How insurers can increase effectiveness and drive efficiency in countering fraud

With a focus on controlling fraud and operational expenses, fraud teams are often being asked to do ‘more with less’. What approaches are you seeing that are proving to be successful in increasing effectiveness and driving efficiency in countering fraud?

As the leading provider of fraud solutions to the insurance industry, Synectics is committed to achieving 'more with less' for its customers. We've witnessed a substantial transformation in insurers' strategies, resulting in heightened effectiveness and efficiency in countering fraud.

The following are some of the strategies and techniques we’ve incorporated to deliver on this commitment:

1. Data Sharing for Comprehensive Insights:

In the ongoing battle against fraud, effective data sharing stands as a cornerstone, even in the face of persistent data quality challenges. The industry's reliance on syndicated data emphasises the importance of widespread membership, fostering collaboration to offer insurers comprehensive insights. Recommending insurers to review and maximise the data items shared is essential to enabling the identification of patterns and fraud networks, thereby bolstering fraud detection and streamlining operational processes with efficiency.

2. Real-Time Data Processing for Proactive Prevention:

Meeting customer expectations in the digital age requires real-time data processing. The shift from traditional batch processing to dynamic, real-time data analysis marks a significant leap in fraud prevention. A seamless strategy from the Point of Quote to Claim Settlement demonstrated in a recent proof of concept, captured an impressive 68% of potential fraud instances at the quote stage. Incorporating fraud prevention and detection as early as possible in the customer journey boosts operational efficiency and empowers insurers to proactively address fraudulent activities from the outset, reallocating resources effectively.

3. AI-Driven Revolution with Machine Learning and Predictive Analytics:

Integrating machine learning, predictive analytics, and artificial intelligence (AI) has revolutionised fraud detection. The introduction of predictive analytics for some insurers has seen a 31% increase in fraud detection compared to syndicated data alone. Simultaneously, there's been a significant 43% reduction in fraud referrals, highlighting the transformative impact of technology in streamlining fraud management processes. This enables fraud teams to focus more intently on high-risk cases, significantly increasing investigator productivity, fraud savings, and enabling the swift processing of genuine claims for good customers.

4. Document Verification for Security Amidst Deep Fakes:

Traditional identification of false documents relied on a trained eye and access to the original document. With the persistent threats posed by generative AI and deep fakes, the landscape of insurance fraud through falsified or altered documentation is rapidly evolving. In response to these challenges, Synectics has developed an advanced document verification solution. These include facial recognition, text extraction, manipulated evidence detection, similarity scoring, and reverse image searching, automating the authentication process. This not only enhances operational efficiency but also ensures a thorough evaluation of potential fraud, significantly reducing reliance on resource-intensive manual investigations. Crucially, this capability expedites the settlement of genuine claims amidst the ever-evolving landscape of deceptive practices.

Richard Daley, Business Development Manager at Synectics, said: “

By harnessing the power of collaboration, advanced analytics, and automation, we are transforming fraud prevention across both policy and claims. These strategies empower insurers to proactively tackle fraud, improve operational efficiency, and ensure resources are optimised for both prevention and resolution.

Learn how you can do more with less, with innovative fraud prevention solutions, click here.