AI in Claims Management: How AI is Transforming Insurance

How AI is transforming claims management in insurance

June 17, 2025
Use Case
Marius Gotschol

In an insurance company's claims management , damage reports, accident reports, medical assessments, and repair shop invoices , which must be manually reviewed, are part of everyday life. But what if an AI could perform this task in seconds – precisely and scalably?

In the insurance industry, not only are the number of contracts and claims increasing, but so are customer expectations. While a letter and a weeks-long wait were once considered normal, today a digital inquiry is often eagerly awaited after just a few hours. At the same time, skilled workers are in short supply. Given traditional, often manual processes, artificial intelligence is increasingly gaining attention, not only to increase efficiency but also to unlock new potential in scalability and accuracy.

The benefits of AI are particularly evident in claims management. Large volumes of unstructured data, including workshop invoices, legal letters, and damage descriptions, are received daily. At the same time, there is a need to derive decisions quickly and reliably from this data.

The manual effort is high and error-prone. At the same time, all processes must remain compliant, customer-friendly, and cost-effective. AI-based document processing takes over repetitive tasks, freeing up space for the truly essential tasks: individual review, empathetic customer communication, and targeted management of complex cases.

Why AI-based claims management is driving change in the industry

"AI-based claims management" refers to the use of artificial intelligence to automate and optimize claims processing. Intelligent Document Processing (IDP) solutions automatically analyze and structure claim-related documents, and extract relevant data.

Technologies such as natural language processing (NLP), deep learning, machine learning, and optical character recognition (OCR) are used to recognize this data regardless of format and deliver it in a structured JSON format. This eliminates manual data entry—a process that is both time-consuming and error-prone.

The result: shorter processing times, a significant reduction in errors, and less workload for employees, who gain time for more complex tasks such as evaluating contentious cases or customer communication.

Given the increasing number of claims due to rising contract volumes, extreme weather events, and higher service requirements, traditional processes are reaching their limits. AI-based solutions enable insurers to meet this challenge efficiently and with assured quality.

They form the foundation for modern, future-proof claims management that not only saves costs but also meets customer expectations.

Typical challenges in claims processing

In the day-to-day processing of claims, insurers often have to contend with the following problems: Workshop invoices come in different formats and structures, which makes manual review difficult and prone to errors.

This manual data entry is also difficult to scale. As the volume of claims increases—for example, due to severe weather or a high number of claims—traditional processes quickly reach their limits.

Heterogeneous document formats : Workshop invoices and other documents are available in a wide variety of layouts and structures – a challenge for manual processing.

High time expenditure : Manually entering and checking data costs valuable time and ties up resources.

Limited scalability : Traditional processes are difficult to adapt flexibly as document volumes increase.

Detect fraud attempts : Irregularities such as double-billed items or excessive amounts must be detected in order to prevent economic damage.

Regulatory requirements : Data protection (GDPR) and traceability (GoBD) must be strictly adhered to – while ensuring efficient processing at the same time.

How exactly can AI help detect fraud attempts?

The fight against insurance fraud requires a synergistic combination of document processing and intelligent pattern recognition . AI -supported processes identify fraud attempts, such as manipulated workshop invoices or forged documents, early in the process.

Automated data extraction : Relevant information from documents is extracted using AI and provided in a structured manner.

Early detection of fraudulent characteristics : Documents and images are checked for potential manipulation and anomalies.

Efficient system integration : All processing steps run via standardized interfaces – scalable, automated and data protection compliant.

Early warning system : Suspicious cases are automatically marked so that targeted follow-up can be carried out.

Greater security : The entire claims process becomes more resistant to fraud attempts – while saving time and resources.

Buildsimple as a solution for insurers

Buildsimple is a powerful solution for automated document processing. It helps companies efficiently extract and classify large amounts of unstructured data and make it usable for subsequent processes. The platform is already being successfully used in various industries to make document-based processes more efficient and secure.

