Method for automatically generating financial data demand specification

Abstract

The invention discloses a method for automatically generating a financial data demand specification. The method comprises the following steps: determining a source of financial data extraction demand information; cleaning and formatting the identified demand information to reduce invalid texts; a natural language processing technology is utilized, and a uniform input outlet is adopted to ensure the uniqueness of a data source and the accuracy of data; and finally, forming normalized and quantifiable data. Forming financial data indexes according to the data, and analyzing dependency, conflicts and priorities among the financial data indexes; verifying the consistency, completeness and accuracy of the generated demand document; verification is carried out through an evaluation system, and evaluation prompts can be divided into very conformity, basic conformity, conformity, non-conformity and complete non-conformity from high to low; and iterative optimization is carried out according to use feedback until a preset condition is met, and the method is ended. The method has the technical characteristics that a good support can be provided for a subsequent data mining process, and the participation degree of technicians is possibly reduced.

Description

Technical Field

[0001] The present invention relates to a generation method, and more specifically, to a method for automatically generating a financial data requirement specification, and belongs to the fields of computer technology and finance. Background Art

[0002] With the continuous growth of financial business, the importance of financial data requirements specifications in banking operations has become increasingly prominent. However, the traditional manual writing method is time-consuming, labor-intensive and prone to errors. At present, the implementation schemes for the automatic generation of financial data requirements specifications mainly include semi-automatic generation, requirements improvement generation and semantic generation schemes. Although the semi-automatic generation scheme simplifies the creation process of the requirements document, it still requires human participation. The requirements improvement method is based on a large amount of data calculation and proposes improvement directions to users, while the semantic generation scheme combines natural language processing and requirements engineering, and continuously optimizes and improves through dialogue to generate requirements documents more intelligently. However, this scheme still needs further development in specific professional fields to better meet the current diverse needs. Summary of the invention

[0003] The purpose of the present invention is to realize the automatic generation of a set of requirement specifications in the field of financial data use, and to provide a method for automatically generating financial data requirement specifications.

[0004] In order to achieve the above object, the present invention is implemented by the following technical solutions:

[0005] The present invention provides a method for automatically generating a financial data requirement specification, the method comprising the following steps:

[0006] Step 101, identifying the source of demand: determining the source of the financial data extraction demand information, which includes documents, emails, and meeting minutes;

[0007] Step 102, preprocessing the collected data: cleaning and formatting the identified demand information to reduce invalid text, the cleaning and formatting includes text cleaning, noise data removal, and standardization;

[0008] Step 103, financial data mapping: including financial data information identification and demand normalization, wherein financial data information identification: using natural language processing technology, including keyword extraction, entity identification, the data used in this step depends on the data processed in step 102, eliminating non-financial data fields, and identifying financial data field information; demand normalization: financial data standardization, using a unified input and output to ensure the uniqueness of the data source and the accuracy of the data; finally, forming standardized and quantifiable data;

[0009] Step 104, demand arrangement and classification: forming various financial data indicators according to the data in step 103, and analyzing the dependencies, conflicts and priorities between the financial data indicators;

[0010] Step 105, requirement verification: verify the consistency, completeness and accuracy of the generated requirement document; verify through an evaluation system, and the evaluation reminders can be divided into: very consistent, basically consistent, consistent, inconsistent, and completely inconsistent;

[0011] Step 106, document generation and optimization: according to the requirements of step 104, a template document is formed, and iterative optimization is performed according to the usage feedback and step 105. If it does not meet the preset requirements, return to step 101 until it meets the preset requirements and end.

[0012] Preferably, there is also pattern recognition between steps 103 and 104: specific needs are identified according to preset financial data demand patterns or bank-specific rules (banks have their own terms for data descriptions, and the rules vary from bank to bank, such as AUM).

[0013] Preferably, the specific requirements include identifying transaction information, and the transaction information includes amount, debit and credit marks, payer, payee, time, etc.

[0014] Preferably, the financial data mapping includes an alias library, the data in the alias library contains fields, and the fields include English name, Chinese name, and number.

[0015] Beneficial effects: By adopting the technical solution of the present invention, financial institutions can improve production efficiency, enhance business support capabilities, and reduce error rates; the present invention standardizes financial data, can provide good support for subsequent data mining processes, and makes it possible to reduce the involvement of technical personnel; the present invention is suitable for financial institutions of various sizes and has wide application value. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is the overall flow chart of the present invention.

