Claims processing · Production

Trygg-Hansa reduces home insurance claims processing time by 95% with generative AI and digital workers

The problem

A new team assigned to process home insurance claims was uncertain how to work efficiently, causing delays in paying customers who needed rapid reimbursement for damaged personal devices.

Workflow diagram · grounded in source

Customer submits claim

trigger

“When customers submit claims after an adverse experience, they often want and need a rapid and uncomplicated response”

Generative AI fraud detection

ai_action

“developed an algorithm that uses generative AI to help detect if a claim is at risk for fraud and needs further investigation by an employee, or if a claim is from a customer in good standing and can be fast-tracked for payment”

Digital workers assess and label

ai_action

“Digital workers, equipped with intelligence from this algorithm, assess and label each claim”

Route to correct processing area

routing

“route it to the correct processing area”

Human review for fraud risk

human_review

“needs further investigation by an employee”

Process fast-tracked claims

output

“They scan the database and pick up the fast-tracked claims, process them for payment”

Notify customer via portal

output

“send a communication to the customer via Trygg-Hansa's customer portal”

Reported outcome

Claims processing time was reduced by 95% for fast-tracked claims and CSAT rose by 7%.
Employees can now give real-time updates to customers who call in, and digital workers have recovered millions of euros in claims that another insurer should have paid.

Reported metrics

Claims processing time reduction (fast-tracked)95%

customer satisfaction (CSAT) score increase7%

Claims recovered from other insurermillions of euros

Reported stack

SS&C Blue Prismgenerative AImachine learning (ML)Trygg-Hansa's customer portal

Source

https://www.blueprism.com/resources/case-studies/trygg-hansa-claims-automation/

Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

Claims processing time was reduced by 95% for fast-tracked claims and CSAT rose by 7%.

What tools did this team use?

SS&C Blue Prism, generative AI, machine learning (ML), Trygg-Hansa's customer portal.

What results were reported?

Claims processing time reduction (fast-tracked): 95%; customer satisfaction (CSAT) score increase: 7%; Claims recovered from other insurer: millions of euros (source-reported, not independently verified).

How is this claims processing AI workflow structured?

Customer submits claim → Generative AI fraud detection → Digital workers assess and label → Route to correct processing area → Human review for fraud risk → Process fast-tracked claims → Notify customer via portal.

Claims processing time was reduced by 95% for fast-tracked claims and CSAT rose by 7%.Employees can now give real-time updates to customers who call in, and digital workers have recovered millions of euros in claims that another insurer should have paid.