Buildsimple combines artificial intelligence and machine learning to automate the processing of incoming documents in claims management—such as workshop invoices, appraisals, or cost estimates. The platform performs two key tasks: First, it automatically classifies the document type, so it's clear upon receipt whether it's an invoice, an appraisal, or another claim-related document. Second, Buildsimple extracts all relevant content, regardless of layout, and precisely delivers it in a structured JSON format for further processing.

Integration takes place via standardized interfaces (REST APIs) and can be easily integrated into existing systems – without the need for complex IT projects, AI expertise, or lengthy training. This means that even specialist departments without prior technical knowledge can use the solution directly. Thanks to this flexibility and user-friendliness, Buildsimple is ideally suited for use in regulated industries such as the insurance industry – fully GDPR , DORA , and EU AI Act compliant.

Advanced AI use cases in claims management

In addition to the automated reading of workshop invoices, AI technologies can be used effectively in many other areas of the claims process – especially where large amounts of data need to be processed, anomalies need to be identified, or decisions need to be prepared.

Typical fields of application are:

Automated case classification: AI models classify incoming documents not only by document type (e.g. invoice, expert opinion, cost estimate), but also by process (e.g. new claim report, known claim, complaint) , urgency or complexity – for more intelligent prioritization in processing.

Support with cost estimates: The structured processing of historical claims allows for more precise forecasts of new claims amounts – a valuable building block for fairness and efficiency in settlement.

Early fraud detection: Unusual data patterns, duplicate items, differing damage amounts or manipulated damage photos are automatically detected and flag potentially suspicious cases for targeted review.

Monitoring of service providers and workshops: Anomalies in the invoicing of individual partners can be detected using AI and prepared for internal audit processes – a contribution to greater transparency in the network.

Customer dialogue and service optimization: With automatically read information, customer inquiries can be answered more quickly and precisely – e.g., regarding cost coverage, processing status, or queries regarding submitted documents.

Benefits for insurers:

Faster claims processing: Automated data extraction saves time and speeds up processes.
Reduced workload for employees: Routine tasks such as manually checking invoices are eliminated, allowing employees to concentrate on complex cases.
High data quality: Structured, reliable data is the basis for analytics and intelligent fraud detection.
Easy to use: Business departments use Buildsimple without any prior IT or AI knowledge.
Quick start: No training required – ready to use immediately.
Compliance compliant: GDPR, DORA, and EU AI Act compliant. Suitable for regulated insurance companies.

Use Case: Riparo GmbH – Automatically read workshop invoices

Riparo GmbH is a nationwide automotive claims service provider. As a link between insurance companies and auto repair shops, Riparo supports the efficient processing of vehicle claims. As part of the digitalization of claims management, Riparo relies on intelligent solutions for process automation.

The challenge was to efficiently process a constantly growing order volume and over 100 different workshop invoice formats. Buildsimple developed a solution that automatically reads all invoice formats and provides the data in JSON format. This data is then integrated directly into the Riparo system via an API, eliminating manual data entry.

The result: Immediately after go-live, 96% of documents were read correctly. The AI continues to improve, allowing Riparo to process significantly more cases with the same staffing levels. The successful implementation has now been expanded to other company divisions, such as the subsidiary "ri werkstattservice."

Conclusion

The implementation of AI-supported claims management is no longer an option; it's a necessity for insurers seeking to remain competitive in the digital age. AI enables more efficient processing, shortens processing times, and ensures greater accuracy without compromising quality. AI-based solutions like Buildsimple form the foundation for modern claims management that can respond flexibly to growing demands.

outlook

In the future, AI solutions will not only optimize claims management but will also be used in other areas such as benefit assessment, KYC, and policy administration. Complete end-to-end automation of claims processing remains a key goal to further reduce workload and sustainably improve the customer experience. Through various partnerships in the area of claims processing, AI components can be integrated even faster and seamlessly into existing systems. These building blocks of a modular, comprehensive solution not only increase efficiency but also create additional security along the entire process chain. This is a clear advantage for insurers on their path to a digital future.