The Future of P&C Insurance in Canada: Part 2 – Underwriting and Pricing

In our first article outlining the future of P&C Insurance in Canada, we discussed how insurers have been and are continuing to invest in digital transformation agendas in an effort to reshape distribution and service in an industry that has been relatively slow to adopt modern business practices. We illustrated how the sector will evolve by focusing on how consumers (both individuals and small-medium enterprises) are beginning to interact differently with carriers and brokers to obtain new policies and have them serviced once those policies are in force.

In part two of our three-part series, we focus on how insurers are changing their underwriting and pricing practices to be more sophisticated, efficient, and profitable.

Underwriting and Pricing

From an underwriting, pricing, and risk selection perspective, two factors will impact risk assessment, pricing, and underwriting in the future:

1. Data collection and use
2. Increased use of automation and integration of technology

Data collection and use

Concurrent to the digital transformation wave is the rise of big data. As a result, many insurers are looking at their enterprise architecture and setting up data lakes in the hopes of realizing benefits down the road. The promise of these benefits is high as the variety, velocity, and volume of data continues to increase, and insurers create the infrastructure, capability, and culture to exploit this data. Historically, external data sources have been expensive in Canada relative to other geographies, such as the UK where much of the data used for selecting and pricing risks is free. Still, the provincial regulators and collaborative organizations such as the Centre for Study of Insurance Operations (CSIO) understand how valuable data can be to the industry. Data enables insurers to underwrite and price policies more effectively while serving customers better, improving combined ratios, and passing collective savings on to customers.

By accessing additional data from outside parties, direct insurers can reduce the number of underwriting questions that results in a better customer experience. Digital quotes will have a much higher completion rate, and the average handling time (AHT) of calls should get shorter. Operationally, this makes a lot of sense, particularly if the cost of data acquisition decreases.

Lastly, insurers have been looking at alternative data sources to understand customer behaviours better and underwrite and price policies more accurately. Insurers have had a love/hate relationship with telematics. Data collected through an external dongle evolved into mobile apps, and more recently, car manufacturers have been embedding this technology directly into the cars they build. The regulatory environment varies provincially on how this data can be employed. It’s alright to offer a discount, but surcharges for poor driving aren’t yet permitted, although this too could change.

Moreover, regulators are looking to encourage product innovation. The pandemic has cast a bright light on a need for a true User-Based Insurance (UBI) product that better serves a population. For example, there has been a great degree of variability in how people use their vehicles during the pandemic; hundreds of thousands of cars are sitting idle driveways because many people haven’t commuted to work since March 2020. Financial Services Regulatory Authority of Ontario (FSRA) has taken a more progressive approach towards UBI than its predecessor by changing the Insurance Act to encourage innovation. FSRA has also created a ‘sandbox’ that allows insurers to pilot innovative initiatives. This enables insurers to bring new consumer-focused products and services to market more quickly in response to changing consumer needs before rolling out massive programs.

Increased use of automation and integration of technology

Despite the implementation of modern technology platforms, several processes are mired in manual work. For example, our previous article outlined how the intake process in the commercial insurance space is typically manual and time-consuming. Individual underwriters or underwriting assistants ingest a risk, triage who is best able to quote that risk, and then pass it onto an underwriter to complete a quote.

Modern underwriting organizations will use technology to increase the pace of all of these steps dramatically:

• Intake & Triage: Use of optical character recognition (some of which are AI-based), natural language processing, and text analytics to ensure that the risk is digitized and ingested into the system quickly and accurately. Robotic process automation (RPA) can route the appropriate risks to the individual underwriter, using rules to establish a general priority. Insurers can also use artificial intelligence (AI) to know in advance if a specific risk is worth quoting at all, which will free up valuable underwriting capacity through rapid declines.
• Risk Assessment and Pricing: Use of new data sources and risk propensity models with AI-based rules engines that include 3^rd party and proprietary data sources to assess individual risks more quickly and efficiently. Application of forward-looking predictive and dynamic pricing models that factor in market conditions and data sources. Larger insurers will have a competitive advantage in investing in and using these new data sources, whereas smaller insurers could be ill-equipped and suffer from anti-selection. In response, we could see a greater degree of consolidation or collaboration amongst smaller insurers to collectively take advantage of novel data sources.
• It’s also worth noting that dynamic pricing models are prohibitive in Canada for auto insurance because rates need to be filed. But applying similar approaches can increase the rate submission cycle and reduce any exposure of individual insurers’ rates being out of step with their forward-looking claims experience.
• Underwriting Processes: Underwriting referral processes that use workflow tools and case management practices ensure that more complex risks aren’t ‘lost in the system’ and have much faster turnaround times.
• Binding: The ability to bind policies quickly and efficiently through a digital channel allows customers to close the sale themselves. Underwriters have workflow tools that make the process quick and efficient, closing the loop with brokers or customers (when required) through automated/virtual underwriters or agents.

By becoming more adept at using data and optimizing processes, the modern insurer should be able to obtain several outcomes concurrently that will:

1. Increase productivity through workflow tools and automation
2. Increase accuracy in pricing models by applying new data sources and using modern data science techniques to better inform the risk being underwritten
3. Improve capital allocation and management of the portfolio of policies-in-force to better understand book quality and capital reserving needed
4. Better understand the markers that could lead to fraudulent events either at the time of underwriting or during a claim
5. Improve negotiations with brokers or agents for commercial risks by having better data behind pricing decisions
6. Better understand profitable market segments and become faster at developing new products to meet the needs of its customers
7. Ensure that customers are adequately covered through the next best action propensity models
8. Improve the ability to detect and fight fraud at the point of origination

As insurers continue to implement and enhance their core pricing and underwriting systems, add automation, and augment with complementary applications, insurers will become more customer-centric and operationally efficient. In addition, improved pricing and underwriting systems can support simplified products, enabling customers to use self-service channels to purchase and service their insurance policies. While there are a number of improvements that will certainly impact underwriting and pricing as described above, perhaps the biggest changes are occurring within the claims function. Our next article will explore the claims journey and how innovation and AI will create winning customer experiences that are more efficient and help limit both claims frequency and severity.

By: Andrew Wolch, Practice Leader, Insurance