Combating Insurance Fraud with Digital

Why Insurance Fraud Remains a Growing Threat?

Insurance fraud continues to be one of the industry’s most persistent and expensive challenges. According to leading studies:

• 3–4% of all claims — about one in 30 — are fraudulent.
• Fraudulent additions to claims cost insurers $5.6–$7.7 billion annually in auto insurance alone.

Fraudsters keep evolving their tactics, exploiting weak points in the claims process. Meanwhile, traditional detection methods are struggling to keep up, leaving insurers with higher loss ratios, increased operating costs, and pressure on profitability.

This whitepaper explains why conventional approaches fail and how digital innovation — from business rules management systems (BRMS) to predictive analytics — can help insurers proactively detect, prevent, and manage fraud.

Understanding Insurance Fraud — Soft vs. Hard Fraud

Fraud is not always obvious. Insurers need to understand its two main types:

• Soft Fraud: Inflating legitimate claims. For example, after an accident, a claimant may deliberately add unrelated car damage or submit fake medical bills to increase payouts.
• Hard Fraud: Fabricating loss events entirely. Examples include staging accidents or submitting claims for damage that never occurred.

Both types drain profitability but require different detection strategies.

Why Traditional Rule-Based Systems Fall Short?

Many insurers use hard-coded rules in claims management systems, a set of pre-defined conditions that trigger fraud alerts for adjusters. For instance, a rule might flag if a claim is filed just before a policy expires or if a vehicle chassis number matches one previously marked as total loss.

While helpful, this approach has serious limitations:

• Static and error-prone: Rules may miss critical fraud indicators and become outdated.
• Labor-intensive: Too many false positives overwhelm adjusters and slow processing.
• Complex maintenance: Updating rules requires developer time and can break existing logic.
• Low agility: Changing fraud patterns demand constant re-coding, which is slow and expensive.

As fraudsters evolve faster than systems, insurers need a smarter, more adaptable defense.

Modernizing Fraud Detection: Two Digital Approaches

Forward-looking insurers are moving from static rule engines to dynamic, intelligent fraud detection built on configurable platforms and data-driven insights.

1. Business Rules Management System (BRMS)

A BRMS allows business users (not just IT) to create and update fraud rules quickly with intuitive decision tables and logic — no coding required.

• Flexibility: Add, test, and deploy fraud rules rapidly as new patterns emerge.
• Integration: Connect seamlessly with claims systems to trigger checks at the point of claim intimation or registration.
• Real-time alerts: Immediate suspicion triggers for anomalies such as:
  • Loss within 3 months of new policy issuance
  • Claims just before policy expiry
  • Inconsistent contact details across multiple claims
  • Vehicles previously declared total loss being reinsured

With BRMS, insurers can stay ahead of fraud trends without lengthy IT cycles.

2. Predictive Analytics & AI Models

Predictive analytics builds on historical fraud data and advanced modeling to flag suspicious claims automatically and even predict fraud likelihood.

The process includes:

• Data gathering: Collect historical claim and fraud records across lines of business.
• Trend analysis: Use regression, correlation, and advanced data mining to detect anomalies.
• Model building: Train algorithms to classify claims as normal, suspicious, or fraudulent.
• Outcome reporting: Provide clear reasons and confidence scores to adjusters for review.

This approach grows stronger over time — the more data the model processes, the more accurate and self-learning it becomes.

Example: In motor claims, analytics can spot patterns such as frequent accidents from the same location, unusual surge in claims during a particular period, or repetitive use of the same garages and surveyors.

Why Modernization Is Critical?

Insurers using digital fraud detection see measurable business impact:

• Fewer false positives — saving adjusters’ time and increasing operational efficiency.
• Faster, fairer claims settlement — improving customer experience while reducing leakage.
• Proactive fraud prevention — identifying suspicious activity before payouts.
• Better compliance — with auditable, explainable decisions that regulators can trust.

By integrating predictive analytics with configurable BRMS, insurers can move from reactive fraud detection to proactive fraud prevention.

How Newgen Helps Combat Insurance Fraud?

Newgen’s Claims Management Software, part of the NewgenONE Digital Transformation Platform, enables insurers to modernize fraud detection and streamline claims management end to end.

Key capabilities include:

• Unified claims processing: Multi-channel claim registration with centralized data.
• Dynamic fraud detection: Integrated BRMS for easy rule creation and updates.
• Predictive analytics: AI-driven insights to identify outliers and fraud probabilities.
• End-to-end automation: Faster processing with reduced manual intervention.
• Audit-ready compliance: Complete traceability and reporting for regulators.

Insurers using Newgen report significant improvement in fraud detection accuracy, claims cycle time, and operational efficiency.

Action Plan for CxOs

To modernize fraud detection and claims management:

1. Assess current detection methods: Identify gaps in your rules and analytics.
2. Adopt configurable tools: Move away from hard coding to a flexible BRMS.
3. Leverage historical and external data: Build predictive models and continuously refine them.
4. Integrate end-to-end workflows: Connect claims, underwriting, and fraud teams on one platform.
5. Invest in explainable AI: Ensure transparency for customers and regulators.

Why Acting Now Matters?

Fraudsters are becoming more sophisticated, using digital channels and social engineering to bypass traditional controls. At the same time, customers demand fast, frictionless claims — and punishing honest customers with overly strict checks can backfire.

By implementing agile, AI-driven fraud detection today, insurers can cut losses, speed up payouts, and protect both profitability and customer trust.

Start Your Fraud-Fighting Transformation

If your claims processes still rely on static rules and manual reviews, it’s time to step up your defenses with intelligent, adaptive fraud detection.