Manjit Rana: Moving at the Speed of Trust

Insurance has become extraordinarily good at finding the few. The next competitive advantage may come from clearing the many.

In this episode of Scouting for Growth, I sit down with Manjit Rana, Executive Vice President for Insurance across the UK, EMEA and APAC at Clearspeed, to explore a deceptively simple question: can insurers establish trust at the same speed at which they are automating decisions?

More than 90 out of every 100 customers coming to an insurer are genuine. Yet much of the industry's fraud infrastructure has historically been designed around identifying the minority that may represent risk. Manjit's argument is not that those systems were wrong. They were built for a different information environment. Today, AI is accelerating both the automation of insurance decisions and the ability to manufacture convincing evidence, making the trust problem more urgent.

We explore the emerging concept of a Trust Intelligence Layer: a continuous, voice-derived, regulatory-ready risk signal designed to help genuine interactions move forward quickly while directing scarce human judgement toward the cases requiring closer attention. Manjit's airport metal detector analogy captures the distinction well. The signal does not make the final decision. It identifies where something unexpected deserves a closer look, allowing everyone else to keep moving.

The implications extend well beyond claims. Historical data and behavioural profiles can indicate risk, but they cannot necessarily reveal what an individual knows about an application, renewal or claim happening right now. As insurers automate more of those interactions, the challenge is to preserve trust without simply adding more friction, more profiling or more manual intervention.

Most importantly, the conversation moves from technology to operating model. If you could clear more genuine customers, identify more risk and make decisions faster, what would that change about your people, processes, workflows and economics? Manjit argues that this is where leaders should start. Because the question is no longer whether insurance will automate. It is whether insurers can tell which of those automated decisions deserve their trust.

KEY TAKEAWAYS

I want to challenge the way we have traditionally framed fraud and trust in insurance. For decades, we have become increasingly sophisticated at identifying the interactions that may represent risk. But if the overwhelming majority of customers are genuine, there is ano