Knowledge AI-Powered Agent Excels in Delivering Customized Experiences, Achieving Over 58% User Growth
CASE STUDY: ARAG ITALY
Accurate policy data capture at First Contact
ARAG Italy transformed policy data capture with an AI-powered, voice-to-digital experience that securely extracts information from policy documents, improving accuracy while eliminating manual data entry.
Full
Policy data captured digitally
Zero
Manual data entry required
Seamless
Voice-to-digital handoff
Industry
Insurance
Region
EMEA
Company size
Medium
Share
About
ARAG Italy processes legal protection claims where policy details and identifiers vary with each case, requiring accurate data collection directly from customers at the outset. This created a critical dependency on capturing complete and reliable information during the initial interaction. To address this, ARAG Italy introduced a transactional, agentic user experience that combines voice interaction with guided, real-time data capture, enabling customers to securely submit their policy number by taking a photo during the call.
Industry
Insurance
Location
EMEA
Size
Medium
The Challenge
Every claim required ARAG Italy to collect detailed policy data such as names, addresses, tax codes, and policy numbers directly over the phone. This information is long and highly error-prone when captured verbally. Even small mistakes led to downstream corrections, delays in claim handling, and additional effort for service teams and customers.
The problem was compounded by ARAG Italy's business model. Policies originate from multiple partner companies, each using different document formats, layouts, and data models. This made standardization nearly impossible and significantly complicated accurate data collection.
A purely voice-based process could not reliably handle this variability. Manual transcription introduced errors, extended handling times, and created friction in what should be a straightforward claim initiation process. ARAG Italy needed a way to capture structured data accurately without interrupting the conversation or forcing customers into separate digital journeys.
Instead of asking customers to read out complex policy details, we now capture everything directly from the document in one step. That removes errors and makes the process much easier for everyone.
Vice President Operations and Process Innovation Manager
ARAG Italy
The Solution
ARAG Italy introduced agentic AI and NiCE Cognigy xApps, enabling document-based data capture within an ongoing voice conversation. During the call, customers receive a secure link via SMS, allowing them to upload a photo of their policy document without leaving the interaction context.
Once uploaded, OCR and AI Document Intelligence automatically extract all relevant policy and customer data, regardless of document format or partner-specific layout. The extracted data is immediately fed back into the active process by the agent and transferred to the claims management system.
This approach removes the need for manual transcription entirely. Customers remain within a single guided interaction, while service teams no longer need to capture or verify complex data fields manually. The process works consistently across all partner policies, independent of format or structure.
The Impact
The new process eliminates one of the most error-prone steps in claim handling: collecting structured policy data via voice. By shifting data capture to document-based extraction, ARAG Italy significantly improves accuracy while reducing handling time and operational effort.
Claims can now be initiated directly with complete and validated data, removing the need for follow-up corrections and accelerating the overall process. At the same time, the interaction becomes simpler for customers, who no longer need to read out complex information or switch channels.
The solution also scales with ARAG Italy's partner ecosystem. As new policy formats are introduced, the system continues to process them without additional configuration, ensuring long-term robustness in a highly variable environment.
