Automation through speech analytics and AI provides the most adaptable and comprehensive anti-fraud cover for insurance companies, allowing them to protect business and customers with minimal impact on customer interactions.
Fraudulent activity in the insurance sector is constantly evolving, proving challenging for companies to keep pace with and prevent. Speech recognition and AI technology are providing the foundations necessary to adapt to changes in fraudulent behavior, maintaining a far higher level of protection for companies and their customers. Tackling the analysis of audio and video data, speech analysis technology is pushing the boundaries of fraud prevention to create effective and systematic strategies.
What roles do speech recognition and machine learning play in anti-fraud strategy?
Speech analysis technology factors into fraud prevention in a variety of ways. NLP (natural language processing) is particularly effective, allowing for the understanding of the human language by computer systems. Combined with AI and machine learning, it creates an adaptable and efficient fraud detection process.
Machine learning refers to computers utilizing data and previous records to improve, alter, and correct their algorithms without human intervention. This allows algorithms to evolve alongside the changing nature of the fraudulent activity, keeping pace with the ever-shifting behavior of fraudsters. When combined with speech analysis technology such as NLP, machine learning programs can learn to track the speech, language, and behavioral indicators that suggest fraudulent intent.
In advanced anti-fraud technologies, these systems can be backed by detailed behavioral analytics which are able to detect fraud from the first phone call, driving end-to-end fraud management.
What features can speech analysis AI recognize?
Full article: Voice: The Key to Combating Insurance Fraud | Insurance Innovation Reporter (iireporter.com)