Predictive Analytics – Peering into the future
 Radar provides a ship captain with the ability to see ahead, to get a glimpse of the future. Using radar they can see obstacles that lie ahead and steer clear of them to move forward safely. They can see storms and potential dangers that enable them to make informed decisions and determine the best, quickest and safest path to their final destination. Predictive Analytics provides similar capability for businesses today.
Transactional, historical and other types of data are used to make predictions on future events, processes and behaviors. Statistics, data mining tools, multidimensional data and complex algorithms are used to develop predictive models. Predictive Analytics can be used in business to identify risks and opportunities.
A simplified overview of predictive model development includes the following steps – Data is collected, predictors are identified and a statistical model is formulated and validated. Once validation is complete the model can forecast future probabilities with acceptable levels of performance. Models capture relationships among factors that allow assessment of risk or potential associated with a particular set of conditions, these models can guide the decision making process for different types of transactions. Over time these models need to be revised and re-validated to ensure they continue to predict future actions and activities.
Predictive Analytics was used to develop credit scoring in the financial services market. Predictive Analytics applies to virtually any business scenario. HELM Analytics Predictive Analytics capabilities include data modeling, business process automation and data capture optimization. Predictive models can be used to increase marketing effectiveness. They can be used to determine data patterns that address questions about customer performance, fraud and compliance considerations. Predictors are a central element of Predictive Analytics. Insurance companies use predictors such as age, gender, driving record, even FICO score as predictors when making car insurance policy decisions.
Predictive Analytics helps identify consumers with a higher probability response to targeted marketing efforts. Predictive Analytics can also be used to reduce liability and business exposure to fraud. Businesses must account for risk exposure and associated costs. Auto insurance providers must accurately determine premium amounts, financial companies must assess a borrower’s ability to pay back a loan, health insurance providers use predictive analytics to determine probable future medical claims coverage activity. Predictive Analytics predicts the possible risks associated with each scenario.
Commercial applications of Predictive Analytics are all inclusive such as, modeling, customer retention, product recommendations, marketing optimization, behavior-based advertising, email targeting, insurance pricing, credit and behavioral scoring, insurance, the list is limitless.
HELM AnalyticsTM capabilities and expertise can help your organization optimize:
- Compliance Automation
- Business Process Automation
- Customer Relationship Management (CRM)
- Decision Support Systems
- Collections
- Portfolio Optimization
- Cross-sell & Up sell Strategy Development
- Customer Retention
- Direct Marketing
Our Analysis and Data Mining Solutions support Predictive Analytic program development. We have experience in proprietary and commercial score development and implementation for multiple industries. Our solutions help maximize historical data and turn it into business intelligence to help you increase effectiveness and efficiency, steer clear of hazards and help your organization see into the future.
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