In Part 1 of this blog series on Customer Choice in Insurance, we unpacked why understanding how customers make buying decisions about insurance is crucial to designing better journeys, and how choice architecture and behavioural economics can aid this understanding.
We also explored how behavioural biases like overconfidence, status quo bias, over-confidence and loss aversion shape the way people buy and use insurance.
This part 2 focuses on designing for trust: how insurers, MGAs and digital intermediaries can translate those insights into real-world experiences that help customers make confident, well-informed decisions, ultimately leading to customer retention, engagement and stronger relationships.
When choice architecture is done right, it doesn’t manipulate, it clarifies - strengthening customers’ trust in the product and in the firm providing it.
Flexible core insurance platforms enable better design
Our guiding product principle is to provide a flexible, reliable, and elegant core insurance platform.
Flexibility matters because it allows insurers, MGAs and digital intermediaries to craft products and customer journeys that use choice architecture responsibly, whether that means well-timed reminders, clear defaults, or carefully placed friction.
We’ve seen that when insurance businesses design this way, customers feel supported and protected, and long-term trust grows naturally.
Everyday insurance applications
These are 3 practical ways to apply behavioural insights to product builds that improve customer decisions and relationships:
Policy issuing journeys
When a customer applies for a new policy, the first experience sets the tone for the entire relationship.
A well-designed application flow is streamlined and intuitive, with data pre-filled where possible. Use plain-language explanations at key decision points to explain policy benefits and exclusions, as well as for policy schedules, welcome letters and other documents. Make customers aware upfront of the different steps within the journey to ensure expectations are aligned (FCA).
Consider surfacing facts that challenge overconfidence bias: the belief that “it won’t happen to me.” Including contextual risk statistics or brief examples during the quote or benefit-selection flow helps ground choices in reality, but beware of unintentionally exploiting emotion to lead to biased decisions. These are recognised dark patterns.
Renewals and ongoing communication
People are more likely to value insurance when the benefits feel vivid and recent - classic recency bias.
Consider whether renewal notices for annual policies can reinforce trust by reminding customers how their policy has served them over the past year: highlighting claims that were paid out, a roadside-assist call that saved the day, or even simple risk-avoidance (“another year without unexpected costs because you stayed covered”).
Regular, transparent updates and personalised reminders make renewals a moment of reinforcement that creates customer engagement rather than a chore, encouraging customers to continue their protection with confidence.
Policy changes and cancellations
When a customer decides to reduce cover or cancel a policy, clarity matters most. A well-designed process explains any rights a customer may have to reinstate their policy within a period of time after cancellation, so customers know they have the opportunity to change their mind if circumstances shift. It should also highlight the practical implications, such as waiting periods or reinstatement rules, in straightforward language.
By making these consequences transparent before a final decision, insurers give customers confidence that they’re acting with full information, while preserving the freedom to walk away.
Case study: Standard Bank’s smart friction
A striking example comes from Standard Bank in South Africa. During the pandemic, many customers, under financial stress, used the bank’s app to reverse valid debit orders, unintentionally cancelling their insurance policies.
The bank introduced a single, well-timed pop-up message explaining that reversing a legitimate debit order would cancel cover and trigger new waiting periods. This small dose of intentional friction slowed users just enough to prompt careful thinking.
The results were dramatic: monthly policy cancellations due to debit reversals dropped by 57% within months and by over 80% year-on-year, preserving more than R334 million in premiums (Naidoo & Gottlich, 2023).
Customers kept full freedom to reverse payments, but clearer information and a moment to pause helped them avoid costly mistakes.
The Standard Bank example shows how a single touchpoint, payments, can dramatically influence customer outcomes. But it’s only one moment in the broader insurance lifecycle.
From policy applications to claims, renewals, third-party administration, and ongoing communications, each interaction shapes how customers perceive value and make decisions. Consider how your other touchpoints across the entire customer journey are designed, and whether they help customers avoid bias and make confident choices.
AI and the Future of Choice Architecture
So far, we’ve focused on how human biases shape insurance decisions and how insurers can design to support better outcomes. But what happens as AI takes on more of the decision-making process?
Increasingly, customers turn to digital agents to do the choosing for them. For example, asking an AI agent to “Find me three quotes for car insurance.” In that scenario, it’s no longer just the end customer weighing options, but also an algorithm filtering, comparing, and recommending.
This raises new questions:
- How does our understanding of behavioural bias change when the “chooser” is an AI agent rather than a human?
- Do agents replicate human biases, or do they introduce new kinds of bias altogether?
- How should firms design products and journeys that are attractive and clear not just to people, but to the AI agents that will increasingly act on their behalf?
- Is the language and format of marketing and insurance product information optimised for AI search and decision-making?
- What does it mean to architect for choice in a world where choices are navigated by machines?
The answers to these questions are unclear. But as AI reshapes how decisions are made, these are questions firms will need to engage with when designing products and customer journeys.
Building trust by design
Choice architecture in insurance isn’t about nudging people to buy more cover.
It’s about creating clarity and earning respect: structuring decisions so customers understand risks and trade-offs and feel confident that their insurer is acting transparently.
The benefits of insurers designing experiences this way are incredibly clear:
- Customers make better-informed decisions and stay protected.
- Insurers benefit from stronger retention and fewer avoidable lapses.
- The industry moves closer to closing the global protection gap.
The science of choice shows that trust is the natural outcome of thoughtful design, which is the surest foundation for long-term customer relationships.
