The marketing platform of a city commercial bank
The bank wants to deeply explore and analyze the business data of its retail business, retail customer base, enterprise customers, and credit-card loans.
As projects usually involve a wide range of areas, limited human resources cannot cover numerous data mining modeling demands and heavy modeling tasks. By setting up an automated modeling platform with Model Magic, the efficiency of modeling work is improved and models are launched more quickly. As a result, customers can meet diverse business needs and simultaneously capitalize on marketing opportunities.
A new fund purchase forecast model is built to provide a marketing list for the initial fund launched monthly and to achieve accurate hit.
Forecast on capital demand
Customers with high capital demand sought by establishing a capital forecast model
Mining of potential customers of credit
The success rate of marketing response is improved through the use of a marketing-response model that helps the screening of credit white-listed customers.
Customer churn alert model
The customer churn probability upon the maturity of a given loan product is predicted through the use of a customer churn alert model. One can also formulate corresponding strategies for prevention.
Customer group operation
Analyze life-cycle operations, including customer life-cycle management, marketing management, and product service management for health insurance cardholders to improve the overall AUM.
Credit-card collection model
The overdue probability of customers migrating from M1 to M2 is scored by setting up the credit card collection risk model (Card C)
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