Analytics, Data Science, Operation, Predictive solutions

The 4 Parts that Make Fraud Detection Work | AI Fraud Detection is reducing risk in insurance

Josh Jones

Claims fraud has infected the insurance industry for decades, impacting nearly all lines and now costing billions of dollars nationwide. The good news is that new technology gives us better ways to identify and stop fraud before it’s a high exposure loss.  

Artificial intelligence (AI) is revolutionizing how we accomplish this, but not all solutions are made equal.  Below we’ll take a look at the key components of NEMESIS, and how together they create an AI fraud detection model that works.

 

Let’s start with Anomaly Detection.

Traditionally anomaly detection has been a labor-intensive process, relying on IT and data professionals to sift through large amounts of customer or claims data to identify new patterns of fraudulent activity.  

This process has been time-consuming, costly, and prone to human error.  AI now automates and enhances the process.  NEMESIS uses AI anomaly detection to identify new cases of fraud in your claims op. and immediately alert investigators to potential issues.

 

This sets the stage for Predictive Analytics.

One of the primary benefits of anomaly detection is that it can complement predictive analytics.  Using known patterns and past data, predictive analytics builds predictive models that are useful for identifying claims needing attention before they escalate.  

However, predictive models alone have their limitations as they rely solely on past data.  NEMESIS meshes AI anomaly detection with predictive analytics to both prevent known fraud methods and detect new instances–deriving insights from those that can be input back into your predictive model.  This creates a fraud detection model that can continually learn and improve over time.  

 

How do you make sense of your fraud model results?  Easy, Interactive Dashboards.

For a fraud model to be effective it must be easy to understand and able to adapt on the fly, being only as good as the insights that it can provide.   

NEMESIS delivers a unique and robust interface that lets business users easily interact with their claims data through visual dashboards.  These dashboards are crucial in designing a fraud model that’s on target, allowing users to slice, dice, and drill-down areas of interest and derive the insights they need at the click of a button.

Not only is this important for fine-tuning and streamlining the modeling process, but it makes the ability to do so accessibly to those who matter most–your claim leaders and investigative teams.           

 

Ok, so you have spotted suspicious claims needing attention.  What’s next? 

Case Management is the final piece to our puzzle.  Once you’ve identified the right claims, NEMESIS’ integrated case management makes it possible to quickly segment those and immediately assign them to the individual or team that is going to be best equipped to resolve the issue–without having to re-enter or delegate tasks in another system.  

Managers and investigative team members can now monitor the progress and outcomes of assigned cases.  NEMESIS then generates resolution data; claim details, outcome results, and investigative results, used to enhance your modeling and claims triage over time.  

 

Empower your team with a true End-To-End AI Fraud Solution.  

The time has come for insurance moguls to embrace the AI revolution and reach outside of what their legacy systems have been capable of in the past.  With fraud projections for 2023 continuing to go south, use a tool that makes it simple and cost-effective to transform with the new generation.  AI fraud detection is reducing risk in insurance ops, how are you reducing risk in yours?

Whether you want to stop new fraud or identify what’s already there, NEMESIS has the solution you need.  

Josh Jones