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Thanks to technological advancements, insurance service for policyholders, distribution partners and internal stakeholders should be better than it was 20 years ago. But it’s not. If you visit practically any carrier, you’ll notice that service — managing data, applying service knowledge, managing the associate workforce, customer interactions and performance, as well as compliance and oversight — remains a disjointed exercise supported by a host of systems that don’t talk to each other, requiring double and triple data entry, and desks covered in countless sticky notes.
This problem is more than just an inconvenience. These back and mid-office services underpin everything insurers do and set the baseline for success. When they’re ineffective and inefficient, they hinder company strategy and operations.
As we’ve noted throughout this series, the clear path to competitiveness is putting the customer first, with the ultimate goal of reinventing the business of insurance. The industry’s traditional approach, i.e., incremental and pragmatic change, will not achieve these goals, particularly when it comes to the functions that rely heavily on new technologies to be effective and support the rest of the business. In fact, because the world outside insurance is likely to continue changing quickly and dramatically — especially when we consider the likely impacts of generative (genAI) — a customer-first approach to the future is the minimum. And to meet customers’ expectations, radical reinvention of service needs to be a carrier priority.
Surprisingly, there’s typically considerable investment in service technology. However, most carriers have only incrementally improved their overall service because too many “reinventions” have taken place within solitary functions. In other words, most organizations have lost sight of the interdependencies between different service disciplines and how they make or break each other. This compromises the stakeholder experience and ultimately the bottom line.
Here are some prominent examples of the ways in which the back- and mid-office wind up stuck in first gear and how you can move them — and as a direct result, your business — into overdrive:
Current challenges: Typically as a result of insufficiently supported, one-off data initiatives, many carriers fail to exploit their greatest asset: their own operational data. Without ready access to this data, carriers can’t easily answer questions from customers, distributors and business leaders. The problem is exacerbated by the high standards of companies from other sectors that have put data at the heart of their strategies and have begun to enter the insurance industry and insurance-adjacent market niches.
What you can do: The three steps to operationalizing data are defining a logical data model that faithfully models your business, defining and prioritizing the data-driven use cases that support business strategy, and establishing a cloud-based repository where data can be amalgamated, maintained and made widely available for both analytics and service. Once you’ve achieved this, you’ll need a data governance system that tends the garden and keeps it from becoming a weedy mess.
We’ve already seen this approach facilitate effective management of a wide variety of valuable data, both financial and operational, with GenAI proving particularly useful. Moreover, in this scenario, data scientists work hand-in-hand with business owners to solve business problems and measure business performance, using empirical data to validate that investments in service are worthwhile.
Current challenges: Compliance is absolutely essential to insurers’ ability to do business, and senior management naturally want to avoid regulatory complications. However, most carriers view compliance and governance as a cost center and drag on operations. As a result, they don’t always select and fund appropriate compliance tools and protocols, missing out on helpful technology and data that can mitigate risks and support coordinated compliance throughout the organization.
What you can do: As you improve how you use data and technology (see above), you’ll have the opportunity to incorporate effective governance and oversight into every aspect of service. Because much (if not most) of service centers’ routine work is likely to be automated in the not-so-distant future, it will be essential to incorporate the appropriate level of oversight into functional design and coding.
With proper structuring and management, the back office can effectively meet regulatory requirements and have built-in capabilities for oversight and monitoring of first-line-of-defense compliance activities. The expanded use of data also will introduce useful tools for the second line of defense, including additional real-time oversight that leverages automated reporting, triggers and controls throughout the end-to-end process. With such regular evaluation and iteration of capabilities at the center, management can expect company strategy to closely mesh with genuinely enterprise-wide compliance.
Lastly, as we note elsewhere, responsible AI and analytics should be a foundational part of carriers’ compliance efforts. As service functions use increasingly more advanced analytics techniques, there will be a corresponding need to apply governance around the data the organization uses and the decisions the data informs. This includes how the company monitors and maintains decisioning models. Carriers will need to provide employees appropriate training and maintain effective oversight of their use of new technologies, and — even more importantly — validate that those technologies align with applicable regulations and company strategy.
Knowledge management challenges
It’s an unfortunate truth that sticky notes and long-tenured associates are insurers’ true knowledge management platforms. While capturing and democratizing knowledge has been on carriers’ agendas for years, it rarely outranks other initiatives as a priority.
