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HELM360’s Predictive Analytics Solution – Peering into Your Future
HELM360’s Predictive Analytics solution gives you the ability to see ahead and intelligently guide the business in the future. Using our expertise, clients operating in a variety of different industries with different issues 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.
Our solution uses transactional, historical and other types of data to make predictions on future events, processes and behaviors. Statistics,
data mining tools, multi-dimensional data and complex algorithms are used to develop predictive models. Predictive Analytics can be effectively used by business people to identify risks and opportunities.
A simplified overview of HELM360’s predictive model development includes the following steps: the data is collected, predictors are identified and a statistical model is then formulated and validated. Once validation is complete, the model can forecast future probabilities with acceptable levels of performance. Models capture relationships among factors that assess the 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 applies to virtually any business scenario in any industry. HELM360’s Predictive Analytics capabilities include
data modeling, business process automation and data capture optimization. Predictive models can also be used to increase marketing effectiveness. They can be used to determine data patterns that address questions about customer performance, risk, fraud and compliance considerations. Predictors are a central element of Predictive Analytics. As an example, insurance companies use predictors such as age, gender, driving record and even FICO score as predictors when making car insurance policy decisions. In another example, Predictive Analytics has successfully been used to develop credit scoring and risk assessment models in the financial services industry.
Predictive Analytics helps identify consumers with a higher probability of 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 services companies must assess a borrower’s ability to pay back a loan. Health insurance providers must determine probable future medical claims coverage activity. Predictive Analytics foresees 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 and more. The list is endless. |
