Safety on Two Wheels: When Telematics Becomes an Ally
In recent years, motorcycles, scooters and—more recently—e-bikes and kick scooters have become major players in our cities. They are fast, agile vehicles, ideal for moving through traffic and navigating areas where parking is difficult. At the same time, however, those who use them know very well that being more exposed on the road also means taking on greater risks.
Safety on two wheels is a topic that regularly returns to the center of public attention, especially because it takes very little to end up in a dangerous situation: a distraction, sudden braking, or an unexpected oil patch on the asphalt. This is why today, alongside traditional safety measures, modern tools capable of making a real difference are becoming increasingly important. Among these, technologies for data collection and analysis play a leading role.
Riding on two wheels means experiencing the road in a direct and immediate way: there are no protective barriers, balance is more fragile, and the rider’s reaction time matters more than ever. Several factors can impact safety, including limited visibility to other road users, road conditions, weather, sudden changes in traffic flow, and riding habits that are not always fully aware. In a context where light mobility continues to grow rapidly, potential risk situations increase as well. This is where intelligent tools can offer concrete support.
Telematics makes it possible to collect, analyze, and interpret a large amount of data that helps us better understand what happens during a ride. It is not just a monitoring system, but a true ally capable of improving safety in practical and immediate ways. Thanks to sensors, it becomes possible to observe the vehicle’s real behavior—from harsh braking to sudden acceleration, from corners taken at excessive speed to moments in which traction is lost. All this information becomes a kind of “mirror” for the rider or for fleet managers, providing a clear view of driving habits and helping identify where improvements can reduce risks.
The integration of artificial intelligence further enables the identification of recurring patterns and potentially dangerous situations, such as stretches of road where more accidents occur, weather conditions that increase the likelihood of falls, or times of day when certain risky manoeuvres occur more frequently. This predictive capability opens the door to a completely new approach—not just intervening after an incident but preventing it before it happens.
Another equally important aspect concerns emergency management. The most advanced solutions can automatically detect a fall or impact — the so-called crash detection — and send an immediate alert with the precise location and essential information about the event. In many cases, especially outside urban areas or at night, the speed at which help is activated can make a significant difference. Technology also plays a key role in protecting the vehicle itself. Riders know how vulnerable motorcycles and scooters are to theft, and tools such as real-time tracking, unauthorized-movement alerts, or customizable “safe zones” provide valuable support in reducing risks and improving vehicle recovery.
Ultimately, safety is not built on rules and devices alone: it is a balance between conscious behavior and the tools that help protect us. Digital solutions enter this balance discreetly but with significant impact. They make riding more informed, support fleet managers, promote a culture of prevention, and contribute to reducing risks.
In a future where two-wheel mobility will continue to expand, equipping these vehicles with intelligent systems is no longer optional—it is a natural step toward safer, more responsible travel.
OCTO and Liberty Rider Join Forces for a New Era of Safety and Connectivity on Two Wheels
Milan, 20 November 2025 – Safety meets innovation: the partnership between OCTO Telematics, a global leader in telematics and IoT solutions for the insurance sector and connected mobility, and Liberty Rider, Europe’s leading app dedicated to protecting motorcyclists, has officially begun.
The new alliance will be presented today at the Italian Insurtech Summit 2025 in Milan, through a joint keynote by the two CEOs — Corrado Sciolla (OCTO Group) and Emmanuel Petit, CEO and Founder of Liberty Rider — along with the unveiling of OCTO’s new device dedicated to motorcyclist safety.
The collaboration between the two players has given life to a project with a shared objective: making the road a safer and smarter place for those who travel on two wheels, by integrating advanced detection technologies and connected prevention tools.
The goal is clear: to make technology an ally for those who live the motorcycle experience every day, combining OCTO’s expertise in telematics and connected protection with Liberty Rider’s proven capabilities in automatic crash detection.
Founded in France, Liberty Rider is now used by hundreds of thousands of motorcyclists and is recognized for its fall-detection algorithms, capable of sending an alert to emergency services within seconds — significantly reducing response times. After dominating the French market, with 13 insurance partners, Liberty Rider has chosen Italy as its first European expansion country, bringing with it a model that blends technology, safety, and community spirit.Thanks to the collaboration with OCTO, the Liberty Rider ecosystem will be enhanced with new intelligent protection features, designed to accompany riders at every moment of their journey, from departure to their return home.
“The collaboration with Liberty Rider reinforces our vision of increasingly connected and safer mobility,” said Corrado Sciolla, CEO of OCTO Group. “By combining technological expertise and deep knowledge of the insurance world, we aim to create concrete value for the entire ecosystem, offering solutions that elevate safety and innovation standards in the industry.”
“This partnership represents a decisive step toward our mission: protecting every motorcyclist, wherever they may be,” stated Emmanuel Petit, CEO and Founder of Liberty Rider. “The introduction of smart anti-theft technology adds an additional layer of protection, because safety is not only about the rider but also the vehicle that accompanies every journey. Liberty Rider is the leader in 100% software-based telematics, while OCTO brings extensive experience in connected technologies applied to safety. Together, we can create unique synergies capable of delivering solutions that are even more complete, flexible, and aligned with the needs of all road users.”
The collaboration between OCTO and Liberty Rider marks a significant step toward a safer, more digital and sustainable mobility — where connectivity becomes a concrete element of protection for everyone who chooses motorcycling as a lifestyle.
