RAM), and may further include a non-volatile memory (non-volatile memory), such as at least one disk memory; the communicator may be a wired or wireless communication circuit, such as a wired network card, a wireless network card, a 2G/3G/4G/mobile communication circuit, a bluetooth circuit, an infrared circuit, a Zigbee module, or a LoRa module.
In summary, the index analysis method, the storage medium, and the device of the financial technology center provided by the present invention construct a specific evaluation index framework for index analysis of the financial technology center, which includes: a plurality of index items; collecting city ranking report data and selecting sample cities from various cities involved in the city ranking report data; acquiring index data related to each index item in each sample city and the specific evaluation index frame; analyzing the city ranking report data and the index data by adopting a hierarchical analysis mode based on a scoring rule to determine the index weight of a target index item of a specific evaluation index frame, which is related to each element in the city ranking report data, and the standardized score of each sample city in the target index item; carrying out weighted sum according to the index weight and the standardized score to obtain the index value of the financial science and technology center of each sample city; the method can accurately display the strong and weak links of each city in the development of financial science and technology, and reveal development opportunities and the direction of effort so as to more purposefully promote the development work of financial science and technology.
The invention effectively overcomes various defects in the prior art and has high industrial utilization value.
The foregoing embodiments are merely illustrative of the principles and utilities of the present invention and are not intended to limit the invention. Any person skilled in the art can modify or change the above-mentioned embodiments without departing from the spirit and scope of the present invention. Accordingly, it is intended that all equivalent modifications or changes which can be made by those skilled in the art without departing from the spirit and technical spirit of the present invention be covered by the claims of the present invention.
Claims (15)
1. An index analysis method of a financial technology center, applied to a computer device, the method comprising:
constructing a specific evaluation index framework for index analysis of the financial science and technology center, wherein the specific evaluation index framework comprises the following steps: a plurality of index items;
collecting city ranking report data and selecting sample cities from various cities involved in the city ranking report data;
acquiring index data related to each index item in each sample city and the specific evaluation index frame;
analyzing the city ranking report data and the index data by adopting a hierarchical analysis mode based on a scoring rule to determine the index weight of a target index item of a specific evaluation index frame, which is related to each element in the city ranking report data, and the standardized score of each sample city in the target index item;
and carrying out weighted sum according to the index weight and the standardized score to obtain the index value of the financial science and technology center of each sample city.
2. The fsc index analysis method according to claim 1, wherein the analyzing the city ranking report data and the index data in a hierarchical analysis manner based on scoring rules to determine the index weight of the target index item related to each element in the city ranking report data of a specific evaluation index frame and the normalized score of each sample city in the target index item comprises:
calculating authority degree of each ranking report in the city ranking report data, matching degree between an index frame used by each ranking report and the specific evaluation index frame, and contribution degree of each city in each ranking report;
determining the elements related to the index items in the specific evaluation index frame in each ranking report according to the calculated matching degree;
calculating the importance degree between every two elements related to the index item in the specific evaluation index frame in each ranking report, wherein the importance degree is determined by the weight and the matching degree of each element related to the index item in the specific evaluation index frame in the ranking report;
constructing a judgment matrix according to the calculated importance;
and calculating the maximum characteristic root and the normalized characteristic vector according to the judgment matrix, carrying out consistency check, and obtaining the weight of each index item according to the characteristic vector under the condition of passing the check.
3. The index analysis method of the financial technology center according to claim 2, wherein the authority is calculated by:
wherein, the Australityllevel i : ranking the authority of report i; authority institution : the authority degree of the ranking issuing organization is obtained by the scoring of experts, and the range is (0, 1); year i : rank report i year of release; currentYear: the current year; year earlist : earliest reporting year included in the collection range; α: the weight adjustment factor.
4. The index analysis method of claim 2, wherein the specific evaluation index frame is distributed with one or more layers of index items, and the index item at the last layer includes one or more tool variables; the calculation mode of the matching degree comprises the following steps:
wherein, matchLevel i，j : matching degree, namely the similarity degree of the element j in the ranking report i and all index items in a specific evaluation index frame; matchelement i，j : the matching number of the tool variables contained in the element j in the ranking report i and the tool variables in the specific evaluation index frame; element: the number of tool variables in a particular evaluation index framework.
5. The index analysis method of the finance and technology center according to claim 2, wherein the calculation mode of the contribution degree includes:
wherein, the ContributeLevel i，city : ranking the contribution of the city in the report i; x is the number of city : the ranking reports the ranking of the city in i. α: an elasticity adjustment factor; beta: normalizing the adjustment factor; λ: a range adjustment factor.
