Case Study July 1, 2024

AXA

Transcript:

We really only know what our clients tell us or what their brokers tell us, and that’s not a complete picture.

And and having having technology and services that can augment our understanding of that risk, not only enables us to hopefully move faster, but also in the end, for a better service to our clients.

My name is Newcombe Clark. I work for a company called AXA. Which is, in some measures, the largest commercial insurance company in the world. So we, underwrite and manage and consult on essentially risk.

And my function is, basically applied r and d, kind of assessing, models. Right? When we would say, okay. Well, how quickly can we assess the model? And with a big organization like ours, particularly when we’re talking about some sensitive client data, you’ve got, you know, soup to nuts with legal procurement, sourcing, info security, data privacy, all of that needs to be true to bring it into our laboratory to actually do our our work as we affectionately like to say cyber risk makes everyone crazy.

And particularly when you’re trying to underwrite a very dynamic always changing risk landscape, right, moves at the speed of the internet quite literally.

There’s always a hunger to understand what new datasets, what tools, what services, could could improve our our understanding and our underwriting and our mitigation and management of those So a tool like secure scorecard can play critical role. There’s the proactive and reactive job of a underwriter. The policies tend to come up for renewal often once a year. And so you’re always kind of aware of how that risk may be evolving how the client’s needs may be changing. And then, you come to that point where you actually have to price it. Right? So you’ve got a body of activity that results in a snapshot.

And a tool executed score cutter can be helpful monitoring that risk throughout the life of the policy, understanding how it may be shifting and changing, perhaps it’s an opportunity for our risk consultants step in and saying, Hey, we’ve noticed something different about your risk, but then also when it actually comes time to to reevaluate the risk and think about, you know, what, what the insurance may may price at. There’s that that helpful snapshot that comes together. A lot of action behind the scenes for what ends up being a single number on a piece of paper. When we sit down to assess a technology, a tool, a partner, or usually looking for a couple of key things.

One is, is it intuitive, useful, understandable, do the users of SecurityScorecard understand what it does. The second is we really wanna understand the methodology and and how can that knowledge inform our youth. And then the third one is how predictive it is. And and can we often historically look at at what, a model could have predicted, what security scorecard could have predicted at the time, and then compare it to our own internal historical data.

So we’re always looking for those kind of three elements and SecurityScorecard’s really been, you know, quite exemplary on all three points. The team has been most impressed with how security scorecard’s own internal innovation and model development has progressed. It’d be perfect if, you know, you could one and done, say, this is the model that predicts it all and rules it all, but Cyber just doesn’t work that way. So it’s good to have a team that is always investing in their own view of risk and their own technology and their own product, and so that we can be ready to test what’s the latest and greatest.