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Machine learning-based financial statement transnational accounting criterion conversion method

A financial statement and machine learning technology, applied in instrumentation, calculation, structured data retrieval, etc., can solve the problems of low efficiency, time-consuming, time-consuming, etc., to achieve high efficiency and reduce business costs.

Active Publication Date: 2019-12-03
深圳市原点参数信息技术有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0013] Time-consuming and inefficient
[0014] Because relying on the professional judgment and manual operation of personnel, it takes a lot of time and the efficiency is not high

Method used

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  • Machine learning-based financial statement transnational accounting criterion conversion method
  • Machine learning-based financial statement transnational accounting criterion conversion method
  • Machine learning-based financial statement transnational accounting criterion conversion method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0057] A method for transnational accounting standards conversion based on machine learning financial statements, characterized in that:

[0058] Collect and store financial data such as balance sheets, profit statements, cash flow statements, other comprehensive income statements, and financial notes of companies in different countries around the world, and classify and manage all data according to preset rules;

[0059] Form a knowledge base from various financial information, access the knowledge base through machine learning, learn accounting standards between industries in different regions, and understand the relationship between subjects and subjects, and between reports and reports;

[0060] Form specific conversion rules according to different accounting standards, report structures, and subject relationships and classifications, and store the conversion rules in the corresponding relationship library;

[0061] Realize the automatic conversion of accounting standards ...

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Abstract

The invention provides a machine learning-based financial statement transnational accounting criterion conversion method. The method comprises the steps that a big data platform collects and stores global financial statement data of different countries, different languages and different industries over the years, and all the data are classified and managed according to preset rules. A machine (algorithm) embedded in a program accesses a big data platform to learn accounting criteria of different countries and different industries, each subject in accounting reports and logical relationships among the subjects, such as hierarchical relationships divided into first-level relationships, second-level relationships, third-level relationships and the like, and association relationships among thereports, such as relationships among an asset debt table, a profit table and a cash flow table. Conversion rules are formed through automatic learning of accounting criteria, accounting report tablestructures, subject classification and report relations of different countries. Based on the conversion rules, automatic conversion of accounting criteria is realized through a background algorithm.

Description

technical field [0001] The invention relates to the field of financial tools, in particular to a method for transnational accounting standard conversion of financial statements based on machine learning. Background technique [0002] Current status: [0003] In the financial industry, when it comes to industry analysis, enterprise analysis or cross-border investment, financial institutions such as banks, securities companies, fund companies, and investment companies need to perform cross-border (accounting standards) conversion of corporate financial statements. [0004] The most common method at present is to entrust a professional accounting firm to handle it. After receiving relevant tasks, the experts of the accounting firm: [0005] First, determine the country of the enterprise to be converted before and after the conversion, as well as the industry attributes in the respective countries, the reporting period (year) and other information. [0006] Secondly, the acco...

Claims

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Application Information

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IPC IPC(8): G06F16/22G06F16/2455G06F16/28G06Q40/00
CPCG06F16/2282G06F16/24564G06F16/284G06Q40/125Y02P90/30
Inventor 叶利亚张小苑韩晓芊薛逸竹
Owner 深圳市原点参数信息技术有限公司
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