29 September 2026
Insurance customer retention in the AI age
How the 96% rule will deliver agentic outcomes for the insurance industry
Franklin Manchester
Global Insurance Strategic Advisor, SAS
The combination of forecasted softening premium growth and strong profits means future growth for the insurance industry must come from tactics other than premium increases. To enable growth in this market cycle, focusing on insurance customer retention strategies – to reduce churn, keep policyholders renewing coverage over time and protect policies in force (PIF) – is a priority. Stated differently: PIF is king again.
Across industries, the growing role of artificial intelligence (AI) in everyday interactions has reset customer expectations. Insurers will need to lean into new technological capabilities to meet customers’ needs if they expect to retain customer loyalty.
Slow premium growth, strong profits
Swiss Re forecasts real premium growth (non-life and life) for 2026 at 1.3%, with a slight increase to 1.6% in 2027. This is down 67% from 2025 (3.9%). At the same time, global carriers are reporting historic profits and policyholder dividends. In advanced markets, like the US, the National Association of Insurance Commissioners reported (in 2025) that underwriting income jumped by more than $40 billion compared to last year.
What policyholder retention means for insurance
Customer satisfaction, customer service and customer lifetime value in insurance are deeply valuable to the industry. Because in a highly commoditized sector, true differentiation and defensible space come from high-relationship, high-value touch points.
Some in the industry refer to these as “moments that matter.”
Many are already familiar with tactics like policyholder loyalty programs, real-time personalization and next-best action or cross-sell and upsell to increase insurance customer retention rates. But with today’s AI tools widely available to consumers and businesses, policyholder behavior has evolved. And with it, the insurance customer journey. More than ever, retention comes from a series of positive “moments” along a lengthy customer journey.
New customer purchasing behavior requires new approaches
According to the JD Power 2026 US Insurance Digital Experience Study, about half of all insurance policies are purchased digitally – meaning, customer buying behaviors have evolved significantly.
Customer relationships still matter, perhaps even more so in a digital ecosystem where insurance personalization can either create meaningful insurance customer engagement or destroy it. But for carriers, brokers and agencies, this shift signals the need to build long-term relationships in different ways to protect retention levels and grow policies-in-force.
The 96% rule
Retention analytics indicates that policy renewals react consistently to increases or decreases in “share of wallet.” The 96% rule follows a heavily linear trajectory. That’s why the industry invests heavily in multiline campaigns as part of its broader efforts in insurance policy or customer churn reduction.
In standard lines, a customer with one line of business retains at about an 88% rate. In other words, for every 100 customers with the same profile, 12 will lapse or churn in a calendar year.
This retention rate increases to 92% if insurers increase a monoline customer's share of wallet by adding another policy (assuming the customer needs a different type of insurance coverage). Adding a third line of business brings this rate to 96%.
Achieving this benchmark matters deeply – because on a billion-dollar book of business, an 8-point swing in retained ratio saves $80 million.
Why do you think we see so many “bundle and save” ads on television?
Getting out of the customer retention hole
The boost from policy renewals has a cascade effect. In addition to the premium dollars saved, it relieves pressure for new sales by reducing the sheer number of policies that must be sold to “get back to flat” (replacing lost customers).
Likewise, insurers retain a more profitable segment of the portfolio because new business policies tend to have higher loss ratios. The additional premium from increasing share of wallet also aids in premium growth goals.
It’s reasonable to expect the household premium for these target customers to more than double. And getting out of an insurance customer retention hole half as big is significantly easier than getting out of one twice as large.
Benefits of digital transformation
In a report, Swiss Re found that insurers were using digital transformation to target a 3% to 8% improvement on the loss ratio, and savings of 10% to 20% in other parts of the value chain. It also found that leaders of advanced economies would benefit faster from digital transformation due to more reliable infrastructure, investment in innovation, and technological advancements (such as AI).
Why is insurance customer retention so important?
A 1-point drop in retention could represent an 8-figure loss in premium (reversing the earlier calculation). So, retention not only boosts growth – it also helps maintain the size of the book and stabilize cash flow expectations.
Customers pay their premiums at a known cadence, and companies benefit through a known revenue stream. When insurance customer experience declines, policyholders cancel their coverage. This outcome directly affects the financial health and outlook of an insurance company.
Know why your customers leave
The list of reasons why customers leave – the underlying factors in achieving insurance customer loyalty – are well-known. They include:
- Poor claims experience.
- Unexplainable changes in premium.
- Coverage being reduced or removed.
- Disjointed customer service interactions.
- Unhelpful AI agents or chatbots.
- Invalid or unwanted offers.
- Ease of doing business (or lack thereof).
- Affordability and cost.
Customer interactions in traditional channels have been well-managed (through in-person, local agent or direct company interactions). But the rise of “digitalization” has created new digital risks for insurance carriers. Every possible interaction a customer could have across the insurance value chain has been replicated in the digital ecosystem. That includes buying a policy, asking a coverage question and filing a claim.
The benefits of digitalization come with downside risks, including cyber vulnerabilities, competitive pressures from disruptors, and both known and unknown customer behaviors. Such speed, ease and efficiency also come with a hidden, yet inherent risk. Simply put, it’s possible a customer could suffer a terrible experience and leave without a human ever knowing (until they were gone).
So, we look to the power of AI and predictive analytics to guide both online and offline journeys and to create what we call true omnichannel engagement.
The role of analytics and AI
Insurance companies have long used analytics for customer churn prediction, with customer complaint volume being a common example. Some companies track complaints through escalations originating from customer service calls or regulator inquiries. It’s reasonable to expect that as the volume of these types of interactions increases, customer cancellations will follow suit – meaning, churn will increase.
