Use Case Explorer

Due to the increasing amount of data produced by components and systems installed in the vehicle, automotive manufacturers have the opportunity to improve their after-sales service in a data-driven manner. By monitoring and analysing this data, potential maintenance needs or defects can be identified at an early stage and appropriate measures can be initiated. In this way, maintenance work can be planned in good time, thereby reducing unexpected breakdowns. Everyone involved benefits equally from this use case. Drivers themselves since they arrive at their destinations without annoying incidents. Automobile manufacturers benefit from more satisfied customers and reduced warranty costs. In addition, this data allows drawing conclusions about quality problems in the installed parts at an early stage. If quality deficits should exist, it is possible to react at an early stage and thus prevent greater damage.

This use case is interesting for all companies, especially manufacturers, that offer warranties for their products. Usually, these companies have to bear huge costs arising from fraudulent warranty claims. AI and machine learning techniques can use the data related to these claims to identify if a claim is likely to be fraudulent automatically. Such a system can then be complemented by human inspectors who manually investigate suspicious claims. Implementing this allows to process a high volume of claims quickly and efficiently, reducing costs arising from fraudulent warranty claims considerably. It works particularly well if there is a lot of data related to each specific claim fed into the fraud detection system.

Chatbots are nothing new, but through rapid advancements in natural language processing, a subfield of AI, they become smarter and more valuable month by month. They can be used in the retail & consumer goods industry in two ways. First, they can emulate a human salesperson, helping the customer to find what they are looking for, providing valuable advice and relevant alternatives – bringing one of the traditional key advantages of brick-and-mortar stores to the e-commerce world. Second, they are also perfectly suited for many customer service and support activities. They can automatically respond to frequently asked questions, process incoming customer requests or complaints completely, direct a customer to a human support employee, and automate many other tasks. That usually results in less human labour, decreased response times, and happier customers.