About OCTO
For over 20 years, we have been developing integrated solutions that enable us to support our clients in seizing the opportunities offered by smart mobility and digital transformation. Thanks to an innovative approach based on Artificial Intelligence, we have developed advanced algorithms for accident detection, driving behavior analysis, claims management, and consumption optimization. These solutions allow us to meet the needs of key markets, such as insurance and mobility, with a strong focus on modularity and customization. Our scalable and modular data analytics platform delivers solutions for the Insurtech and mobility markets, helping partner companies transform the way they manage and grow their business.
A robust and purpose-driven ESG strategy ultimately guides our market proposition, focusing on the development of solutions that support the energy transition and data-driven urban planning.
OCTO has profiled 20 million drivers and holds the world’s largest telematics database, based on 610 billion kilometers of driving and over 13 million crashes detected. octotelematics.com
OCTO Media Contact
Adriana Zambon
press@octotelematics.com
Phone +39 339.3995640
Liberty Rider
marketing@liberty-rider.com
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AI and Telematics in Insurance Fraud Prevention: The New Market Standard
Insurance fraud prevention has become a strategic priority for insurers. It no longer involves simply identifying suspicious claims: it directly impacts profitability, operational efficiency, and the overall customer experience. As fraudulent behaviors grow more sophisticated, policyholders expect fast, digital, and transparent insurance processes — a combination that requires insurers to rethink their fraud detection models.
Insurers today face two critical challenges. First, they must reduce the Loss Ratio by preventing fraudulent claims from bypassing controls. Second, they need to keep the journey of legitimate customers smooth, avoiding delays that negatively affect satisfaction and loyalty. At the same time, insurers must manage an unprecedented amount of complex data: telematics data, driving behavior insights, weather information, crash dynamics, and vehicle history. These elements offer immense value but are increasingly difficult to interpret using traditional fraud analytics tools.
As insurance claim management becomes faster and more digital, fraud detection can no longer be reactive. The industry now requires predictive fraud models capable of identifying inconsistencies early in the claim lifecycle, without slowing down operations.
Traditional rule-based systems and manual verification no longer provide the accuracy needed. By contrast, AI and Machine Learning for insurance enable the analysis of large datasets, uncover hidden correlations, integrate multiple data sources, and significantly reduce false positives. A key advantage of ML-driven fraud detection is its ability to continuously learn from new scenarios, adapting quickly to emerging fraud patterns and offering insurers a more accurate and efficient solution.
The integration of telematics data into fraud prevention is redefining the market. Insights such as real crash dynamics, vehicle behavior prior to impact, and severity analysis introduce a new level of objectivity, reducing ambiguity and accelerating claim assessment. This allows insurers to make faster, more confident decisions — improving both operational and financial performance.
Fraud Shield as a Signal of Industry Evolution
Among the technologies shaping this evolution, OCTO Fraud Shield stands out as a relevant example. Leveraging a vast telematics data lake and AI models trained on thousands of real incidents, it identifies anomalies, supports investigations through automated preliminary analysis, and contributes to a lower Loss Ratio. Crucially, it enhances fraud accuracy by reducing false positives — a key limitation of traditional fraud detection systems — and distinguishing suspicious behaviors from legitimate ones.
The Future: Integrated, Intelligent, Real-Time Fraud Prevention
The next generation of insurance fraud prevention will rely less on manual checks and more on dynamic, real-time data analysis. AI-driven fraud detection systems capable of interpreting actual claim circumstances will become essential.
A smarter, integrated, and predictive fraud prevention model is no longer just a competitive advantage — it is the new market standard for insurers aiming to ensure speed, sustainability, and transparency in their operations.
AI as an Operational Accelerator in Fleet Management
Companies managing large fleets face three clear priorities today: cost control, operational stability, and risk reduction. Artificial intelligence addresses these needs by turning vehicle-generated data into immediate, actionable insights, enabling fleet managers to make faster and more precise decisions. As vehicle connectivity continues to expand, the volume of available information has grown significantly: diagnostics, actual usage, driving behavior, consumption patterns and traffic conditions become factors that, when interpreted correctly, help predict issues and optimize asset utilization. Applied to these data flows, AI can identify behaviors that increase exposure to risk, enhance driver safety and reduce avoidable incidents, with a direct impact on service continuity.
The same predictive logic applies to maintenance. Understanding exactly when a component is likely to deteriorate allows interventions before a failure leads to downtime, reducing unexpected costs and keeping the entire fleet fully operational. Acting in advance rather than reacting becomes a tangible competitive advantage, especially in complex scenarios such as mixed fleets, multibrand environments or high-utilization assets. AI provides a comprehensive reading of the vehicle by integrating technical parameters with real usage conditions, offering a complete overview of asset health throughout its lifecycle.
At the same time, energy optimization and the management of thermal, hybrid and electric powertrains require a progressively data-driven approach. AI makes it possible to assess different operational scenarios, forecast actual energy consumption, detect inefficiencies and understand which routes are genuinely suited to electrification. This enables companies to make more informed decisions from both an economic and sustainability perspective, reducing waste and maximizing the use of available energy, regardless of the technology deployed.
The evolution of fleets toward integrated digital ecosystems makes it necessary for telematics, analytics and operational processes to interact seamlessly. AI does not replace the fleet manager; it strengthens their ability to interpret complexity, prioritize daily actions and develop more robust strategies. The ability to unify data from vehicles, drivers and infrastructure into a single, coherent interpretation shifts management from a tactical approach to a truly Total Cost of Mobility-oriented vision, where efficiency, safety and asset value reinforce one another.
Organizations that adopt intelligent tools in fleet operations not only reduce costs and downtime—they build a more stable, scalable operating model. AI becomes a practical enabler for competing in a market where fast decisions, accurate planning and the strategic use of data represent the new drivers of performance.