The collaboration will integrate NFU Mutual into the UK's largest syndicated risk intelligence network, enabling the insurer to offer real-time, accurate quotes and fast-track customer applications while effectively identifying and preventing fraud.
The partnership leverages National SIRA, Synectics' advanced suite of fraud solutions, which includes AI, machine learning, and sophisticated risk analysis tools. These tools are used by insurers across the UK, from quote to claim, to improve fraud detection and ensure accurate decision-making. As the UK's largest database of cross-sector risk intelligence, SIRA is continually updated by hundreds of insurers and financial services providers, ensuring its accuracy and effectiveness in combating fraud.
The initial phase of the partnership will focus on improving fraud measures for NFU Mutual's home and motor insurance lines. NFU Mutual will also gain access to Synectics' expert team of analysts and investigators. The collaboration aims to provide cutting-edge technology that safeguards against fraud while maintaining a high level of customer service, reinforcing NFU Mutual's commitment to protecting its member policyholders from financial crime.
Fraud continues to be a major financial burden for the UK insurance industry, with an estimated cost of over GBP 1.2 billion annually, according to UK Finance. This substantial figure includes both fraudulent claims and the operational costs associated with detecting and preventing fraud. Insurance fraud affects insurers directly by draining resources and increasing the complexity of claims processing. However, the impact extends beyond insurers, as the costs are often passed on to genuine customers in the form of higher premiums. As a result, the financial strain from fraudulent activities creates a ripple effect throughout the entire insurance market, influencing both the profitability of insurers and the affordability of policies for consumers.
To combat this persistent issue, insurers are increasingly adopting advanced technologies, including AI and machine learning, which offer greater precision and efficiency in detecting fraudulent activities. AI-driven fraud detection systems can analyse vast amounts of data in real time, identifying patterns and anomalies that may indicate fraudulent behaviour. Machine learning models continuously improve their accuracy by learning from historical data, allowing insurers to detect new and evolving fraud tactics.
Every day we send out a free e-mail with the most important headlines of the last 24 hours.
Subscribe now