We focus on our customers’ data and the challenges they face while providing them advice that encompasses the full range of technologies available. Examples of suitable methods and tools include:
Innovative methods and tools
From data and analytics to machine learning and artificial intelligence
We use leading technologies tailored to the customer’s need
Aisaac is an application-neutral system that uses machine learning methods to classify documents based on unstructured information. Along with that, relevant data is extracted and made available in the form of structured data for further processing in backend systems.
Aisaac is highly versatile and can be used in a wide range of applications such as:
- Classification of incoming mail – for targeted integration into inbox/workflow systems, etc.
- Generation of structured technical and invoice data from unstructured information (including e-mails, letters or faxes) for automated processing in backend systems
Data and analytics
Having comprehensive data is the foundation of data and analytics. This is typically available at different places in different structures. To handle this information and achieve a high level of efficiency, a data management platform is needed. A platform like this can use the data to categorise claims by means of big data engineering, for example.
Google Document AI/Expert AI
These solutions automate the process of reading and analysing contracts to extract important information. This is made possible thanks to their ability to understand and process natural language, which allows the meaning of each word to be identified within the specific, insurance-related context, similar to the approach a professional consultant might take. During the project, we select the most suitable solution for the relevant task:
- Google Document AI
- Google Cloud
Using the combined methods of machine learning and natural language processing along with a variety of search engines, texts are interpreted and compared and data is extracted in a context-sensitive manner.
AI methods can be used in semantic comparisons of insurance texts and/or policies and to extract information.
Through a combination of natural language understanding and machine learning techniques, Expert.ai supports a number of commercial insurance applications in claims management and underwriting.
Do you have any questions?
There is no website or brochure which can replace a personal meeting to talk about your goals and topics. We are looking forward to an appointment on site.