Speech Recognition and AI are cementing their place in anti-fraud intelligence for the insurance industry, providing new opportunities for comprehensive, rapid, and effective detection of fraudulent action and intent. According to a 2021 survey, AI has already been deployed by 31% of insurance CIOs, with 23% reporting the intent to also deploy this technology in the next year. Across the next two years, 21% of respondents from a survey undertaken by the Coalition Against Insurance Fraud have also reported the intent to invest in anti-fraud focused AI systems. Although the adoption rate of AI systems has been high, many companies fail to effectively utilise their unstructured data – information that can be significant to the validation of customer claims. Effective use of these new AI and Speech Recognition systems can help to tackle this problem through the integration of processes such as machine learning, automating certain processes in the verification process while creating and evolving algorithms to better detect fraudulent intent.

What are the core AI systems and processes in anti-fraud technology?

The term AI refers to an extensive range of technologies. However, the most relevant processes to anti-fraud intelligence are Conversational AI, Natural Language Processing (NLP), and Automatic Speech Recognition (ASR). Conversational AI provides automated messaging and voice-enabled applications, which facilitates conversation between people and computers.

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