The value of Blockchain Technology – Data Science Point of View

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Blockchain technology offers large potential for the digital transformation of various industries. This article provides insights on the blockchain applications in the automotive industry and its relevance for data analytics.

Blockchain sparks the phantasy of tech-nerd and business people alike as it is about to revolutionize the way we store and share information. In a nutshell the blockchain summarizes techniques and technologies for organizing, transmitting and storing data in a decentralized and secure way. While the idea is simple its impact may be massive as almost all transactions today depend on a regulating centralized third party. In contrast, the blockchain technology enables a distributed consensus protocol that manages transaction records in real-time and without a central trustee. Blockchains can also facilitate smart contracts, which are digital representations of agreements with transparently verifiably code, that self-execute if certain conditions are met. Up until today, companies in many industries have realized the opportunity provided by blockchains and constantly discover new applications and services. In the following blog-series we present a diverse spectrum of use cases and Capgemini Consulting’s view on their implementation in various industries (see figure 1 for an overview).

Figure 1: Blockchain technology applications across the industries

Figure 1: Blockchain technology applications across the industries

Part 1: Applications for the automotive industry and mobility services

The first blog entry summarizes cases and ideas developed in our Applied Innovation Exchange and the Data Science Lab in joint working sessions with our clients. The biggest potential have been attributed to the generation of personal mobility profiles generated on the blockchain for customers of automotive companies or mobility services. Such a profile, which is stored in a distributed ledger and accessible through a private cryptographic key, may act as proof of ownership for the vehicle or conducting a journey – e.g. for cab or truck drivers; in the future even autonomous driving cars. Personal mobility profiles store the vehicles mileage and other user data, which enable the OEM to analyse customers and create additional revenue streams through up and cross-selling based on identified user behaviour. Further, blockchain technology offers the OEM a secure way of exchanging data with collaborating parties and the customer purchase history can be tracked along the customer life cycle. This traceability and transparency allows the OEM to control any component repairs and verify that solely original spare parts are authorized during maintenance and repair.

Additionally, the information on the blockchain can be leveraged in relating financial services (see figure 2). For insurances purposes, the OEM can build a detailed repair and maintenance history on a blockchain ledger, which is directly linked to the vehicle and independently updated for each component exchange or service action undertaken by any operator. This provides transparency over insurance claims and the state of the vehicle at the moment of an incident. Further, insurance contracts can be signed via smart contracts and enable customers and insurance companies to manage insurance policies in a transparent, responsive and irrefutable way. When contracts and claims are recorded into a blockchain ledger, which is validated by the network, it secures that only valid claims are paid. In case of an accident that was validated by the blockchain, the payment in the smart contract is activated and directly transferred to the vehicle repair upon the repair being complete.

Figure 2: Blockchain can facilitate smart contracts for vehicle related financial services

Figure 2: Blockchain can facilitate smart contracts for vehicle related financial services

Such thinking offers a large variety of services for the car owners and users turning mere analytical predictions into concrete action, e.g. by enforcing payments and automating contracts between vehicle owner and the driver. For example, real time transfers are implemented with reduced risk through blockchain technology and the transparency gained through public records allows the collection of large datasets for analytical applications. Anomaly detection algorithms are generally used to detect fraud patterns and identify risky transactions. Before the introduction of blockchain technology fraud detection could be undertaken retrospectively, but transparent ledger record keeping and increasing amount of data facilitate real-time anomaly detection. This accelerates companies’ speed in decision-making about pseudonymous data and real-time detection mechanisms largely decrease the risk of fraud.

Ultimately new lines of services will arise when say autonomously driving, shared cars will communicate which each other, the passenger and third parties. Corresponding future business models certainly will be around sharing and distributing data. One can easily imagine how all the sensor data of the car can be monetized or used for community purposes like documenting the state of the environment along the roads. As of today, most of these business models still have a way to go until they reach market maturity. Also our clients are hesitant taking up the competition with the big tech-giants in the field of data brokering and distribution. Hence, the fist applications – like comparing driver behaviour in online driving communities – seem more to be like toying around than to promise future returns. Yet, it is worthwhile keeping an eye on the underlying patterns and an open mind.

This article was written in collaboration with my colleagues Sebastian Olbrich and Lukas Ley.


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