New data from Targa Telematics and Viasat shows their Smart Vehicle Protector technology is helping to drive down vehicle thefts in the UK.
The two businesses, which joined forces last year, have revealed statistics from their network of Operations Centers. These reveal that in 2023, theft incidence within fleets, comprising over one million vehicles under five years old, decreased by more than 30%.
The companies attributed the achievement to customer implementation of Smart Vehicle Protector, a technological solution rooted in artificial intelligence, leveraging predictive capabilities to prevent theft.
Targa Telematics’ and Viasat’s advanced technological solutions draw on artificial intelligence and machine learning algorithms to identify potential theft risks proactively. Drawing from over two decades of industry expertise, these solutions pre-emptively address risks, often days before any incident occurs.
The hardware components onboard Smart Vehicle Protector perform a wide range of functions simultaneously, integrating theft prevention with various services aimed at optimising business operations. They also enable companies to innovate and diversify market offerings, tailoring contracts to meet the specific needs of end customers.
Targa Telematics data indicates significant cost saving benefits from the adoption of Smart Vehicle Protector. For fleets encompassing around 100,000 vehicles, cost savings of about £8m can be expected, as stolen vehicles need not to be replaced.
Furthermore, timely vehicle recovery also slashes restoration costs – sometimes even before the customer reports it – estimated at about £546,250. Additionally, the solution helps with fraud detection, allowing customers vital insights and enhancing the reliability index of car rental services.
Thomas Smith, UK country manager at Targa Telematics, commented: “We provide our customers with a comprehensive asset protection service, leveraging our extensive experience with major fleet customers, including rental and leasing companies.
“Through the development of artificial intelligence and machine learning algorithms, we create dynamic risk models and constantly update behavioural patterns, cross-referencing various types of point and contextual data, enabling proactive intervention to prevent theft.”
