Underwriting needs to advance. It can do so by embracing continuous underwriting to empower both underwriters and customers. A Society of Actuaries presentation defines continuous underwriting: “It refers to the use of regularly updated (and possibly real-time) policyholder data to rapidly determine consumer risk and adjust policy terms and prices accordingly, as opposed to traditional term-based updates and renewals.” This is achieved by improving risk assessment to drive profitability. Predictive data is quickly becoming a part of the underwriting process for many insurers.
Predictive insights make insurance more efficient and profitable than relying on reactive data such as loss history. The understanding is that data is needed, and not just for reviewing after the fact, but as an integral thread that carries through the entire insurance lifecycle. This is beginning to have a transformative effect on insurance. For example, predictive data is already proving useful for increasing retention and making upsell efforts more effective, and it’s good for insurers and policyholders alike. However, complexity is part of proactively collecting and managing relevant and predictive data insights before, during, and after the risk evaluation timeframe.
Complexity emerges from the number of data sources that have exploded in recent years. New sources need to be vetted, and then also plugged into processes where risk is evaluated. A decade ago, who would have thought claims managers and loss adjusters would be checking Facebook pages before rating a business owners’ policy? Yet here we are. In many cases insurers are using similar data to build that business owner policy (BOP) product in a way that meets the policyholder’s needs before they even go to market. To that end, we have to acknowledge that there isn’t a set timeframe for risk evaluation in today’s insurance lifecycle. Risks still need to be evaluated at policy inception and renewal, but there are numerous opportunities now to underwrite continuously—usage-based insurance demands it, for example.
A number of developers are building excellent solutions for gathering data from various sources and they’re often designed for very specific market areas—a common example is driving behaviour collection for personal auto policies. Whatever an insurer’s data needs, there’s probably a solution out there to meet them, and sometimes the key is just having a solid framework for connecting that data to policy administration where it can be used effectively. In the following interview, Eugene Lee, senior vice president and general manager of InsuranceSuite at Guidewire, speaks ahead of his Intelligent Insurer webinar presentation, “Embrace Continuous Underwriting to Empower Underwriters and Customers, Improve Risk Assessment, And Drive Profitability”, which will be held on Thursday, July 22, at 3pm BST/10am EDT.
What tools can insurers use to leverage real-time data flows to improve decision-making and to deliver dynamic services to customers? It comes down to true integration. It requires a system that’s built to incorporate data into the workflow for underwriters, product managers, claims adjusters—anyone touching policies or insurance products. With data no longer being a “nice to have”, it is important to get it embedded into processes so it’s available in a way that is useful. Where and when it’s needed is key.
As far as dynamic services for customers goes, predictive analytics in particular are helpful in making sure policyholders are offered the products they need, when they need them, especially in upsell or relationship-deepening situations where we know something about that customer and can offer them a tailored experience.
Data can also help us reach out to customers proactively to help mitigate risk: for example, sending notifications about imminent weather events.
How can insurers fine-tune risk assessments by combining the most useful external and internal data to help differentiate risk, and pave the way for more sophisticated segmentation, risk selection and pricing decisions? You said it in the question: combining all these elements with some aspect of appropriate automation is the way to go. You have to be able to identify specific pieces of data that are likely to affect a customer’s risk profile, or their appetite for a policy enhancement or new product, and put processes in place to make sure that those things are identified, and actioned on at the right times.
This is an area where data comes together with services to create something great. It’s two sides of the Amazon/Netflix experience—we’re all used to the “you might like” recommendations based on what we’ve already watched or purchased, and that’s the process for offering new products, but the same concept can be applied to “your rates need to be adjusted” based on risk indicators.
“Predictive analytics in particular are helpful in making sure policyholders are offered the products they need, when they need them.” Eugene Lee, Guidewire
What are the best ways to cultivate smart operations to enable a streamlined and frictionless experience for customers, establish simpler business processes with fewer steps from application to quote, and leverage pre-fill to ask fewer questions and cut the turnaround time to issue a policy?
It’s a balance. You can’t automate everything, particularly with complex lines of business, but you do have to automate the right things. Autoclearance and autoassignment of submissions to specific underwriting groups are the most obvious—write smart rules that allow technology to do as much work as it can do, then get the submissions to people with the knowledge to complete the process.
Pre-fill is obviously huge for getting more submissions in: a customer is less likely to abandon a submission before completing it if most of the work is done for them. Obviously, this isn’t foolproof, and pre-fill is not always 100 percent reliable, so some things can’t be addressed this way. But when you add the automation of simpler process steps to increased submission volume, you have a recipe for writing more, and more profitable, policies. Insurers can use data and analytics to streamline the process and save time for underwriters. In addition to things such as autoclearance and submission assignments that address entire submissions, data can also help identify specific areas of a submission that need an underwriter’s attention.
For example, embedded data in the underwriting workbench could help an underwriter quickly identify specific properties on a commercial lines submission that may pose higher risk and require specific attention.
What are your top 5 tips for embracing continuous underwriting to empower underwriters and customers?
- Automate what you can and infuse data into your processes to help underwriters do the rest efficiently and accurately.
- Make the shift from reactive to proactive risk analysis, and infuse data into every step of your workflow. For example, invest in data and analytic solutions that are interoperable with your rating engine to produce automated, transparent, and consistent outcomes when it comes to pricing risks.
- Iterate: regularly consult your data at a macro level and make sure your rules, processes and automation are doing what you want them to do.
- Embrace non-traditional data sources, verify their reliability, and integrate them into your day-to-day processes. This can mean anything from driving data from internet of things devices such as those used for usage-based insurance products, to non-obvious data gleaned from web-based sources for things such as small business policies, and whatever the cool new data source will be tomorrow.
- Go omnichannel: make sure the data is constantly available to automated processes and to people making more complex decisions.
What would you like delegates to take away from the webinar and your presentation?
I want people to leave this webinar excited about infusing data more deeply into the underwriting process. The world is shifting to an “always-on”, continuous model—we see that in the news cycle, in entertainment, in customer service—and insurance is certainly not immune. Continuous underwriting will be a key component of making this shift successfully, not only in winning new business but in increasing retention and wallet share with existing customers. Insurers should all be extremely excited about what we can do for insurance customers and for underwriters with the level of data now available. It can feel overwhelming, but used strategically it’s a game-changer. Remember that your core systems are still where the magic happens, so that’s where the data needs to be in order to be effective.
In insurance, we used to think that merely having a bunch of data was great, but that’s no longer enough—now you need to make that data usable and available when and where products are being built and policies are being written, as well as serviced.
At Guidewire we’ve worked to integrate several kinds of data and analytics, as well as the digital experience, deeply into our core systems, along with a robust integration framework that allows InsuranceSuite customers to pull in data from a variety of third-party services as well.
Hear from Eugene Lee, senior vice president and general manager of InsuranceSuite at Guidewire, by enrolling in this Intelligent Insurer webinar titled “Embrace Continuous Underwriting to Empower Underwriters and Customers” on Thursday, July 22, at 3pm BST/10am EDT, and learn to augment straight-through processing with advanced data and analytics to enable automated coverage and pricing recommendations, to empower underwriters to focus on complex risk decision-making and strategic relationship-building with customers and brokers.
Guidewire, InsuranceSuite, Technology, Underwriting, Society of Actuaries, Insurance, Reinsurance, Eugene Lee, North America