The cyber market continues to lack harmony, and with increased scrutiny on both sides of the transaction, brokers must be more prepared than ever to advise their clients and justify their recommendations.
The right cyber risk analytics can arm brokers with data-driven insights to help navigate insureds through today’s challenging environment. Equally important, however, is the broker’s ability to successfully deliver these insights to clients in an understandable and meaningful way.
In this blog, we’ll explore how you can use cyber risk modeling effectively, and what else you need from your analytics solution partner to ensure you have the right insights to advise your clients.
Hardened market conditions continue to impact the way in which cyber insurance is procured. Heightened underwriting scrutiny coupled with a dynamic threat environment quickly illuminate shortcomings in an organization's cyber risk posture, placing significant pressure on brokers to ensure their clients' overall insurability and deliver on program objectives.
Analytics have become a necessary component of this journey, empowering brokers to demystify cyber risk and inform effective risk transfer strategies. But how exactly can brokers leverage analytics to achieve successful placement outcomes for their clients?
As part of the underwriting process, carriers are increasingly performing network perimeter scans and flagging security signals that indicate poor risk posture. Brokers would be prudent to surface these network observations to their insureds in an effort to remediate any issues before the quoting process.
A reliable analytics solution will leverage a diverse ecosystem of data to determine relevant insights, allowing brokers to identify key areas of exposure and streamline the placement process.
Threat actors often take the path of least resistance that will also yield the greatest payout when leveraging an attack. Understanding your client’s exposure across a spectrum of threat scenarios will help to narrow the focus on key risk drivers and areas requiring improvement. A comprehensive analysis will rely upon a combination of firmographic and internal and external security data to evaluate how well a company is safeguarding its assets, as well as how attractive they may be as a target to threat actors.
Brokers may then justify coverage and limit recommendations by highlighting the types of losses clients should be on the lookout for based on their high exposure to certain threats.
Cyber risk has emerged as a top concern across the enterprise, yet limited loss experience relative to more established perils and a constantly changing threat landscape pose a challenge for brokers when evaluating true exposure.
An effective modeling solution will marry historical experience with current market trends to provide a view of inherent financial exposure to cyber risk that can be further augmented by company-specific risk attributes. Calculating a range of potential loss outcomes across a variety of incident scenarios will translate an organization’s cyber risk into financial terms and thus fuel more relevant and productive conversations surrounding limit adequacy.
There is an important distinction to be made between how much limit companies are purchasing and the percentile of risk to which they are insuring. Brokers can differentiate themselves by utilizing a tool that highlights the relationship between these two values.
Does 10 million in limit mean your client is transferring 80%, 95% of their financial risk? How much risk are their close peers transferring, and how much limit does this translate to in the context of your client’s unique risk profile?
Comparing risk transfer strategies is an important lever brokers can pull to help clients understand their risk appetite and decide upon appropriate limits. Your cyber risk analytics solution should provide this additional layer of insight, allowing you to most effectively benchmark your client’s cyber risk against peers.
Once you choose an effective cyber risk modeling tool that suits your business needs and goals, making the most out of that solution can help ensure consistent, long-term profitability.
Work with your vendor to onboard your team, and consider designating internal champions to act as dedicated resources to triage questions from team members and support overall usage. Taking advantage of the expertise your cyber risk analytics partner has to offer will help to ensure that brokers are armed with the talking points they need to be successful.
During the onboarding process, ensure you effectively embed the solution into your workflow, taking into account renewal objectives across your book of business and identifying opportunities for differentiation in your sales pipeline.
At CyberCube, we understand the challenges brokers face in today’s dynamic market. If you’d like to learn more about what brokers need from a cyber risk analytics solution to optimize their workflow, check out CyberCube’s blog all about their risk modeling solution designed for brokers — Accelerate client engagements with Broking Manager.