Business decision-making method and system based on rule engine and storage medium

Abstract

The invention discloses a business decision-making method and system based on a rule engine and a storage medium, and the method comprises the steps: a rule configuration server side deploys business configuration rule information in real time according to a rule strategy set pre-configured by a business side, and stores the business configuration rule information to a database, different resources are independently simulated and tested according to different resources, a result is output, and service configuration rule information is sent to a rule execution server; and the rule execution server executes a corresponding strategy according to the model data sent by the service calling party and the service configuration rule information, and outputs a decision result. The method can get rid of the great dependence of the traditional operation decision on business personnel and IT personnel, reduces the enterprise cost, reduces the learning cost of a decision engine system, achieves the real simplicity, rapidness and easy operation, shortens the strategy release period, and deals with the environment change in real time.

Description

technical field [0001] The present invention relates to the technical field of rule engines, in particular to a rule engine-based service decision method, system and storage medium. Background technique [0002] Developed from the inference engine, the rule engine is a component embedded in the application, which separates business decisions from application code and writes business decisions using predefined semantic modules. Accept data input, interpret business rules, and make business decisions based on business rules. [0003] The existing technology is to configure the data model corresponding to the business side through the rule configuration server, abstract resources corresponding to different scenarios, such as rule sets, single-axis decision tables, dual-axis decision tables, functions, score cards, etc., and use decision flow to connect all Resources form a whole for rule execution. [0004] At present, complete decision-making requires a complex human review ...

AI Technical Summary

Problems solved by technology

[0004] At present, complete decision-making requires a complex human review process, and the decision-making cycle is uneven. It is difficult for enterprises to carry more business under limited resources.

The human review process requires a large number of high-quality personnel to ensure the timeliness and accuracy of the review. Due to lack of personnel and mistakes in decision-making based on subjective experience, it is easy to cause business losses

And because the policy and market environment are changing rapidly, the response is not timely, resulting in a lag in policy adjustment

Mixed development rules by business personnel and IT personnel cannot provide a private black box environment for risk control technology, and there is a risk of leakage

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