Knowledge base solution accelerator for consolidating
To do this effectively, organizations must first identify and quantify their risk levels. Streamline and integrate your claims processing. Best of all, you can easily add components and functionality as your needs change. Features Statistical and analytical functions enabled for in-database processing.
This inefficiency is exacerbated by the use of aging in-house claims management tools and lack of integration between systems. The massively parallel architecture of data warehouses is useful for processing larger, more complex information sets. This type of in-database processing reduces the time needed to build, execute and deploy powerful predictive models.
For some, this may seem an insurmountable challenge. They must better manage and mitigate risk. The system lets you work strategically with outside counsel to manage legal expenses and optimize outcomes while ensuring efficiency and consistency. Understanding past claims can help prevent or mitigate future losses, and shortening claims cycle times can reduce potential litigation exposure and lower overall expenses. Modelers can easily add new sets of variables if model performance degrades or changes are needed for business reasons.
Enhance the productivity of analytic teams. It also increases the utilization of the enterprise data warehouse or relational database to reduce costs and improve the data governance that is required for successful analytics applications.
Improve accuracy and achieve better outcomes using more data points and sophisticated analytical models. These organizations need to fundamentally change the way they gather data and evaluate information. Managing claims can be an onerous manual process for organizations, especially for those using older, inflexible systems. Achieve faster time to results by building, updating and deploying models more quickly. It also reduces the latency and complexity associated with the model development process.
You also can create application files and modules to address your specific needs. No other package integrates onto one platform so many functions from the same vendor. In-database analytics helps modelers, data miners and analysts focus on developing high-value modeling tasks instead of spending time consolidating and preparing data. This delivers faster time to results and provides better insights for improved business decision making.
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