Abstract 

This dissertation studies how artificial intelligence (AI), blockchain-i and the Internet of Things (IoT) can be integrated to improve vehicle lifecycle management and motor insurance in Albania. This problem is essentially related to how they are created, stored, verified and si vehicle data is used and of insurance policies between different ecosystem actors. Methodologically, the study relies on research based on design science (Design Science Research DSR) and mixed methods. The aim of the paper is to build an artifact for the Albanian context. The research work begins with the analysis of the Albanian ecosystem of vehicles and motor insurance where the main problem identified is data fragmentation. Data on vehicles, repair services, technical inspections at the General Directorate of Road Transport Services (DPSHTRR), as well as on insurance policies and claims for compensation are stored in the systems of each actor and end are not interconnected. This makes it difficult to track the complete history of the vehicle throughout its life cycle. Also, the process of handling claims and assessing damages remains tied to physical documentation and manual verifications. Another problem is that the practical implementation of the system bonus malus for determining the price of the policy, where insurance premiums increase or decrease based on risk and claims history, is still limited, even though the legal basis exists. To better understand these gaps in the Albanian ecosystem, the study uses two main components as sources of evidence. The quantitative component relies on a questionnaire on compensation claims with 224 responses full. The qualitative component is based on 12 interviews in total: 11 with professionals covering all eight licensed motor insurance companies in Albania and 1 with an independent expert in the field.. Identification of gaps and triangulation, combining quantitative data, e qualitative evidence and e literature review, serve as a basis for identifying the requirements that the architecture must meet REFERENCE proposed, both from a functional and feasibility point of view, as well as from a governance and trust perspective among ecosystem actors. Based on the requirements derived, the dissertation proposes a reference architecture that integrates AI, blockchain-in and IoT-In IN an artifact designed within the framework of DSR, where the vehicle is placed at the center of the model CONCEPTUAL of the problem area. The vehicle is the central entity associated with insurance policies, claims and damages, repair events in service, technical checks at the DPSHTRR, granting consent for the use of data, data summaries telematics and the results produced by AI-IIn this context, blockchain-it serves as a layer for event recording, control access conTinously, traceability and auditability. A.I-I is used as a supporting layer for determining the price, categorizing claims for compensation, identifying suspicious cases and reviewing decision-making. While IoT-I and telematics are treated as complementary sources of of data, which can only be used when the conditions of consent, control and governance are clearly defined. Finally, the artifact is demonstrated and evaluated through two scenarios of the motor insurance process. The first scenario is related to the determination of the price, considering system implementation bonus malusThe second scenario follows the workflow for claims processing, claims handling and fraud control. Thisa The scenarios aim to show how the architecture logic could work in cases relevant to motor insurance, without claiming full market implementation. In line with the DSR steps, the evaluation phase tregon that the practical implementation of the artifact should be carried out in stages. The evaluation examines whether it covers the identified requirements and whether it is suitable for the conditions operational of the Albanian market. Also, is assessed whether it is consistent with empirical evidence and whether it respects the needs of data governance. In conclusion, the findings e dissertationt suggest that modernizing motor insurance in Albania requires a more sustainable approach, starting with building a common database to increase trust between actorsFrom a research perspective, the study contributes design knowledge based on the Albanian context, as well as providing insights into TRANSFERRED even for other small or emerging markets. 

Field: Information Systems, AI, Blockchain, Decentralized and automated systems 

Kataët Keywords:  Artificial Intelligence (AI); Blockchain; Internet of Things (IoT); Vehicle Lifecycle Management; Motor Insurance; Research Based on Design Science; INTEROPERABILITY; 

Abstract 

This dissertation examines how artificial intelligence (AI), blockchain, and the Internet of Things (IoT) can be integrated to improve vehicle lifecycle management and motor insurance in Albania. At its core, the problem concerns how vehicle and insurance policy data are created, stored, verified, and used by the different actors in the ecosystem. The study is based on Design Science Research (DSR) methodology combined with a mixed-methods approach. The main purpose of the dissertation is to develop an artifact adapted to the Albanian context. The research begins with an analysis of the Albanian automotive and motor insurance ecosystem, in which the main problem APPROBATION is data fragmentation. Data related to vehicles, repair services, technical inspections at the General Directorate of Road Transport Services (DPSHTRR), insurance policies, and claims are still stored in separate systems for each actor and are not shared among them. This makes it difficult to trace the complete history of a vehicle throughout its lifecycle. In addition, the process of handling insurance claims and assessing damages remains closely linked to physical documentation and manual verification. Another important issue is the lack of practical implementation of the bonus malus system for underwriting and insurance policy pricing, despite the legal basis. To better understand these gaps in the Albanian ecosystem, the study uses two main sources of evidence. The quantitative source is based on a questionnaire on insurance claims with 224 complete responses. The qualitative source included 12 interviews: in total, 11 were conducted with representatives of all eight licensed motor insurance companies in Albania, as well as one with an independent domain expert. The identification of gaps and the triangulation of quantitative data, qualitative evidence, and the literature review serve as the basis for defining the requirements that the proposed solution should address, in terms of functionality and feasibility, as well as governance and trust among ecosystem actors. Based on the derived requirements, the dissertation proposes an architectural solution that integrates AI, blockchain, and IoT into a single artifact, with the vehicle at the center of the domain model. The vehicle is treated as the center entity linked to insurance policies, claims and damages, repair events in service garages, technical inspections at DPSHTRR, consent for data use, telematics summaries, and AI-generated outputs. Within this framework, blockchain serves as a layer for recording events, controlling access, ensuring traceability, and supporting auditability. AI is used as a supporting layer for pricing, claims categorization, identification of suspicious cases, and reviewable decision support. IoT and telematics, meanwhile, are treated as complementary data sources that may be used only when clear conditions of consent, control, and governance are in place. Finally, the artifact is demonstrated and evaluated through two motor insurance process scenarios. The first scenario concerns pricing that accounts for the application of the bonus-malus system. The second scenario follows the workflow of insurance claims, damage handling, and fraud control. These scenarios aim to show how the architecture's logic can operate in important motor insurance cases, without claiming full market implementation. The artifact evaluation emphasizes that practical implementation should take place in phases. The evaluation examines whether the artifact meets the identified requirements, is suitable for the operational conditions of the Albanian market, aligns with empirical evidence, and respects data governance needs. In conclusion, the dissertation findings suggest that modernizing motor insurance in Albania requires a more sustainable approach, beginning with the construction of a shared data foundation to increase trust among actors. From a research perspective, the study contributes design knowledge grounded in the Albanian context and offers transferable insights for other small or developing markets facing similar challenges. 

Field of study: Information Systems, AI, Blockchain, Dcentralized and automated systems 

Keyworders:  Vision Intelligence (AI); Blockchain; Internet of Things (IoT); Vehicle Lifecycle Management; Engine Insurance; Design Science Research; Interoperability