Predictive Modeling

Predictive modeling is not only commonly used statistical technique to predict future behavior, it is a huge asset for any large or small business. First step in predictive modeling is the data collection upon which the statistical model is formulated. Predictions and forecasts are made based on the original training data set, and the model is validated or enhanced as additional data becomes available. Usually predictive models analyze past performance based on the historical data that is available to assess how likely a customer is to exhibit a specific behavior in the future.

By “listening” to the data and identifying subtle data patters, predictive modeling solutions enable companies to anticipate and address any market shifts, predict consumer preference changes, and prepare for new market trends. Predictive credit risk models can combine internal to the firm and external data from credit bureaus as well as customer lifestyle information from additional external sources to improve underwriting accuracy, credit limit assignments, portfolio profitability etc. Nowadays multiple fraud detection models are performing calculations and make predictions during live transactions to evaluate the risk of opportunity of a given customer or transaction to guide a decision. In modern, extremely competitive marketplace the use of predictive models can position a company for a successful growth trajectory and allow the firms to discover untapped niche markets based on their data-driven decisions.