What We Do

NeuralMetrics delivers risk insights through our risk intelligence data engine, which utilizes approximately 400 questions supported by 700+ AI models (and growing). These questions extract meaningful risk insights based on actual underwriting inquiries. We personalize the questions according to the risk factors and allowances of individual insurance organizations, allowing customization, prioritization, and addition of questions based on client needs. Each client’s inventory of risk-evaluation questions is unique and proprietary.

Our classification data engine leverages distinctive prediction models to determine accurate class codes down to the last digit. Whether it is NAICS, SIC, or other line of business codes such as WC and ISO GL, our classification engine enhances underwriting efficiency by aligning risk appetite with insurers’ insurance products.

Yes, our system typically prioritizes information sources based on their confidence level. Sources with higher confidence levels are ranked higher. The prioritization methodology can be customized according to client preferences. For example, if social media search results are preferred over information from business websites, NeuralMetrics can adjust the presentation of risk information accordingly.

We prioritize accurate data for efficient AI implementations. Our data management practices include validation, cleansing, and normalization processes to maintain uniform, clean, and current data. We emphasize source transparency, allowing traceability of outcomes to specific data origins and locations within the data source. Consistency in AI setup is established to ensure effective information-seeking and organization across diverse data sources. Our approach enables us to provide valuable solutions for accurate and contextual commercial lines underwriting, facilitating informed decision-making for our clients.

At NeuralMetrics, we combine structured and unstructured data from dynamic public sources, including online platforms, websites, social media, news articles, and other publicly available sources. We gather this data through a custom-developed web scraping mechanism. Our intelligent scraping technology efficiently and ethically collects data while respecting the terms of service and policies of the sources we scrape. Once collected, we utilize a graph data approach to store the structured data and build relationships, enabling effective analysis and extraction of insights. We prioritize data privacy and comply with relevant laws and regulations governing data usage and protection.

We assist underwriters in consolidating information about small and medium businesses, including neighboring businesses located around the insured. Through artificial intelligence, we provide accurate risk predictions based on limited data, enabling underwriters to assess risk impact with precision.

Clients can engage with NeuralMetrics in multiple ways. They can directly input information into our platform and receive the output. Alternatively, they can integrate our data engines with existing systems, calling ours via an API for real-time results displayed within their preferred interface. In this scenario, NeuralMetrics operates seamlessly in the background. Clients also have the option to perform a bulk upload for processing many insureds, which may be suitable for activities such as book rolls or acquisitions.