Fast forward to today. Now, customers don’t just have a human agent or a customer service rep to answer their questions. They also have AI-powered chatbots, contact forms and generative AI-fueled web search.
Customer interactions have become highly complex. In turn, building a cohesive and personalized view of a customer using all the data collected through these channels is a very involved, seemingly impossible task.
Real-life examples: Insurance companies that have solved the problem of customer retention
With marketing AI solutions, insurers can combine powerful machine learning and agentic AI capabilities to collect disparate transactions and activate those insights in meaningful ways. But the concept is not technology alone. It involves solving the business problem created by the dramatic shift in customer behavior (such as how policies are purchased or renewed).
Let’s explore some real-life examples to see how insurance companies are approaching this today.
Using AI-driven insights to enhance customer trust and speed processes
Together, HUK24 and SAS Viya prove that AI can truly be a tool for human connection and trust.
Direct insurer HUK24 positions its website as the customers’ primary point of contact. Treating its digital platform like a virtual insurance agent, the insurer wants to help users complete simple, standardized processes directly on the website – with more complex issues handled by highly trained processing colleagues.
To ensure every AI response is contextually relevant and helpful, HUK24 orchestrates search, chatbot and contact forms. At the core of its strategy is visibility into the AI's performance.
To bring clarity to the complexities of its virtual insurance machine, HUK24 linked data from upstream systems, cleansed and aggregated it, then loaded it into a SAS Viya environment for analysis. Here, KPIs were calculated and visualized in dashboards that became the cornerstone for decision-making across management, technical departments and AI training experts.
Now, customers save time and gain confidence while interacting with AI. It takes maybe 10 or 15 minutes to complete a process directly through the site – something customers deeply appreciate.
Using AI-based personalization to enhance customer engagement
"By using new technologies, we improve the efficiency of our processes and enhance customer satisfaction. Our Omnichannel Sales division demonstrates how important intelligent customer management is to meet our customers’ constantly evolving needs in a tailored way."
— Alexander Hombach, Head of CRM, ERGO
ERGO, one of the largest insurance groups in Germany and Europe, has implemented a comprehensive digitization strategy to make the customer experience as personalized as possible.
Long before the systematic use of AI, ERGO was already an early adopter of machine learning and deep learning. With this technology, they’ve experienced significant advances across multiple areas, including:
- Workload forecasting for customer service.
- Processing time and payment of legitimate claims.
- Next-best action/next-best offer for each customer.
Because of their steadfast focus on personalized customer experience, they recognized the strong correlation of online and offline channel interactions throughout the customer journey. This recognition allows them to meet customers at their individual point of contact by deploying “relevant messages at the right time via the right channel – instantly.” So, customers with young drivers may see auto policy offers, while a recently retired couple may receive information on travel insurance.
By taking advantage of both technology and a mindset of delivering tailored, fast and convenient service for customers’ constantly evolving needs, ERGO has achieved its strongest level of new business in over a decade – for the second consecutive year.
Other examples of AI in insurance customer retention
Using AI for online insurance services is not the only strategy we see carriers employing to maximize the value of their AI investments. While some have used AI to scale engagement through intelligent recommendations and automated service, other examples include:
- Predicting churn before it happens.
- Improving digital claims experience.
- Creating omnichannel customer journeys.
Augmenting, not replacing, humans
In its Work Trend Index Annual Report, Microsoft calls attention to leader sentiment regarding AI use. It is not a call to action to replace, but to enhance worker capacity. The report details that: “82% of leaders say they’re confident that they’ll use digital labor to expand workforce capacity in the next 12 to 18 months.”
The future of insurance retention
Natural language interfaces have shown us a glimpse of what’s possible through the power of today’s large language models. Agentic AI promises similar innovation and cost.
Consider the example of ERGO – a company committed to human-in-the-loop (or “human-in-the-lead”) technology. Their story illustrates a common desire of organizations to integrate advanced technology into processes and workflows that amplify – rather than replace – their own staff’s expertise.
This sentiment represents a far departure from big tech predictions of the “white collar blood bath,” which Sam Altman himself recently walked back. Said differently, the AI “jobs apocalypse” prediction is wrong.
So, insurers must begin considering the use of data and AI solutions that:
- Accelerate human capacity to work.
- Tune our thinking and strategy to account for those same humans to supervise the technology.
Think of how insurers can use agentic AI in a claim investigation, for example. As this blog post and demo illustrate, it’s no longer necessary for an insurance professional to interact with a policy administration platform to do their work. The future will entail marketers, underwriters and adjusters interacting with technology in natural language to complete their work. And that will provide a tremendous business benefit for insurance companies.
Return on investment for AI in insurance
In a 2025 report, SAS found the highest ROI for AI use was improving customer experience (not reducing costs).
Natural language interfaces represent just one branch of artificial intelligence that will be embedded in agentic solutions for customer retention, experience, engagement and beyond. Other AI capabilities include:
- Computer vision for building customer journeys or settling claims (as this insurer is doing).
- Prebuilt machine learning models to determine customer propensity.
- Agentic AI to build next-best action/next-best offer marketing journeys.
- Synthetic data generation to plug data gaps and protect privacy.
These capabilities are not science fiction or on a roadmap 10 years into the future – they’re available now. And the call to action for insurers is simply that you can and should invest in all these capabilities now. Achieving a world-class, 96%-retained ratio is not just possible; it is inevitable. And you can bet if you don’t achieve it, your competitors will.
But perhaps the best reason to invest in trustworthy AI is that your customers will expect the highest quality, most valuable interactions in their relationship with their insurance company. If you believe this to be true, then you already know: Premium growth through rate increases is dead.
Long live PIF.
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