Bank dynamic credit monitoring system based on wireless sensing network and method

Abstract

The invention provides a bank dynamic credit monitoring system based on a wireless sensing network. The monitoring system comprises multiple wireless monitoring base stations, a wireless acquiring server, an automobile balance controller, a local monitoring server, a bank front-end processor and a credit management server. The wireless monitoring base stations are disposed to all enterprises and are connected with the wireless acquiring server and the local monitoring server. The local monitoring server is wirelessly connected with the bank front-end processor which is connected with the credit management server. The wireless monitoring base stations and the automobile balance controller respectively acquire and then send enterprise special index data and stocking and sales volume scale data to the credit management server which will carries out loan client rating. According to the invention, dynamic production and operation state data of enterprise clients are added as quantitative non-financial index, so continuous tracking for credit granting clients and credit assets is achieved and credit rating is scientifically and properly evaluated.

Description

technical field [0001] The invention relates to the technical field of bank credit, in particular to a wireless sensor network-based dynamic bank credit monitoring system and method. Background technique [0002] The credit management system is an important business system for banks to grant credit loans to customers and manage their debts throughout the process. It generally includes basic modules such as customer management, credit rating (including customer rating), survey application, contract management, account management, post-loan management, and risk classification. These subsystems constitute pre-loan management, loan management, and post-loan management. Among them, customer rating is a periodic rating of credit customers (generally, corporate customers are rated once a year, and individual customers are rated once every two years), and different credit lines are corresponding to different credit ratings according to the rated credit rating; risk classification is...

AI Technical Summary

Problems solved by technology

In the first- and second-tier cities, most of the offices of industrial credit customers are located in the suburbs of the city. In the third- and fourth-tier cities, banks’ financial service outlets cannot effectively cover

This directly leads to the fact that credit customers are far away from bank outlets

Relying on manpower to carry out credit rating requires a lot of manpower, material resources, and financial resources to complete, which directly increases the cost of credit rating

[0010] Second, there is a lag in credit ratings

[0011] Third, credit ratings cannot reflect changes in customers' credit ratings, and proactively reveal risks

With the rapid development of the economy, the customer's business conditions may undergo several drastic changes within a year, and the credit rating once a year cannot effectively reflect the changes in the customer's credit rating.

When the customer has serious credit problems during the year, the customer's risk cannot be disclosed in a timely and proactive manner. Before the credit rating is carried out at the end of the year, the customer is unable to repay the loan, resulting in the unrecoverable loan

[0012] Fourth, the data collected by credit ratings is inaccurate

There is also a risk of misinformation transmission in the transfer of information from manually collected databases to credit rating systems

[0013] Fifth, the data collected by credit rating is not comprehensive

In credit rating, if the production characteristics of the enterprise are not effectively used, bias will inevitably occur

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