Predictive Analytics is based on an AI technique called Machine Learning. To put it in short, ML is the science of looking for patterns in data. Machine Learning provides algorithms that can build a mathematical model of your data.
Our platform Cerescope has capabilities to store and process the data that is used in Predictive Analytics, but the key skill here is to work with large amount of data. Our expertise lies in curating, processing and analyzing such large amount of data and coming up with correct models. Also, predictive analytics is another use for the structured data can be put to.
Knowing future is vital for any organization, especially if the future is about the demand for its goods. Using past data, we can build models of future demand. These are not only used to decide what to stock more, but also to decide what should occupy the more important shelves.
Failure of an equipment is disastrous for many industries such as healthcare, power and heavy engineering. A working estimate of failures in the machinery can not only save time and money, but can become the difference between life and death sometimes.
Every claim received by the insurer needs to be scrutinized. This requires time and effort by skilled manpower. If there is a preliminary triaging of the claims, separating the ones that look suspicious from the one that look benign can save cost and time. Predictive Analytics can do this job.
In industries like finance and pharmaceuticals, measuring the risks correctly is important. While this is similar to failure prediction, the data to be processed is very different. Accurate risk assessment can induce a degree of confidence in the organization.