In the insurance industry, it is essential for both the insurer and the insured to derive mutual benefits from their partnership. This win-win relationship can be further strengthened through Cloud Data & AI, providing numerous advantages to the insurance world.
Cloud data & AI can be leveraged to efficiently handle low-volume, high-demand claims, while more granular data can be processed to optimize analytics techniques for risk assessment, and to enable the development of new insurance services. AI is used to detect claims at an early stage. The use cases for cloud data and analytics in the insurance industry are diverse, and include optimizing the customer journey, detecting fraud, managing risks, improving business processes through process mining, image recognition for motor vehicle damage, and evaluating damage based on images.
Created an RAG-based chatbot to make insurance documents searchable for life, health, and property sectors.
Development of a tailored LLM for automatic categorization of claim types and extraction of relevant details from insurance claim reports – for more efficient analysis and faster claims processing.
Conceptualization and implementation of the entire data management for a group-wide IFRS 17 implementation for a leading Swiss insurance company. In this process, more than 200 information systems of different group companies were connected.
Knowledge transfer in the field of data science, implementation of various advanced analytics use cases such as next-best-offer, next-best-customer, potential analysis and document verification. Establishment of a central advanced analytics environment. Automation of the document review leads to a saving of costs by an external reviewer and speeds up the processes.
Analysis, design and implementation of a planning system for cost centre planning including cost allocation and target/actual comparison. Survey of the cross-departmental technical requirements for the company-wide DWH system. Design and implementation of a company-wide data warehouse.
The Investment Analysis project is designed to enable the specialist department to evaluate the portfolio, risk, performance, stress test and order data of its investments in a structured manner. The application is used to monitor and adjust the customers investment strategy.
Development of a control cockpit for the analysis of KPI key figures and the performance of service level agreements across different process areas.
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