Risk Management and Deep Learning

Good news! You can develop Decision Support Expert Systems using Deep Learning techniques very easily. What you need is relevant data for Deep Learning.

Risk management is an important area for financial industry. To know how Predictive Modeling and Deep Learning can be used for risk management, recommend to read the following pages;

• Credit risk prediction
  
• Credit risk predictive modeling
  
• Credit risk machine learning
  
• Credit risk deep learning
  
• Insurance claims prediction
  
• Insurance claims predictive modeling
  
• Insurance claims risk machine learning
  
• Insurance claims risk deep learning
  

Big Performance Enterprise Solutions

Rosella predictive modeling provides complete enterprise solutions from model development to model deployment over web and Android devices. High performance web server and powerful neural network and RME-EP combination can be essential for enterprise risk management. For more information on risk management and predictive modeling, please visit the following links;

• Credit risk modeling
  
• Insurance risk modeling
  

Big Data Analytics

CMSR Data Miner / Machine Learning / Rule Engine studio provides reporting tools and data visualizations, supporting advanced techniques such as regession with smoothing, seasonal adjustment, and hotspot visualization.

For more, please read Big Data Analytics.

Database Marketing

Customer database provides rich customer information. Predictive analytics can identify customer tendencies which can be used in developing marketing plans;

• Sales trend analysis and sales forecasting (Excel Addin Tools)
  
• Time series analysis and tools
  
• Database marketing
  
• Customer segmentation
  
• Direct mail catalog marketing
  
• RFM marketing
  

Marketing Survey Research

Marketing survey research is essential part of marketing. Predictive analytics can automatically identify important factors from survey data and build predictive models. For more, please read marketing survey analysis.