LEGAL SERVICESNetherlandsAVICLAIM
Aviclaim handles the entire flight compensation process for their customers making it more likely to be successful. Due to their growth during the pandemic, they process 10K claims a year - which would be nearly impossible without the efficient software system that we’ve been working on for the past 7 years.
years collaboration
claims processed/year
Managing over 25K claims– and processing around 10K– a year isn’t easy. The process involves many tedious tasks, such as categorising requests, responding to emails and extracting data from documents. This situation created not only more workload for employees but also a delayed response time for airline customers.
Aviclaim chose Qubiz due to our track record of creating process automation solutions based on AI, that allow employees to switch from manual tasks to high-value activities.
We’ve helped to develop a white-label solution that can be adapted to each country’s policies and regulations regarding flight issues. Furthermore, third parties can use the solution to further expand the reach of coverage. With a strong SEO component, it enables proper indexation and higher positions in search results.
All data points are consolidated in this back-office solution. Managing emailing, notifications, documents, digital signing and payments is done in an easy and straightforward manner. It also offers insights and statistics for important business operations.
Another component manages pulling relevant data from a number of external sources, such as weather data and flight delay announcements and can offer advice to potential customers. Furthermore, third-party integrations, such as car rental services and taxi companies, are possible through an API.
Aviclaim needed a faster way to offer first-level support for known issues and to guide customers through the flight claim process.
We developed a chatbot for the Aviclaim websites and those of their affiliate partners using natural language processing (NLP) to understand user conversation intent.
To create and train models for language understanding, we used the Microsoft Bot Builder framework and LUIS, they’re a machine-learning service.
Previously, Aviclaim employees had to take each email and analyse which claims have a higher chance of compensation.
To speed up this process, we created the claim payment prediction feature to automatically predict which claims will be successful.
How does it work? Using ChatGPT for predictive analysis. We worked with a dataset from their system and enriched it with other features derived from the existing ones or created by us. First, the system uses the airline response classification (such as “claim acceptance”) then it uses both Aviclaim-customer and airline-customer email exchanges to predict whether or not the claim request will be accepted.
Aviclaim employees had to manually categorise claims, a highly tedious and time-wasting process.
Instead, using a ChatGPT integration, scanning and interpreting incoming airline responses is much more efficient. The agent now classifies email responses into categories such as “claim acceptance” or “claim rejection.”
Timely responses=happy customers. To ensure this, we worked on an email bot that can understand and respond to customer inquiries.
The ChatGPT-based bot uses the client’s database, Aviclaim emails and airline conversations to offer an overview of everything related to a claim. In this way, customers get quick and accurate answers to their emails, regarding the status of their claim, delays, documents, etc.
A large percent of Aviclaim employees’ time is spent verifying and extracting information from documents, such as passports, and responding to customer emails.
We are developing a ChatGPT solution to handle customer inquiries, classify airline responses and handle legal documents (missing or incomplete information).
For example, if a claim has missing information or documents (ID, plane tickets), the agent will automatically send an email asking customers for their information.
Additionally, the machine learning models are tested for accuracy and reliability, as they will continuously learn new customer questions, minimising errors over time.
As part of our continuous development and support process, we are currently working on adding more AI features and training models for increased efficiency and accuracy.
With our help, Aviclaim can now:
As we’ve worked now for 7 years with Qubiz, we had very innovative projects such as great-working chatbot where people could submit a claim – which is now actually an upcoming thing, but we had it already 5 years ago… I would recommend Qubiz because they are a flexible company, they do what they say they are going to deliver, and they are also open for feedback. If you have to switch companies, it costs a lot of energy, it brings a lot of costs. I think that’s one of the key points from Qubiz, that you can create a long-lasting relationship with them.
Get in touch to discuss your challenges or project idea.
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