In rural commercial banks, the decision analysis system in the business intelligence system generally has the following construction requirements:
1. Establish a unified and long-term data platform to analyze historical data trends, month-on-month, year-on-year, etc.;
2. Effectively process and analyze the analysis reports required by the data management department according to the subject requirements;
3. Express business data through rich graphic display, so that leaders can understand the business situation more intuitively and comprehensively. ;
4. Effectively use data, mine and analyze the analysis data required by the management department, and provide a scientific and effective basis for the decision-making of behavior leaders.
In the construction of decision analysis system, we also need to follow the following principles:
1. Guided by the decision-making analysis of line leaders, it is displayed through the system to provide data support for operation and management;
2. The business scope is based on deposits, loans, and income-oriented analysis methods, and drills layer by layer based on data permissions at all levels;
3. The system uses time points and daily averages as elements to process the period (beginning of the year, the beginning of the month, the beginning of the quarter, and yesterday) on a year-on-year basis, month-on-month, drilling, and linkage;
4. The main display methods are different according to the business, for example, they can be displayed through bar charts, line charts, and pie charts respectively;
5. The system is based on practicality and is guided by the direction of line management.
Rural commercial bank decision-making system analysis dimension example
Dimensional description of several typical bank decision-making systems
target sales
Mainly use the forecasting model to determine and select the sales target and target;
Risk Analysis
The method of data mining has been widely used in the establishment of risk models, including approval model, behavior model, overdue model, bankruptcy model, etc.;
Customer Profit Contribution Analysis
Determine the distribution of gold customers, profit-making customers and non-founding customers according to the estimation model and customer contribution analysis;
Analysis of Bank's Key Operational Indicators
Including comparative analysis of changes in indicators such as deposits, loans, and non-performing assets;
Estimated credit value / potential value
It has been widely used in North America, mainly through the analysis of the potential value of customers, which helps banks to adopt different strategies according to the level of customer credit value and potential value;
predictive analytics
Forecast is mainly used for sales forecast, interest rate forecast and cost forecast. The use of data mining methods will greatly improve the bank's future planning and management level.