How can the industry use AI and automated systems and yet stay compliant with local market regulators? This is the them in February and IE wants to delve deeper into the balance between rapid insurtech progress and maintaining compliance.
This article is by Hanre Cillie, RVP of Insurance Growth and Compliance at nCino.
The FCA’s recent simplification of insurance rules signals a clear intent to support innovation while maintaining robust customer protection. This is welcome news for underwriters and brokers operating in soft market conditions marked by heightened competition and margin pressure.
Simplification, however, does not mean relaxation. The challenge is how to deploy AI in a way that demonstrably strengthens compliance while delivering tangible gains in efficiency, decision making, and customer experience.
Hanré Cillié, Regional Vice President of Insurance Growth and Compliance at nCino, explores why compliance and technology are not opposing forces and how, when applied thoughtfully, AI can underpin a new era of improved customer outcomes.
With the right data, Consumer Duty becomes an opportunity
The FCA’s been clear that 2026 represents a shift. Moving the focus away from whether Consumer Duty processes exist, towards their effectiveness and evidencing that customers are consistently receiving good outcomes.
This requires robust, auditable data trails demonstrating how decisions affect customers throughout the policy lifecycle. When embedded correctly, the ability to capture, analyse, and act on this intelligence does more than satisfy regulatory scrutiny. It creates a competitive advantage.
Firms that integrate regulatory requirements directly into workflows, enabling unified views of customer interactions, product performance, and outcome monitoring, are already transforming compliance from cost centre to source of competitive advantage.
Reducing compliance risk by removing human inconsistency
Manual processes inevitably introduce variation. Underwriters may interpret risk differently, and compliance teams may apply judgment inconsistently. AI, by contrast, consistently applies the same standards, thereby reducing regulatory risk and supporting fair treatment.
When algorithms assess fair value, identical criteria are applied across products. When AI screens submissions for completeness and accuracy, it identifies the same issues regardless of timing, volume, or complexity.
Crucially, AI can also continuously analyse customer data to detect emerging patterns that may signal poor outcomes, flagging issues before they escalate into regulatory concern. Used in this way, AI becomes a proactive compliance tool rather than a reactive control.
Maintaining focus on what matters most
Administrative burden continues to consume a disproportionate amount of time for underwriters, brokers and compliance teams, time that could otherwise be spent on higher-value client engagement and strategic decision making.
AI excels at handling repetitive, time-intensive tasks, aggregating intelligence in seconds, extracting key data points instantly, and performing risk assessments with speed and accuracy.
When submissions are digitally triaged, underwriters can focus their expertise on nuanced judgment calls that require human insight. Brokers, freed from hours of administration, can concentrate on client needs, strategic advice, and building trusted relationships that drive retention, growth, and better outcomes.
Role-based agents, not generic chatbots
Generic chatbots and off-the-shelf automation tools are ill-suited to the complexity of insurance. They lack the contextual understanding of risk, customer empathy, and regulatory obligations the industry demands.
By contrast, agentic AI purpose-built for insurance workflows and trained on insurance-specific data delivers real value.
For underwriters, this means AI assistants that recognise complex risk factors, interpret financial and contextual data, and support more informed decisions. For brokers, it means technology that understands client objectives, identifies relevant needs-based cross-sell opportunities, and prepares submissions that meet carrier requirements, improving rates, terms and speed.
This is not about replacing expertise. It is about amplifying it.
Keeping humans firmly in the loop
Insurance will always require human judgment. The most effective AI strategies recognise this and adopt an augmentation model, using AI to do the heavy lifting while ensuring humans remain firmly in control.
AI can analyse data, model risk, and surface insights, but it’s the experienced underwriter who decides whether to accept a risk, negotiate terms and set pricing. Human oversight also addresses a fundamental limitation of AI, namely the absence of moral reasoning.
Concepts such as fairness, proportionality, and empathy cannot be automated. Human judgment remains essential to ensuring that technology supports, rather than undermines, good outcomes.
Underwriting transformation in a soft market
Nowhere is AI’s potential more evident than in underwriting. Insurers face converging pressures, including maintaining discipline in soft market conditions, responding faster to brokers, and managing rising submission volumes.
Automated triage can instantly assess submissions for completeness, identify omissions, and route risks appropriately based on complexity and expertise. Straightforward risks are processed efficiently while complex cases receive the attention they require.
When underwriters can return comprehensive terms in hours rather than days, they gain a clear competitive edge, particularly in a market where service differentiation determines success.
Welcoming a new era of customer outcomes
Whether it’s harnessing intelligence to enhance client lifecycle experiences, maintaining underwriting discipline, or embedding compliance by design, success depends on embracing AI transformation responsibly. Firms that lead with intention, combining technology, governance, and human expertise, will thrive in an increasingly competitive and scrutinised market.
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