Predictive Modeling and Predictive Analysis

Predictive Analytics

Most would agree that predictive analytics encompasses a variety of statistical techniques from modeling, machine learning, data mining and game theory that analyze current and historical facts to make predictions about future events.

In business, predictive models exploit patterns found in historical and transactional data to identify risks and opportunities. Models capture relationships among many factors to allow assessment of risk or potential associated with a particular set of conditions, guiding decision making for candidate transactions.

Predictive analytics is used in actuarial science, marketing, financial services, insurance, telecommunications, retail, travel, healthcare, pharmaceuticals and other fields.

The Future Beholds...The Mightiest

Off-late,  major iGiants like Google and Facebook have made big bets with the commercialization of Predictive Models and Predictive Analytics. Take a look at Google's Prediction API. I have myself used Google's Prediction API mostly for my personal R&D and private ventures and have been quite satisfied with not only the quality of output but also the thought of the endless possibilities of prediction. 

What are all the things that I can predict? 

And what are all the things that I can very accurately predict?

These were questions that we used to ask. 

Today, the mightiest ask "What can I not predict?" Has the world really come to it that almost anything, but anything, can be predicted with the near certain guarantee that the chance of false prediction is nearly as bad as the odds of winning a lottery jackpot.

Predictive Models

Predictive models analyze past performance to assess how likely a customer is to exhibit a specific behavior in the future in order to improve marketing effectiveness. This category also encompasses models that seek out subtle data patterns to answer questions about customer performance, such as fraud detection models. Predictive models often perform calculations during live transactions, for example, to evaluate the risk or opportunity of a given customer or transaction, in order to guide a decision. With advancement in computing speed, individual agent modeling systems can simulate human behavior or reaction to given stimuli or scenarios. The new term for animating data specifically linked to an individual in a simulated environment is avatar analytics. 

Applications

Although predictive analytics can be put to use in many applications, we outline a few examples where predictive analytics has shown positive impact in recent years.

• Analytical customer relationship management (CRM)
• Clinical decision support systems
• Collection analytics
• Cross-sell
• Customer retention
• Direct marketing
• Fraud detection
• Portfolio, product or economy level prediction
• Risk management
• Underwriting

What's wrong with this list?


One of the most important areas to man-kind that could benefit the most from the recent advancements in predictive modeling is health information technology.
 
  
References:

1. Wikipedia::Predictive Analytics & Modeling
2. Google's Prediction API