Sebastian Thimm

Responsibility and Scope - Strategic and functional responsibility for the automotive claims product portfolio with several million Euros ARR. - Functional leadership of a cross-functional Scrum team for the Multi Domain Case Suite (MDCS), the company's central claims processing system. - Team composition: 3 Product Owners, 5 Developers, 4 Data Engineers, 2 Data Scientists, 1 Scrum Master. - Development and ownership of the product strategy and roadmap over several quarters. - Responsibility for six claims products: claim intake (auto/property), photo damage calculation, suspicious claim detection, document verification auto, AI-supported check decision, and cross-functional reporting. - Supported customer base in the single-digit to low double-digit range, up to about 10 customers.

Impact and Results - Prioritization decisions with direct impact on automation level and process costs for insurers. - Average automation rate of around 40 percent, depending on claim amount and claim constellation. - Balancing technical feasibility, regulatory requirements, and business goals in product steering. - Coordination of the migration from legacy systems to a new platform architecture.

Platform, Collaboration, and Methods - Architectural design of the Multi Domain Case Suite by coordinating system interfaces between check products, upstream services, and customer systems. - Functional responsibility for the development, introduction, and further development of new products such as Claims Assistant and Claims Calculator. - Methods and tools used: Scrum, agile product development, Jira.

Relevant KPI Responsibility - Automation rate. - Processing time per claim. - Straight-through processing rate. - Error or rework rate. - Time-to-value of new product features. - Stability of the end-to-end process chain.

Products and Responsibility - Product responsibility for Claims Cockpit, Claims Data Intelligence, and Claims Prediction. - Claims Cockpit as a reporting dashboard in the claims environment. - Claims Data Intelligence with a focus on analysis and benchmarking. - Claims Prediction as AI-based control of straight-through processing by predicting verifiable documents.

Discovery, Stakeholders, and Data Basis - Continuous discovery through structured customer interviews and workshops. - Derivation of roadmap decisions from user data and business cases. - Key stakeholders: customer representatives on the business side and internal sales. - Primary data source: internal process data.

Impact and Results - Strategic decision to discontinue sales activities for an already well-developed data product after own discovery analysis. - Proof of a systematically misjudged market potential; thereby avoiding a potential six-figure misinvestment. - Development and launch of Claims Cockpit. - Further development of Claims Prediction in conjunction with rule-based check decisions. - Significant increase in the straight-through processing rate through further development of the decision logic.

Product and Target Customer Segments - Product discovery and go-to-market strategy for a data-driven B2B platform at the intersection of Insurance and Automotive. - Product name: Eucon Market Data Engine Insurance. - Target customer segments: Actuarial departments and claims departments. - Close collaboration with a car insurance group as a lead customer.

Use Cases and Competition - Key use cases in the area of rating data and vehicle-related additional data, including ADAS (Advanced Driver-Assistance Systems). - Competitive situation in rating data: few specialized external providers and numerous in-house solutions on the insurer side. - Competitive situation in ADAS data: external data provider as a partner and other data providers with less detailed data pools.