Fraud has been a problem faced by financial services since its conception. However, old problems cannot be combated by outdated solutions – innovative approaches are required to beat financial services fraud both in the present and future. New ideas driven by software such as LexiQal integrate voice recognition technology with Artificial Intelligence and machine learning. This is providing an updated, continuously evolving anti-fraud strategy to protect financial services from fraud from the earliest possible moment.

What are the roles of voice recognition and machine learning in fraud prevention?

Video and audio data have long been viewed as challenging in both data collection and analysis. The use of human-powered processes alone is incredibly time-consuming, and often erroneous, presenting a less-than-ideal approach to combating problems such as fraud.

What is voice recognition AI?

Voice recognition AI technology covers several different processes, including Conversational AI, Natural Language Processing (NLP), and Automatic Speech Recognition (ASR). Utilised both individually and collaboratively, these processes can facilitate the implementation of the most up-to-date fraud prevention. Combined with machine learning, voice recognition AI can be utilised to effectively combat fraud as early as the first call.

What is machine learning?

Machine learning describes the process of automating the evolution of technologies, enabling them to combat issues such as fraud far more effectively. Instead of progress being fuelled by human efforts, machine learning can take over the process and develop systems rapidly, keeping pace with the quickly evolving nature of organised fraud. This ensures that finance companies are not left as vulnerable to fraud attacks.

What can AI technology recognise?

Full article: Why Our Voice Holds the Key to Beating Financial Services Fraud — FINTECHNA

 

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