This disjointed and uncoordinated approach usually depends on a few key individuals — raising succession risks and thwarting the leverage the organization could enjoy if it could widely apply its experience and talents. Even the carriers that have centralized their knowledge management functions have largely failed to instill rigor and discipline around maintaining them. As a result, they’ve seen their repositories become more of a round filing cabinet than a single source of the truth.
Current workforce management challenges
This uncoordinated approach to workforce management. Spreadsheet-based headcount and capacity planning isn’t effective. Though it keeps the wheels of service in motion, it’s an inefficient and reactive approach. For example, carriers often increase their temporary workforce when they experience seasonal back-office surges. However, this approach typically pulls experienced people off the front lines to train temps and causes unexpected surges in operating costs.
What you can do
Carriers should stop attempting to check the box with outdated, unengaging repositories of standard operating procedures. They instead should invest in a cloud-based platform for capturing and organizing service standards in easy-to-consume videos that enhance the onboarding experience, facilitate measurement of ongoing professional development and enable knowledge uptake. GenAI can help improve service by making this video content accessible to chatbots as they answer questions online. Anything that can be codified will be automated in the near future, and even areas that require human intervention will be enhanced with models that help improve service through a feedback loop of measurement and refinement.
It’s important to note that there are certain underlying conditions you’ll have to meet before you can effectively scale and responsibly implement GenAI. Specifically, you’ll need to be on the cloud and largely digital. As we note above, GenAI also requires a secure IT environment featuring effective controls and oversight, cybersecurity and data governance. In other words, the more digitally mature your company is, the easier it will be to economically and quickly deploy GenAI.
Current challenges: Leaders at most insurers know they have to put the customer at the heart of their strategies so they can better understand who their buyers are, their expectations and service channel preferences, and the interactions that matter most to them. However, carriers have often struggled to execute the customer journeys and interaction management they’ve mapped out.
This disconnect between aspiration and execution is usually caused by inadequate focus on what really matters and how to differentiate products and services. Many service models don’t adequately prioritize and incorporate competitive advantages, staff and agents don’t receive adequate training about them, and there isn’t meaningful accountability throughout the organization to build on them.
As a case in point, presuming that “digital” is the means to fulfill customer needs, many carriers have made significant investments in online channels. However, they’ve typically wound up deploying “digital for all” without a nuanced understanding of customers, ultimately resulting in digital for none. More specifically, a carrier’s digital offerings are only as good as its underlying data resources. Providing a chatbot to interact with customers and distribution partners is great, but what good is it if there’s no central source of truth it can access? If you don’t establish a measurement framework before you release bots, how will you know if they’re being effective, necessitating staff retraining or actually increasing customer frustration with your service instead of improving it?
What you can do: As we have described in more detail in our recent perspectives on customer-first strategies, focusing on the customer is simple in theory but requires a lot of work behind the scenes. Effective customer-centricity is the result of refined and integrated:
Current challenges. From the C-suite to business units and operations, many carriers don’t establish clear criteria for what defines success in the above areas (and beyond) and have subsequent problems measuring it. This means they’re often unclear about where and why they’re succeeding or failing. They also lack measurable performance metrics that can help them identify the initiatives that are successful and why, and — as importantly — understand what needs to improve.
What you can do. You should apply the widest possible range of customer, distribution partner and associated data (e.g., from social media) to measure your performance vis a vis their behavior and sentiments. Reporting should focus more on outcomes than after-the-fact, infrequently measured promoter scores. After you determine areas for improvement, you’ll need to define and implement a feedback loop and resolution strategy and make standard mechanisms for identifying and prioritizing enhancements, including rapid piloting and test and learn.
This effort should lead back to customers and other key stakeholders via service models for supported and unsupported channels. The former can help you differentiate yourself to high value customers and partners while the latter can help you efficiently serve smaller scale buyers. Importantly, you’ll be better able to:
PwC’s Paul Livak, Sarah Petuck and Marie Carr contributed to this report.
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PwC's Sarah Petuck and The Standard's Sarah Ross discuss "customer first," and what it means for insurance service.
Topic sections:
Click on the video above and drag the bottom bar to the timeline shown below.
00:00-02:00 | PwC's Insurance 2030 overview
02:01-06:57 | Meeting customers' expectations
06:58-09:29 | Operational data opportunities
09:30-11:36 | Knowledge and workforce management
11:37-14:07 | Service transformation within insurance service
14:08-16:44 | Service strategy delivery
16:45-21:11 | Looking ahead and radical change
21:12-24:06 | Lessons learned
Senior Manager, PwC Insurance Consulting
Sr. Director, Contact Center, The Standard