Identifying High Cost Claims with Predictive Analytics

Identifying High Cost Claims with Predictive Analytics

Infinilytics’ Charlee™ Search Brings Insights on Multiple Levels

If you could search your claims database for insights that will allow you to reduce indemnity and loss adjustment expense, what would you search for?  Basic insights[1] can be mined from the structured data fields in your claims management system. But what about the vast amounts of information in the unstructured text in claim and policy files? How do you obtain these insights? Harnessing artificial intelligence machine learning with a semantic search engine can bring these valuable insights that are missed by claims management systems.

Introducing the Charlee™ Search Insights Engine for Insurance

Infinilytics has built the first insurance insights engine[1] for the insurance industry. An insights engine is a powerful tool to extract insights from a variety of structured and unstructured data. The Charlee™ Search insights engine was trained on over 35 million claims and has 3,000 insights ready to go when deployed. The Infinilytics Team has created and built the required ontology[2] for the insurance claims process.  There is also a powerful semantic search capability for words and phrases utilized in categorizing the types of loss, causes of loss, and the unique characteristics for each type of claim in each line of business.

One of the most powerful things you can do with artificial intelligence analytics is the speed and accuracy of analyzing the millions of data points within your claims system and discovering the patterns and trends contributing to high cost claims.

For example, the traditional “soft tissue injury” can be one of the most expensive claims and lead to high settlements and litigation if it is not correctly processed.  Let’s explore how the Charlee™ Search Insights Engine can bring value to your claims process by reducing allocated loss adjustment expenses, and litigation costs associated with these types of claims.

How does Charlee Search work?

A typical challenge that most claims managers face is to identify risk exposure patterns. These patterns are often hidden in unstructured data (claim notes, documents, etc.), which makes analytics on these topics very challenging. Charlee, with its pre-built models and artificial intelligence, automatically extracts entities, topics and patterns from unstructured data. The Charlee™ Search automatically aggregates these patterns and provides users the ability to start with simple Google-like searches with machine learning to identify loss drivers, fraud and litigation patterns. The pending claims that exhibit these patterns can very quickly be assigned to a senior team member or SIU.  In addition, as appropriate, reserves can be adjusted, fraud investigated and litigation managed effectively.

Cracking the Insight Shell

Let’s take a look at one of the most common and expensive loss types…soft tissue injuries.  Muscle strain and sprain injuries to the neck and back can be caused by a wide variety of traumatic events, whether as a result of an automobile accident or accidental injury to a visitor in your home or a customer in your business.  The Charlee™ Search solution allows managers to examine the frequency and severity of such claims, quickly identify the key topics and events in these claims that make them expensive, plus identify associated entities (i.e., law firms, medical providers, possible fraud rings, etc.) that are preying on your company.

The Charlee™ Search solution has the ability to graphically show loss trends, severity and much more, in a highly customizable format tailored to your needs.  It can also perform comparative analysis on a carrier’s closed claims data against open claim data!

The Charlee™ Search solution gives the claims management team important historical data insights that can assist in prioritizing current claims resource assignments.  For example, if a specific law firm consistently shows up in minor impact or otherwise low-level soft tissue injury claims, but the settlement and litigation costs are disproportionally high, a more senior level claims examiner can be assigned at the outset of any current or future claims involving these parties, thereby effectively managing overall claim costs.  Once Charlee™ Search solution is added to your claims management system you will be able to apply its powerful insights at scale, thereby reducing applicable indemnity costs, lower allocated adjustment expense and streamline your claims process.

Moving Forward

Now is the time to place the Charlee™ Search solution on top of your claims repository to discover the insights which have been hiding from plain sight.  Contact us at info@infinilytics.com or: (844) 826-6906 to schedule a demonstration of Charlee™.


[1] Insights engine defined: https://www.gartner.com/en/documents/3961025/magic-quadrant-for-insight-engines

[2] An ontology for artificial intelligence specific for insurance is the knowledge base (business expert) combined with models and unique knowledge representation that powers machine learning algorithms and the search engine.

[1] The word insight describes a deep understanding of a person or thing. Insurance insights can be described as a system of data points derived from structured and unstructured data revealing patterns of activity in topics, entities, and events.

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