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Survey Report

Fields of dreams: Three areas dominate the field of insurers’ aspirations for advanced analytics

2019/2020 P&C Insurance Advanced Analytics Survey Report (North America)

Insurance Consulting and Technology

January 28, 2020

Many insurers aspire to build up their advanced analytics reserves, notably in the areas of customer experience, claim management and telematics, according to our 2019/2020 P&C Insurance Advanced Analytics Survey Report (North America).

Fields of dreams

Three main areas dominate the field of insurers’ aspirations for advanced analytics: the customer experience (incorporating underwriting and pricing), claim management and applications of telematics. AI and machine learning techniques are also starting to gain more adherents.

Customer focus

Competition for customers’ time and attention — both private and commercial — is only getting more acute. Engagement, and speed and efficiency of service are arguably becoming virtual hygiene factors for commercial success.

That said, a small core of just over 10% of respondents maintain they are not trying to improve customer centricity. However, of the large majority that are, the main priority, regardless of the size of the carrier, remains speed — of both service and access to information (Figure 2). This is further reinforced by how insurers are currently using advanced analytics in underwriting and pricing, and their future plans in these areas. Over three-quarters in pricing, and half in underwriting/risk selection already use advanced analytics, and about 90% expect to be using them in both areas in two years. Furthermore, companies are targeting straight-through processing for the biggest jump in activity in the near term.

The fact that many insurers haven’t met their previous targets for enhancing customer centricity may principally be a result of relatively slow progress in diversifying the range of data available for analysis.

The fact that many insurers haven’t met their previous targets for enhancing customer centricity may principally be a result of relatively slow progress in diversifying the range of data available for analysis. For example, 77% expected to be using internal customer data by now, but only 54% are. Similar gaps in expected versus actual usage have developed for social media (46% versus 26%) and clickstream data (34% versus 14%). Such results haven’t, however, dented ambitions. In all data categories except customer surveys, carriers project wider usage in 2021 than they had forecast for 2019.

Figure 2: Areas of customer experience targeted for improvement by carrier size

Claim management

In comparison with progress in other areas of their businesses, many insurers have gone the extra yard with integrating advanced analytics into the claim process. This is likely stemming from early adopters that primarily targeted improvements in pricing and underwriting, and now see claims as the next big thing. This certainly seems to be the case for Canadian insurers in the survey, judging by their enthusiastic response to a question about short-term intentions, albeit not according to their progress to date.

Although the enthusiasm hasn’t translated into substantial increases in the use of advanced analytics in different aspects of claim management since 2017 (Figure 3), there has been appreciable growth in the use of certain types of related data.

Unstructured internal claim information is the primary targeted source. Over half of commercial lines insurers say they are now using such information, up from 41% two years ago. In personal lines, the use of images (most typically used to verify and expedite claims) has more than doubled to 24% of respondents — nearly on par with where respondents expected it to be two years ago.

The current situation in claims also varies quite markedly by business line. For example, more than half (54%) of workers compensation writers say they are using advanced analytics in claims, compared with 10% in commercial property. Without exception though, all lines of business are behind the schedule they anticipated for claim analytics.

Figure 3: Aspects of claims for which companies use advanced analytics — 2017/2019

Telematics

Because of the volumes of data and the number of data points associated with telematics, creating actionable analysis from it is complicated and a significant undertaking.

Because of the volumes of data and the number of data points associated with telematics, creating actionable analysis from it is complicated and a significant undertaking.

The latest survey results suggest that personal lines carriers (and some commercial carriers) will continue to push forward with telematics, while others are turning to lower-hanging fruit in the area of analytics.

Evidence to support this hypothesis includes the relatively slow volume growth in carriers using telematics in both personal auto (from 28% to 30%) and homeowners (from 2% to 9%) in the last two years and, related to that, the relatively high percentages of carriers that say they have no plans to use telematics in these and other lines of business (Figure 4).

Similarly, when compared with results from two years ago in pricing, underwriting and claim triage, respondents currently see the impact of telematics on various functions as diminishing over the next five years. Indeed, executives questioned for the survey see it falling in virtually all business areas, including loss control and customer behavior modification (e.g., distracted driving).

Figure 4: Current usage and future plans for use of telematics by line of business

Fresh fields — AI, machine learning and InsurTech

By any measure, the volume of industry discussion about the value of AI and machine learning to insurers has increased significantly in the two years since our last survey. This is reflected in how insurers say they expect to develop analytics techniques in the future, with quite significant jumps forecast in the use of techniques such as decision trees, text mining and natural language processing, and gradient boosting machines.

Nonetheless, the progress reported by insurers since 2017 falls well short of expectations and has mainly taken place in three business applications — building risk models for decision making, reducing the time spent by humans on repetitive tasks and gaining a better understanding of risk drivers (Figure 5).

The intentions are clear: Expectations for 2021 leave a lot of work to bridge the gap between where 30% to 40% of companies say they are today and where they want to be in two years’ time.

The intentions are clear: Expectations for 2021 leave a lot of work to bridge the gap between where 30% to 40% of companies say they are today and where they want to be in two years’ time.

One potential shortcut to progress in this and other areas is closer collaboration with InsurTech businesses, where the focus seems to have recently shifted from the end customer to improving insurance back office efficiency. This remains pretty much virgin territory for the majority of insurers, with 91% characterizing their involvement with InsurTech as nonexistent or early stage. Just 1% of survey respondents have what they describe as a fully integrated and resourced InsurTech strategy.

Figure 5: How insurers are using and plan to use AI and machine learning
Actual for 2017 Expected for 2019 (in 2017) Actual for 2019 Expected for 2021
Build risk models for better decision making 13% 44% 26% 60%
Reduce time spent by humans 11% 49% 22% 60%
Better understand risk drivers 21% 44% 20% 56%
Identify cases that pose higher risk 11% 46% 14% 50%
Augment human-performed underwriting 7% 37% 7% 47%
Identify patterns of fraudulent claims 9% 39% 17% 47%
Identify bottlenecks in claim processes/Process claims more efficiently 3% 30% 7% 43%
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