Unfortunately, the claims process is typically time-consuming and labor-intensive, involving
multiple systems, and often outdated technology. The resulting inconsistent processes and
inefficient data management sap resources and slow turnaround times, which leads to a
poor claims experience. Fortunately, in recent years many organizations have invested in
claims management solutions to improve the operational side of the claims process.
However, despite the success of these solutions, most organizations have not realized the
expected benefits from these projects because they have often neglected the vast amounts
of information that is held within the claims process. This is partially because as much as
80% of claims data consists of unstructured data, such as adjuster notes, medical records
and police reports. And now add to this the growing number of digital content pieces such as
photos and videos.
This research paper will provide risk managers, claims leaders IT personnel and C-level
executives with how to use AI and predictive analytics to analyze both structured and
unstructured data at each stage in the claims cycle to enhance claims processing.
Of all the processes inherent to risk management and insurance,
it could be argued that none are more important than
the claims process.
OPTIMIZING CLAIMS | 1
