Challenges: Artificial Intelligence – your strategic chapter for the future
Today, insurance companies have more data about their customers than ever before. Digital as well as analog input data are an integral part of insurance processes. The processing of incoming data, especially documents, continues to play an essential role. Via a multitude of traditional as well as new input channels, these are received every day, partly processed manually and used in many business processes. The sheer volume of documents makes this a challenging and time-consuming task. This is particularly problematic for time-critical customer inquiries.
KI & NLP: Why AI pays off
For many repetitive activities, methods from the field of artificial intelligence, here essentially from the subfield of natural language processing (NLP), can deliver added value. Artificial intelligence bundles data and knowledge in the insurance company, can compare documents at the content level, or independently recognize patterns and trends in data. AI applications make these insights available to your employees to support them and thus ensure greater speed, efficiency and accuracy.
Your advantages: Realize the potential of your data
More efficiency, less administrative work
AI applications take over manual, repetitive, error-prone steps.
Smart product development and control
Identify potential for individual insurance products based on Data Science.
Optimize user experience for your customers
Through faster case processing and shorter waiting times.
AI solutions make insurance conditions more attractive and easier to use for policyholders. This sets you apart from the competition.
Use Cases: Use Cases for Insurance: Where artificial intelligence is already being used
There is potential for the use of artificial intelligence in insurance companies along the entire value chain: In principle, artificial intelligence can be used wherever you are dealing with repetitive tasks that require intelligent decision-making.
In collaboration with existing customers, we have analyzed and re-evaluated processes and identified innovative approaches after taking a holistic view of existing data flows:
Document analysis for migrations and migration preparation
Based on labeled training data, Artificial Intelligence in the form of Natural Language Processing (NLP) makes it possible to model explicit knowledge. This allows the model trained on a fraction of the data to be applied to the entire collection – extracting relevant text passages from a large amount of data in just a few steps.
Semantic document comparison
Compare the content of two or more documents at a glance: With the help of NLP and a pre-trained language model, you can automate the semantic comparison of different documents.
Extraction of key values from continuous texts
Due to the deep language understanding of modern language models, texts can be semantically grouped and assigned. In addition, key values can be recognized automatically. A combination of these methods allows us to extract key values by category. This allows you to increase the dark processing rate e.g. by automatically pre-populating data fields from continuous texts.
Our language model, which has been specially pre-trained for insurance jargon, reliably detects semantic duplicates – regardless of the exact choice of words or formatting. We integrate our model into your template and document management and thus create a user-friendly aid for detecting duplicates. This reduces redundancies, increases text quality and reduces administrative effort.
Pattern and anomaly detection
The stock of data on policies and contracts is a treasure that wants to be put to use. Machine learning algorithms can recognize patterns in your data. Deviations from these patterns – so-called anomalies – provide an indication of faulty contracts, for example, or are used to detect fraud.
Our services: It depends on the right expertise to make AI a success
By combining 25 years of professional and technical experience in the insurance industry with the latest machine learning technologies, we help you identify AI potential in new and existing projects and processes. With a focus on machine learning, data analysis and natural language processing, we work with you to holistically optimize your processes.
We accompany your AI project through all phases – from use case identification, conception, data management and modeling to deployment. You can also take advantage of our training courses to deepen your team’s AI know-how.
Our services for insurance companies
In the Reverse Mentoring Workshop, you will develop a technical and conceptual understanding of ML and understand why and how the algorithm makes its decisions/predictions. The workshop is conducted in the context of a specific use case so that you can apply your knowledge directly in practice.
In the “Exploratory Workshop Machine Learning”, we present our own use cases and identify possible use cases for your company together with you. We classify these use cases according to complexity and benefit and build a backlog for you.
As part of our Outsourced Innovation Lab, we work with you to develop AI models or integrate them into your products. Depending on the customer’s requirements, we take over the complete implementation and provide our infrastructure for this purpose. Even after deployment, we won’t leave you in the lurch – if necessary, you can call on us for technical or specialist consulting.
why Convista: Four reasons for the AI experts at Convista
We are vendor-independent. Depending on your needs, we search for the appropriate technology and provide support during implementation.
We know the specifics, regulations and requirements of the insurance industry. Our team of business consultants and managers has worked in insurance companies for years and brings valuable knowledge of contexts and processes.
Many years of experience in AI projects
From optimizing provisions to automated document incorporation, our AI experts have already implemented numerous projects in the insurance environment. As a result, we are very familiar with various stumbling blocks on the way to the best possible AI algorithm.
Once the AI model has been successfully trained and tested, it should deliver productive added value. Thanks to our many years of DevOps experience, there are numerous options for integration into the existing IT landscape: standalone solutions with a specially developed graphical user interface are just as conceivable as complete integration into the existing IT landscape via all common interfaces. We are also happy to advise and support you in hosting and maintenance.
Professional article: News around AI in the insurance industry
Podcast: Use Case: Artificial Intelligence in Migration Projects
Manually sifting through volumes of documents in migration projects is a mammoth task. Torsten Gillessen, Managing Partner at Convista, and our AI experts Stefan Raab and Maximilian Lorenz talk in the podcast about how Artificial Intelligence in the form of Natural Language Processing simplifies AVB analysis in migration projects.