Actuarial Analysis Team Finds Success with Nomad Data
A Canadian property and casualty insurance company turned to Nomad Data to discover datasets to improve their underwriting process across several of their insurance lines. Over the course of three months the insurer submitted thirteen data requests for a wide range of topics, including foot traffic, business attributes, ESG, risk factors, consumer demographics, and commercial real estate.
For each new use case the Actuarial Analyst quickly outlined the potential underwriting improvement in a few sentences and added a handful of clarifying questions to help qualify responses. Each request was routed via Nomad Data’s machine learning algorithm to a handful of the over 1,800 data vendors on the platform. Within hours the Analyst began receiving tailored responses from multiple providers, and days later was in conversation with those which warranted further exploration. At the time of publication, the Analyst was in deep evaluation or negotiation with eight of the vendors.
Anonymity was also important to this buyer, so they chose to hide their identity at the start of each request. Even after approving a data provider the buyer was able to ask questions anonymously; only when they decided to move forward with an evaluation did they need to disclose their identity.
The amount of data available to corporates, consultants, and investors is increasing at a rapid rate. With over 1,800 data providers and growing on the Nomad Data platform, business users can quickly sift through a cluttered data environment and connect their use cases to the handful of relevant data sellers. Because no one knows their data better than the sellers themselves, cutting out the middleman allows the parties to directly connect, making the process much more time efficient and each connection much more valuable.
Each time I submitted a new request I couldn’t believe how quickly I received responses from qualified data vendors, irrespective of the varied subject matter of my use cases. The capability to search a broad use case and receive differentiated context from a wide set of vendors helped me to narrow down exactly which data would best improve our underwriting performance.
- Actuarial Analyst, Canadian insurance company
