Litigation Classification

Litigation Classification uses advanced machine learning algorithms to predict, if an insured person, who had an accident, is going to open a law suit against the insurance company with the claim that insurer didn’t fulfill their responsibility to the insured.

What is Litigation Classification?

If an insured person, who had an accident, thinks the insurer didn’t handle their case right and/or offered less money than they deserved, they can open a law suit against the insurance company.  

Litigation Classification aims to classify incident cases depending on if the insured person is going to open a law suit against the insurer company for this case or not.

It enables the insurance companies to act proactive, investigate these cases further and sometimes solve disagreements even before the law suit is opened. This proactive behaviour can save the company a good amount of time and recources.

Challenges for Companies

Companies often deal with:

• Too many cases to review

• Law suits causing loss in time, money and human recourses

• Human error during handling accident cases

Utility of Litigation Forecasting

• Companies can place employers and/or lawyers to further investigate the case before a law suit is oppened and act accordingly. (eg. Contact the insurer and solve the disagreement, be prepared for the court with solid proofs.)

• Save time and human resources during review phase of incident cases and offers.

Why do you Choose Trendify?

• Predict litigation outcome with an accuracy of ~80% for freshly opened and ~90% for closed accident cases.

• Develop best performing litigation forecast models super easy and fast.

• With the help of litigation probabilities take the right action fast and cost effienctly.

Related Blog Posts
Product / SKU Segmentation 5

What Are Segmentation Algorithms ?

Product / SKU Segmentation 4

IV. What is key points in Product / SKU segmentation for business ?

Product / SKU Segmentation 2

How Do Business Use Product / SKU Segmentation ? - Inventory Management - Forecasting Ideal Stock Level - Pricing Strategy Read more