Startup MGA founders need to win customers with a compelling product at a good price while maintaining a favorable loss ratio — and do it all without the data that your competitors have.

We know that the road you’ve chosen isn’t easy. That’s why we've distilled our decades of pricing expertise and experience working with clients just like you into an e-book.

At Octagram, we specialize in squeezing out underwriting and pricing insights from data. We've seen data from large carriers to small MGAs, and everything in between. From this experience, here is our wishlist of 4 types of data that are commonly missing, and that we wish you had, to get you competitive insights.

You may be wondering how "good" your pricing model is. You may have poor results and wonder if you should invest to improve pricing. Or you have great results but wonder if you should tweak your model to continue to generate returns. Or you may see competitors charge significantly less but report good results, and you wonder if you are missing a trick.

To answer any of these questions, the first thing to do is to measure the performance of your current pricing model.

Cathy O’Neil and Jessica Leong gave a presentation to help actuaries get on the front-foot of the topic of bias, risk and regulation at the 2023 Casualty Actuarial Society Spring meeting.

O’Neil Risk Consulting and Algorithmic Auditing, Inc. (ORCAA) and Octagram Analytics announce a strategic alliance and a new service to help property & casualty insurers address emerging state regulations designed to detect unintended unfair bias.

The service is called INFER, which stands for INsurance Fairness Explainability Review. INFER helps insurers develop governance policies and practices to detect and prevent future bias. “Combining the expertise of both companies allows insurers to confidently approach model bias and compliance in the era of artificial intelligence,”said Jessica Leong, CEO of Octagram Analytics and former president of the Casualty Actuarial Society.

Every data science team in the P&C commercial insurance space has seen its fair share of models that have failed to achieve the hoped-for business benefit. If you are a leader in this space, how can you maximize the return on your data and analytics investment?