Enterprise value evaluation cloud service system

Abstract

The invention provides an enterprise value evaluation cloud service system. The system comprises a data entry module which is used for entering enterprise information data, including a valuation mode,an industry to which an enterprise belongs and recent main financial data, or selectively entering data, including a business mode of the enterprise, a core team, intangible asset information, data asset information and information which is considered to be helpful for evaluation, wherein the entered data is stored in a database; a valuation process management module which is used for calling theinput enterprise information data from the database, selecting a valuation mode, analyzing the input data, selecting an evaluation method and processing to obtain result data; and a storage module which is used for storing the valuation process and the result data into a database according to a standard format. By adopting a structure combining automatic process management, a machine learning parameter estimation model, scene simulation, an intelligent decision-making system and a classic value estimation model, the problem that non-professional evaluation personnel carry out rapid enterprisevalue evaluation is solved.

Description

technical field [0001] The present invention relates to the technical field of value evaluation, in particular to an enterprise value evaluation cloud service system. Background technique [0002] The present invention is an online system, which can automatically search and match relevant Internet public information, database data, etc. according to the enterprise information and data input by users, and apply scenario simulation and valuation models to calculate enterprise valuations and output valuations Process and results data can support automated valuation reports. The present invention replaces the traditional process of manual valuation, avoids the work of manual collection, sorting, analysis, and reporting, and does not require users to have relevant knowledge and experience in valuation, and can standardize and store valuation-related data for easy query , compare, analyze and trace. At the same time, due to the avoidance of manual intervention, the valuation res...

AI Technical Summary

Problems solved by technology

There are disadvantages: (1) Relying on estimated parameters provided by users, or simply using historical parameters as estimated parameters, the prediction method for future conditions is too simple; (2) The standardization requirements for input data are too high, and non-standard data cannot be applied; (3) Neglecting the free decision-making power of enterprise managers; (4) Cannot freely call the modular evaluation method according to the actual situation

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