How our voices are key to fighting financial services fraud – AI Business

An opinion piece by the CTO of Intelligent Voice, a transcription and analytics services firm

Fraud brings significant challenges to the financial services industry. Anti-fraud strategies must be comprehensive and effective without disrupting the customer experience, able to detect fraudulent activity before it causes any damage. New and innovative measures must be adopted to stay ahead of the rapidly changing nature of organized criminal fraud.

Technologies such as LexiQal are integrating voice recognition technology with AI, creating a continuously evolving anti-fraud strategy that can detect fraud at the earliest possible moment. Now is the time to invest in these new technological approaches to protect financial services in the years to come.

Historically, audio and video data have been challenging to collect and analyze. Human error and time-consuming processes have led to often erroneous fraud detection, with many fraudulent claims slipping through the cracks. Voice recognition AI and machine learning are revolutionizing these problems, closing the cracks and translating audio data into a practical, understandable format.

Voice recognition AI − covering processes such as Conversational AI, Natural Language Processing (NLP), and Automatic Speech Recognition (ASR) − can be utilized collaboratively to facilitate updated and comprehensive fraud prevention.

With the ability to analyze behavioral indicators, language features, and speech characteristics, it can assist greatly in detecting fraudulent intent in the background of customer phone calls without the involvement of customer service agents.

Using ML to spot traits that signal fraud

The term machine learning (ML) describes the process of automation for the purpose of evolution – where technology can learn from its collected data and adapt accordingly. For example, if a certain speech characteristic (such as hesitancy and hedging) is suddenly more present in fraudulent calls, machine learning will identify this rise, record the necessary data and adapt its detection systems to better recognize the feature.

Developments in the capabilities of voice recognition and AI have resulted in the ability to identify and recognize several behavioral, speech, and language features. Technologies such as LexiQal are developed using these voice recognition AI processes in collaboration with law enforcement behavioral experts, ensuring that the correct indicators are being identified for fraudulent intent.

Full article: How our voices are key to fighting financial services fraud – AI Business