The challenge:
Manual insurance claim handling is slow and error-prone

This mid-sized insurer specialising in personal insurance policies struggled with inefficient claim management due to a lack of relevant digital mechanisms.
Traditional processes required extensive manual intervention, leading to prolonged settlement times and frustrated customers. Errors in claims verification and resource-intensive processes also contributed to increased costs.
Recognising the need for change, the company decided to modernise its insurance claim verification and processing practices.
Reviewing possible solutions
The company evaluated various methods to enhance claims management:
#1 Traditional software upgrades.
The IT team assessed available SaaS solutions to structure and automate the process. All the reviewed tools promised incremental improvements but missed integrating real-time incident data.
2# The company considered outsourcing claims processing.
While some of the most repetitive parts of insurance claim handling could be outsourced for immediate relief, this idea risked customer satisfaction and was unsustainable long-term. It also required adding extra data protection mechanisms.
#3 IoT and AI integration.
IoT devices could provide real-time incident notifications, while AI algorithms could verify claims and streamline settlement processes.
The leadership team chose the final option as the most viable solution to current operational bottlenecks and a way to unlock new efficiencies in the future.

The winning solution:
AI + IoT + automation enable more accurate insurance claim processing
The insurer enlisted an IoT and AI development company to implement an advanced claims management system. Together, they started with a pilot implementation tackling the segment of car accident insurance which suffered the most delays.
Key features of the new solution include:
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IoT-powered incident notifications
Connected devices, like vehicle telematics and property sensors, automatically detect incidents like accidents or water leaks. Thanks to real-time data transmission, the system initiates claims immediately without customer intervention.
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AI-driven claim verification
Machine Learning algorithms cross-reference IoT incident data with policy details to validate claims quickly—automated fraud detection flags inconsistencies for further review, reducing manual workloads and errors.
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End-to-end automation
AI systems guide claims through settlement steps, from initial notification to payout approval. Customers can find claim updates in a self-service portal, which improves transparency and user satisfaction.
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Data analytics for ongoing improvement
IoT data and claim outcomes enable predictive modelling to identify and address claim trends. Over time, AI algorithms improve, becoming more accurate and efficient.
Results and plans
The new claim management system delivered remarkable results:
A01
Average insurance claim settlement time decreased by 40%
with many simple claims handled within hours.
A02
Operational costs related to managing claims dropped by 30%
freeing resources for other strategic initiatives.
Faster claim settlement also resulted in significantly better customer satisfaction scores.