[0017] Figure 2 It is a data mapping relationship design diagram in the present invention. DETAILED DESCRIPTION

[0018] The present invention will be further described below in conjunction with the accompanying drawings, but the present invention is not limited to the following embodiments.

[0019] The purpose of the present invention is to realize the automatic generation of a set of requirement specifications in the field of financial data use, and to provide a method for automatically generating financial data requirement specifications.

[0020] like Figure 1-2The figure shows a specific embodiment of a method for automatically generating a financial data requirement specification, a method for automatically generating a financial data requirement specification, the method comprising the following steps:

[0021] Step 101, identifying the source of demand: determining the source of the financial data extraction demand information, which includes documents, emails, and meeting minutes;

[0022] Step 102, preprocessing the collected data: cleaning and formatting the identified demand information to reduce invalid text, the cleaning and formatting includes text cleaning, noise data removal, and standardization;

[0023] Step 103, financial data mapping (the financial data mapping includes an alias library, and the data in the alias library contains fields, and the fields include English name, Chinese name, and number): including financial data information identification and demand normalization, wherein financial data information identification: using natural language processing technology, including keyword extraction and entity identification, the data used in this step depends on the data processed in step 102, eliminating non-financial data fields, and identifying financial data field information; demand normalization: financial data standardization, using a unified input and output to ensure the uniqueness of the data source and the accuracy of the data; finally, forming standardized and quantifiable data;

[0024] Pattern recognition: Identify specific needs based on preset financial data demand patterns or actual designed special rules. Specific needs include identifying transaction information, which includes amount, debit and credit marks, payer, payee, and time.

[0025] Step 104, demand arrangement and classification: forming various financial data indicators based on the data in step 103, and analyzing the dependencies, conflicts and priorities between the financial data indicators;

[0026] Step 105, requirement verification: verify the consistency, completeness and accuracy of the generated requirement document; verify through an evaluation system, and the evaluation reminders can be divided from high to low into: very compliant, basically compliant, compliant, non-compliant, and completely non-compliant.

[0027] Step 106, document generation and optimization: according to the requirements of step 104, a template document is formed, and iterative optimization is performed according to usage feedback and related rules. If it does not meet the preset requirements, return to step 101 until it meets the preset requirements, and then end.

[0028] Finally, it should be noted that the present invention is not limited to the above embodiments, and there are many variations. All variations that can be directly derived or associated with the content disclosed by ordinary technicians in this field should be considered as the protection scope of the present invention.

Claims

1. A method for automatically generating a financial data requirement specification, characterized in that The method comprises the following steps: Step 101, identifying the source of demand: determining the source of the financial data extraction demand information, which includes documents, emails, and meeting minutes; Step 102, preprocessing the collected data: cleaning and formatting the identified demand information to reduce invalid text, the cleaning and formatting includes text cleaning, noise data removal, and standardization; Step 103, financial data mapping: including financial data information identification and demand normalization, wherein financial data information identification: using natural language processing technology, including keyword extraction, entity identification, the data used in this step depends on the data processed in step 102, eliminating non-financial data fields, and identifying financial data field information; demand normalization: financial data standardization, using a unified input and output to ensure the uniqueness of the data source and the accuracy of the data; finally, forming standardized and quantifiable data; Step 104, demand arrangement and classification: forming various financial data indicators according to the data in step 103, and analyzing the dependencies, conflicts and priorities between the financial data indicators; Step 105, requirement verification: verify the consistency, completeness and accuracy of the generated requirement document; verify through an evaluation system, and the evaluation reminders can be divided into: very consistent, basically consistent, consistent, inconsistent, and completely inconsistent; Step 106, document generation and optimization: according to the requirements of step 104, a template document is formed, and iterative optimization is performed according to the usage feedback and step 105. If it does not meet the preset requirements, return to step 101 until it meets the preset requirements and end.

2. The method for automatically generating a financial data requirement specification according to claim 1, characterized in that: There is also pattern recognition between steps 103 and 104: identifying specific needs according to a preset financial data demand pattern.

3. The method for automatically generating a financial data requirement specification according to claim 2, characterized in that: The specific requirements include identifying transaction information, and the transaction information includes amount, debit and credit mark, payer, payee, and time.

4. The method for automatically generating a financial data requirement specification according to claim 1, characterized in that: The financial data mapping includes an alias library, and the data in the alias library contains fields, and the fields include English name, Chinese name, and number.

Images