Unlocking the power of AI for comprehensive risk assessment in insurance
Oct 2024
The new capabilities in Gen 6 will allow insurers to more effectively detect, assess, and mitigate risk.
Oct 2024
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Introducing Gen 6: The next generation of Nearmap AI
We’re excited to announce the release of the 6th generation (Gen 6) of Nearmap AI. This upgrade features enhanced models and faster delivery speeds of key insights for insurers through. The new capabilities in Gen 6 will allow insurers to more effectively detect, assess, and mitigate risk — ultimately enabling faster and more accurate decisions across the policy lifecycle.
What’s new in Gen 6?
- Expanded detections: Gen 6 offers the largest AI detection offering on the market, featuring 130+ detections and scores — including categories like roof condition, roof characteristics, roof objects, yard objects, overhangs, ground surfaces, and more. This expansion is purpose-built to cover a wide array of insurance use cases, ensuring that property insight is more comprehensive than ever.
- Improved accuracy: With increased accuracy and confidence on nearly all detections, insurers can better assess property conditions and associated risks. Whether it’s identifying roof shape, roof condition, or vegetation hazards, the refined models in Gen 6 provide a more reliable foundation for making informed decisions.
- A holistic understanding of peril risk: Peril scores (bushfire, cyclone, hail, and wind) are now included in the latest generation of Nearmap AI insights. These scores are proven to predict claims and are validated and approved for rating in many states. With new detections like woody vegetation, leaf-off vegetation, wooden decking, and low vegetation overhang, the peril scores have elevated performances and provide greater predictive lifts for carriers.
The role of AI in elevating risk assessment
Insurance underwriters and risk managers have long recognised the need for up-to-date, high-quality property data. Traditional methods of assessment often rely on outdated or incomplete information. But with AI-derived risk factors based on frequently updated aerial imagery, insurers can stay ahead of evolving property risks.
Nearmap AI models categorise insights into 10 key categories, including roof condition, yard objects, roof objects, vegetation, and property characteristics. These comprehensive insights provide a holistic understanding of a property’s risk profile, ensuring underwriters make accurate and timely decisions. As a result, insurers can streamline their underwriting process, minimise costs, and reduce exposure to unanticipated losses.
Use cases across the policy lifecycle
- Quoting: Nearmap AI identifies crucial property details like roof material, story count, and the presence of features such as swimming pools, trampolines, and solar panels. This enables insurers to prefill quotes with precise data, ensuring that pricing is aligned with the real risks associated with the property. By detecting up to 12 roof shapes and 13 roof materials, the platform effectively supports quoting for both residential and commercial properties.
- Underwriting: AI-derived insights benefit underwriters because they provide a deeper understanding of property risks, the change of risks, and help determine liability/casualty coverage — such as the presence of swimming pool, solar panels, yard objects, and the condition of ground surfaces. In addition, the relevant detections are converted into easy-to-use scores, like the Roof Spotlight Index, and other peril scores that accelerate underwriting workflows. The ability to accurately assess risks like wildfire exposure or the potential for damage from wind due to overhanging trees improves decision-making and risk evaluation.
- Loss control: AI detections empower insurers to be proactive in loss prevention. By analysing property conditions and potential hazards, insurers can recommend mitigation steps — such as clearing vegetation or addressing poor pavement conditions — to policyholders. This reduces the likelihood of future claims. It also optimizes inspections by focusing only on high-risk properties, and inspectors are equipped with targeted insights, making the process more efficient.
- Data science and rating: Accurate risk modeling is crucial to developing fair and effective rates. AI-derived insights, like roof shape and condition, are translated into peril scores that uplift predictive models. These models help insurers to refine their rating processes, improve claims outcomes, and better manage their portfolios by predicting loss more effectively.
- Claims: Claims handling is significantly enhanced by frequent high-resolution aerial imagery and AI insights, which help adjusters assess damage, detect pre-existing conditions, and verify repairs. For instance, identifying pre-existing missing shingles or structural damage can help prevent bad claims, while confirming that roof repairs have been completed ensures claims are handled accurately. This reduces the need for on-site inspections for low-risk claims, allowing adjusters to focus on complex cases.
Proactive communication for policyholder engagement
AI insights also pave the way for more proactive communication between insurers and policyholders. With detailed property data, insurers can not only assess risks more effectively but also engage with agents and policyholders to recommend preventative measures. This fosters stronger relationships, as policyholders are empowered to take steps to reduce their risks — leading to fewer claims and better outcomes for both parties.
Providing peace of mind and truly protecting lives and assets are core responsibilities for insurers. Nearmap is at the forefront of enabling insurers to achieve these goals through comprehensive AI insights. Incorporating Nearmap AI Gen 6 insights into the insurance lifecycle represents a leap in efficiency and accuracy. Now, insurers can unlock the full potential of advanced data insights to optimise quoting, underwriting, loss control, and claims processes. The future of risk assessment is here, and it’s more powerful, transparent, and actionable than ever before.
Be more effective in detecting, assessing, and mitigating risk.