How are BERT applications in finance and customer service?

[devinluke]

I've heard about BERT applications in finance and customer service. Are they mostly used for chatbots, fraud detection, or customer support automation? How effective are they in real-world use?

 

[Ynessira]

BERT is used in finance for fraud detection, sentiment analysis, document classification, and risk assessment. In customer service, it powers chatbots, intent detection, and automated responses by understanding context in customer messages, improving accuracy, personalization, response quality, and efficiency in handling large volumes of customer interactions.

 

[Oscar]

Finance BERT is applied to auto identify fraud and risk, sentiment analysis, and document review as well as customer service Chatbots, intent detection, ticket routing, and context-aware, automated responses.

 

[Oscar]

Some of the financial applications of BERT are fraud detection, sentiment analysis, and document processing, whereas in customer service, it facilitates chatbots, intent recognition, ticket classification, and precise and context-sensitive automated reactions.

 

[James Miller]

Customer queries, fraud detection, support chat automation, sentiment analysis, and personalized financial recommendations are analyzed with the help of BERT.

 

[Olowricha]

BERT is ideal in finance as it can gain insight into news sentiment and detect frauds in complicated documents with the help of such a model as FinBERT. It is used in customer service to power chatbots to accurately identify the intent and automate the process of classifying tickets, which makes responses much more accurate and satisfactory.