Software-defined vehicles are reshaping risk but are insurers and financial markets ready?

Many believe that once an OEM deploys centralized architecture or OTA capability, it is fully SDV-ready. In reality, SDV readiness is multi-layered, uneven and exists along a continuum, which S&P Global Mobility has defined as Level 0 (not updateable) through Level 5 (full SDV). SDV-readiness spans: 

• Hardware. The maturity level of E/E architecture—domain, zonal or centralized. 
• Software. Whether the vehicle runs on a unified operating system, the nature of software architecture and the level of cybersecurity. 
• OTA capabilities. Basic, intermediate or full OTA capabilities. 

Why does this matter? Treating readiness as binary can obscure architectural weaknesses. To accurately assess risk, insurance carriers and investors must be able to understand where maturity exists and where gaps remain. 

The SDV value chain does not function like traditional automotive supply chains, where OEMs control everything and responsibilities are clearly defined. Historically, automotive supply chains were hardware-focused and relatively straightforward. Software was limited to individual electrical control units (ECUs) handling simple applications, and OEMs sourced components from Tier 1 suppliers that managed sub-suppliers. This model worked well for mechanical and early electronic systems. 

The landscape today is very different. The SDV ecosystem is not linear: it is layered and interconnected. It includes cloud providers, operating system vendors, middleware providers, hypervisor providers, cybersecurity partners, traditional Tier 1 integrators, complete software stack providers and OEM in-house software teams. These layers interact continuously, and software updates can affect multiple layers simultaneously. Supplier responsibilities overlap, and control is distributed across the stack.  

As a result, the vehicle becomes part of a digital ecosystem, not just a physical supply chain. Responsibility becomes shared, faults that originate in one layer may appear in another and cybersecurity maturity varies across layers.  

Understanding this ecosystem requires mapping architecture depth, supplier roles and governance maturity—not just identifying hardware suppliers. This visibility helps insurers identify dependency risks, anticipate supply chain-driven repair costs and recognize where systemic risks could arise.  

A common assumption is that increasing levels of autonomy will reduce insurance risk. If vehicles are better at avoiding collisions than human drivers, the thinking goes, insurers should expect fewer claims and lower overall exposure. 

But the situation is more complex. While advanced driver assistance systems and other autonomous capabilities may reduce accident frequency, they can also increase the severity and complexity of claims when incidents occur. Software-driven systems rely on sensors, cameras and increasingly sophisticated computing platforms. Repairs often require specialized parts, recalibration and software validation, driving up repair costs.  

The rise of SDVs also introduces new financial risks around liability. As vehicles move from driver assistance toward higher levels of automation, responsibility may shift among drivers, manufacturers and software providers. For insurers and financers, the transition to SDVs does not eliminate risk, it redistributes it, requiring new approaches.  

The SDV evolution has real business implications for insurers and lenders. As vehicles become more software-driven and interconnected, evaluating risk increasingly requires visibility into vehicle architectures, software capabilities and supplier ecosystems, areas that have historically been difficult to assess.  

Tools are emerging to address this information gap, including S&P Global Mobility’s SDV Suite of Solutions, which provides greater transparency into the SDV landscape. Such tools can support insurers in several areas: 

Data-driven risk assessment. More intelligence across software stacks, suppliers and architectures helps insurers better understand vehicle capabilities, safety features and usage patterns, enabling more accurate risk profiling and personalized insurance offerings. 

Enhanced underwriting and claims management. Access to real-time SDV data, such as OTA updates, ECU forecasts and autonomy features, can support more precise underwriting. When claims occur, insurers can quickly verify vehicle status, system health and even reconstruct accident scenarios, leading to faster and more accurate claims processing.  

Supply chain and repair insights. Mapping supplier relationships and sourcing trends allows insurers to anticipate repair costs and parts availability, streamlining claims, reducing fraud and improving customer satisfaction.  

New revenue streams. SDVs enable connected services and app stores, creating opportunities for insurers to offer valued-added services such as usage-based insurance, proactive maintenance alerts and safety coaching directly to policyholders though the vehicle’s digital ecosystem. 

Future-proof strategies. As the SDV transformation accelerates, insurers will need strategies aligned with evolving vehicle architectures and technologies to adapt products and remain competitive in a rapidly changing market.  

The rise of SDVs is transforming the relationship between technology, risk and financial exposure. The pitfalls highlighted here represent only a portion of the questions emerging in the SDV era.