top of page
fire-blaze-inferno-conflagration-and-com

Claim management

Maximise your claim management potential

Build robust claim-cost predictive models
 
Tailor your price offers

Cut avoidable losses
​​

In today’s insurance environment, where products and prices can be quickly matched by competitors, tailored offers and superior customer experiences are becoming the primary drivers of differentiation.

 

In this regard, building explanatory and predictive claim-cost models like claim-cost prediction or fraud detection is key

Turn aerial and street-view imagery into actionable intelligence

Make use of all the information the Building Knowledge Centre offers to develop and improve claim-cost-related models.

Claim management.png
tree-on-a-house-due-to-hurricane-and-tor
Picture2_edited.png
claim management fraud.png

Improve claim-cost models:

Claim prediction power

Use the Building Knowledge Centre information to build strong predictive claim-cost models, like frequency and severy-based modelling

Make accurate prediction to decrease costs, better manage pricing policies and better handle claim reserves.

Tailor your offers and adapt your pricing policies accordingly

Better understand claim-cost triggers

Too often insurance companies have a partial understanding of the factors that lead to claim costs.

 

By leveraging a full range of property attributes, from both aerial and street-view imagery, insurance companies can find hidden or implicit correlations between property attributes and claim loss history.

Better identify the individual and combination of property attributes that cause claim losses.

Understand and explain how pricing policies should be adjusted.

Improve claim-cost models:

Fraud detection power

Fraud losses amount to 10% of overall claim expenditures in Europe.

 

It incurs premium increase for all customers and introduces additional time before customers receive legitimate compensation.

 

Improve property fraud detections models to cut avoidable losses and prevent your customers from bearing the price increase caused by fraudsters.

bottom of page