By Byron Fernandez
TDCX Group CIO and EVP

Imagine your policyholder stranded at an airport after a last-minute flight cancellation, with their checked baggage nowhere to be found. Stressed, they open their insurer’s app, expecting a quick, hassle-free process. A few taps, some basic details, and they should be on their way to replacing essentials. Instead, they hit a wall. Multiple document requests. Follow-up calls. A fraud review that adds days or even weeks to the process. For the policyholder, it’s frustrating. Why does filing a simple travel insurance claim feel like a bureaucratic hurdle? 

They’re not alone: In the UK, for instance, half of consumers faced at least one issue during the claims process, with one in four reporting unnecessary delays and 73% experiencing distress. Consumers have also become accustomed to digital-first, AI-powered experiences, with 71% already expecting them to be part of their buying journeys. Whether it’s instant refunds for flight cancellations, immediate banking alerts, or automated approvals, they now expect the same seamlessness from their insurer.

For the insurer, those extra steps are necessary safeguards. It’s been estimated that 20% of insurance claims are fraudulent. In the US, 74% of insurance leaders already reported an increase in fraudulent claims, with losses estimated at US$308.6 billion annually. Without strong checks, these losses could snowball. 

This is the paradox insurers must navigate daily. Tighten controls too much, and real customers get caught in the net. Loosen some of them, and fraudsters could exploit the system and eventually drive costs for everyone. How can insurers walk the tightrope between fraud prevention and customer experience (CX)?

The unique aspects of fraud detection and prevention in insurance

Fraud detection in most industries is event-driven. A stolen credit card triggers an instant alert, and a suspicious login attempt prompts two-factor authentication. These patterns are detected almost instantaneously, with systems blocking threats before they cause harm. In insurance, however, fraudsters don’t just exploit a single transaction. They could manipulate policies, claims, and even entire networks over time:

Low-frequency, high-stakes interactions: Unlike banks, where customers use their accounts frequently, most policyholders only interact with their insurer a handful of times — when purchasing a policy, making changes, or filing a claim. Each touchpoint matters. In fact, more than half of consumers would readily abandon their application for a financial or insurance product if they feel that the process feels frustrating or cumbersome.

Fraud across the policy lifecycle: A fraudulent insurance claim might take months or years to uncover. Some fraudsters inflate claims, while others manipulate policies from the start, using synthetic identities or staged claims across multiple insurers. Unlike banking or e-commerce, fraud in insurance is often calculated and difficult to detect until after payouts happen. For example, a recent survey of life insurance fraud in the US reported at least 10 types of fraudulent activities that carriers find hard and costly to detect, with 84% of insurers often needing specialized teams to audit after the transaction. In a market study in Spain, 40% of insurance fraud were premeditated, which cost more for insurers to mitigate.

The rise of deepfake fraud: Fraudsters are increasingly using AI-generated deepfakes to bypass verification systems, forge claim evidence, and create synthetic policyholders that don’t even exist. Traditional fraud detection tools, often designed for document-based reviews, cannot keep up with AI-generated deception. Insurers need advanced verification methods that detect fraud in ways static models can’t. In the Asia-Pacific (APAC) region, deepfake fraud surged by 194% year over year, with average losses of up to US$630,000 across the financial services and FinTech industries.

Regulatory complexities: Unlike other industries, where preventing fraud could focus on reducing chargebacks or stopping financial loss, insurers must also navigate strict regulations. Anti-money laundering (AML) laws and know-your-customer (KYC) protocols vary by region and policy type, adding another layer of complexity. In North America, 79% of financial institutions reported increased costs in technologies needed to meet evolving AML and KYC requirements. In Europe, insurers must comply not only with national regulations but also nearly 70 cross-border EU reporting mandates set to take effect.

Why insurance fraud detection and prevention requires a CX-centric approach

Fraud prevention in insurance must protect both insurers and policyholders without turning the claims process into an obstacle course. Traditional fraud detection models — which 77% of companies reportedly still rely on — are built on rigid rules and manual reviews, creating friction for legitimate customers while struggling to keep up with increasingly sophisticated tactics.

AI-powered risk assessment enables insurers to detect fraud patterns earlier and with greater accuracy by analyzing policyholder interactions over time. Instead of relying on static rules or manual checks, AI can identify anomalies that allow insurers to act proactively. In fact, 62% of decision-makers in APAC reported that their company is already using AI and machine learning (ML) in their fraud detection efforts.

With human expertise, fraud detection moves beyond data points to real-world understanding. The CX frontliners’ intuition and adaptability help them spot contextual, industry-specific red flags. At the same time, they can help maintain trust and transparency by communicating directly with customers, addressing their concerns, and ensuring that the process feels like a safeguard rather than a hindrance. In fact, nearly 50% of anti-fraud experts across 23 industries already use or plan to adopt AI and ML within the next two years to combat fraud.

This is where CX is a competitive advantage in fraud detection and prevention. Adaptive risk models, enabled by AI and behavioral analytics, apply controls based on real risk factors instead of forcing every claim through the same process. This builds trust while keeping fraud in check, ensuring a seamless experience for legitimate customers while flagging high-risk claims for deeper analysis. Meanwhile, CX support teams can ensure that fraud checks operate in the background, while omnichannel dispute resolution enables insurers to provide fast, efficient responses when concerns arise.

A global lodging company used this synergy to tackle payment fraud, coupon abuse, phishing, and unauthorized transactions in its online marketplace. With TDCX, they utilized robotic process automation (RPA) and a customized knowledge base, which improved operational efficiency and resolution rate. At the same time, a human-led “audit-the-auditor” approach ensured that quality assurance met the company’s certification standards. The results: 90% efficiency, 22.33% of productivity time saved, and 53 newly identified fraud trends that strengthened their detection efforts across the platform.

Fraud prevention should not be a hurdle. When embedded into the broader CX strategy, it becomes a trust enabler that protects businesses while keeping policyholders engaged and confident.