Risk managers looking to drive better value and efficiency today need to know how to use data. Because it’s only through accurate, comprehensive and interpretable data that you can make more informed decisions that allocate resources more efficiently, enabling risk management to have greater impact on organizational success.
But how exactly can you improve data quality and use advanced analytics and artificial intelligence (AI) to reduce risk and increase value, particularly if your organization has a sub-optimal approach to gathering and maintaining data?
In this article, based on a webinar from our popular Outsmarting Uncertainty series, we offer practical insights to help risk managers modernize their approach by leading on better data use. We provide guidance and useful checklists on:
Leading the charge on re-wiring your data strategy may need to begin with communicating the drawbacks of sticking with an approach that’s not fit-for-purpose. Poor data strategies can have significant and far-reaching consequences.
Bad data can mean you overstate risk. The business may then be unnecessarily cautious. It could also face increased costs through paying too much for insurance; where insurers face gaps in risk data, they tend to make assumptions that err on the side of caution, making for higher premiums.
Conversely, if you understate risk based on inaccurate data, you leave the business more vulnerable to losses and business failure. Let’s say, your flood risk data on a property wasn’t accurate, you based your cyber insurance limits on bad data or your valuations for business interruption purposes were unknowingly low. You could face underinsurance, shortfalls when it comes to funding recovery and having to watch competitors bounce back better from events impacting your industry.
Getting a better grip on data is about value.
Flawed risk data means you might retain risks you should have transferred or walk away from emerging opportunities that could have paid off. If you allocate resources based on flawed data, your organization risks wasting resources on low-priority areas while neglecting high-priority risks, moves that could define its enduring success or ultimate failure.
AI can play a role here, taking poorly structured data out of spreadsheets and organizing it for ingestion and easier evaluation.
Your ability to identify good data and robust data management is crucial for delivering more effective, modernized risk management.
This checklist can help you evaluate the quality of your data, the internal actions you can take to improve it and where you may need to look for external support to fill gaps:
Supplementing your own data is another way to deliver more refined risk management. Integrating external data sources lets you fill gaps where your own data can’t give you the full picture.
Let’s say you’re reviewing your cyber insurance but haven’t had a loss for many years. Using external industry data, cyber loss forecasting and scenarios can help you make an informed decision that avoids over or understating the cyber risks most likely to impact your industry and business.
External data sources can also give you fresh perspectives through industry benchmarks or economic indicators. These could provide valuable context for your risk recommendations to business leaders.
Supplementing your data with external sources can also enhance the accuracy and reliability of your risk models, particularly important for complex risks best managed with a multifaceted approach, such as amplified and inter-connected exposures due to climate risks.
If you’re considering working with external data and analytics providers, you’ll need to be confident on the accuracy and efficacy of their own approach to data. Things you’ll want to look out for are:
Want to learn from businesses rewiring their digital strategy to realize more value? Watch the full Outsmarting Uncertainty webinar.
Your ability to drive more value from data lies in the quality and structure of the data itself, as well as the tools and processes you use to analyze and act on it. Can we help? Get in touch with our risk and analytics specialists.
WTW hopes you found the general information provided here informative and helpful. The information contained herein is not intended to constitute legal or other professional advice and should not be relied upon in lieu of consultation with your own legal advisors. In the event you would like more information regarding your insurance coverage, please do not hesitate to reach out to us. In North America, WTW offers insurance products through licensed entities, including Willis Towers Watson Northeast, Inc. (in the United States) and Willis Canada Inc. (in Canada).
