Email RFQ automation is a valuable tool for streamlining trading workflow. It allows traders to quickly and efficiently send and receive Request for Quotation (RFQ) emails to counterparties.
This white paper has explored the role of NLP in the automation of OTC RFQ answers, and has examined the various ways in which NLP can be used to improve customer experience and streamline OTC trading activities. AsAI capabilities continue to advance, it is likely that NLP–enabled technology will become an increasingly important tool for financial institutions looking to automate customer RFQs.
There is a rapid evolution in natural language processing (NLP) and artificial intelligence (AI). As they do, more and more industries are using NLP to boost their products and customer service.
When you send out a request for quotation (RFQ) to potential vendors for an automation project, you end up with a stack of widely different prices and proposals? Most likely, you won’t accept the highest bid, but if you choose the lowest bid, you could face rejections. When it comes to automation, what’s the secret to setting it up for success from the start?
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