6. The index analysis method of claim 2, wherein the determining the elements related to the index items in the specific evaluation index frame in each ranking report according to the calculated matching degree comprises:
judging whether the matching degree is greater than a preset value; if the number is larger than the preset value, the element is judged to be the relevant element.
7. The index analysis method of the finance and technology center according to claim 2, wherein the importance calculating means includes:
wherein, C i，a，b : for ranking report i, the importance between element a and element b; w i，a : the weight of element a in ranking report i; w is a group of i，b : the weight of element b in rank report i; matchLevel i，a : the matching degree of the element a in the ranking report i; matchLevel i，b : the matching degree of the element b in the ranking report i;
the W is i，a 、W i，b The calculation method comprises the following steps: in a ranking report, taking the contribution degree of a city as Y, taking the corresponding value of the relevant elements determined according to the matching degree as X, and obtaining a coefficient W used by the Y obtained by calculating the X through a regression algorithm, wherein the coefficient W is the weight; the regression algorithm includes: linear regression, logistic regression, or polynomial regression methods.
8. The index analysis method of claim 2, wherein the judgment matrix is calculated. The method comprises the following steps:
wherein, the Australityllevel i Is the authority; c i，a，b : for rank report i, the importance between element a and element b.
9. The fsc index analysis method of claim 2, wherein in case the consistency check fails, the city ranking report data is re-collected and the decision matrix is reconstructed therefrom.
10. The index analysis method of claim 1, wherein the type of the index comprises: one or more of a financial technology industry index, a financial technology experience index, a financial technology ecology index, and a composite index of any one or more of these indices.
11. The index analysis method of claim 10, wherein the specific evaluation index frame is distributed with one or more layers of index items, and the lowest index item includes one or more tool variables;
the first-layer index items corresponding to the financial technology industry index include: any one or more of a network credit industry index item, a crowd funding industry index item, a third party payment industry index item, a big data credit industry index item and a block chain industry index item;
each second-layer index item corresponding to the first-layer index item comprises: any one or more of the number of businesses, market size, capital strength, and talent supply sub-indicator terms;
each of the second-layer index items includes: for quantifying one or more tool variables representing the second layer metric term.
12. The index analysis method of the fsc as claimed in claim 1, wherein the collected index data is subjected to data processing, the data processing comprising: any one or more of data cleansing, correlation, and de-dimension.
13. A computer-readable storage medium on which a computer program is stored, the program, when executed by a processor, implementing the financial technology center index analysis method of any one of claims 1 to 12.
14. A computer device, comprising: a processor and a memory;
the memory is configured to store a computer program, and the processor is configured to execute the computer program stored by the memory to cause the computer device to perform the financial technology center index analysis method of any one of claims 1 to 12.
15. A network device, comprising: a processor, a memory, and a communicator;
the communicator is connected with the user terminal through a network so as to receive an index analysis request of the financial science and technology center;
the memory is used for storing a computer program;
the processor is configured to execute the computer program stored in the memory to cause the computer device to perform the index analysis method of the financial technology center according to any one of claims 1 to 12 to generate a financial technology center index value and store the financial technology center index value in the memory;
the processor is further configured to search a corresponding index value of the financial technology center in a memory according to the index analysis request of the financial technology center, and respond to the user terminal through the communicator.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108898531A (en) * | 2018-06-26 | 2018-11-27 | 深圳市亿道数码技术有限公司 | A kind of benefit information processing system and method based on block chain |
| CN110705820A (en) * | 2019-08-23 | 2020-01-17 | 上海市研发公共服务平台管理中心 | Scientific and technological innovation capability diagnosis report generation method and device, storage medium and terminal |
| CN112258027A (en) * | 2020-10-21 | 2021-01-22 | 平安科技（深圳）有限公司 | KPI (Key performance indicator) optimization method, device, equipment and medium |
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108898531A (en) * | 2018-06-26 | 2018-11-27 | 深圳市亿道数码技术有限公司 | A kind of benefit information processing system and method based on block chain |
| CN108898531B (en) * | 2018-06-26 | 2021-11-12 | 深圳市亿道数码技术有限公司 | Benefit information processing system and method based on block chain |
| CN110705820A (en) * | 2019-08-23 | 2020-01-17 | 上海市研发公共服务平台管理中心 | Scientific and technological innovation capability diagnosis report generation method and device, storage medium and terminal |
| CN112258027A (en) * | 2020-10-21 | 2021-01-22 | 平安科技（深圳）有限公司 | KPI (Key performance indicator) optimization method, device, equipment and medium |
| CN112258027B (en) * | 2020-10-21 | 2021-05-18 | 平安科技（深圳）有限公司 | KPI (Key performance indicator) optimization method, device, equipment and medium |
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