Enable RFQ automation with Emmie
Who is Emmie?
Emmie is tasked with providing day-to-day assistance to you by helping manage your customers and users’ requests in real time 7X24.
She digitizes inbound requests and turn them into FIX or REST messages in order to automate their processes.
What Can I Do With Emmie?
Emmie will help you process requests from your customers and users so that you can automate their requests. #RFQ automation #Automated RFQ
Emmie helps your clients’ complete various transactions such as RFQs in a fast and secure way. From creating an RFQ from a message, processing a deal, to providing reports, your Team has now a virtual team mate to handle clients’ requests.
Emmie can provide full support to your team to speed up administrative and repetitive tasks, and facilitate complex and time-consuming operations such as managing internal documents, send a post trade.
What Are Emmie ‘s Advantages?
A Huge Time And Money Saver
Emmie is a huge time and money saver. She handles thousand of requests in parallel and prevent human error, which significantly reduces costs.
This allows your team to shift their focus on operations that have greater added value and can increase margins on banking products.
Emmie is trained to answer in realtime. Users who are assisted by Emmie are able to find the information they need faster. She can automatically present new offers that may interest the customer (RFQ automation).
Using Emmie makes moving between transactions seamless, which can increase customer engagement and the number of bank accounts opened.
Emmie is scalable and holds multiple conversations simultaneously. Not to mention that chatbots work 24 hours a day, 7 days a week.
This is a huge benefit because customers and users can get help whenever they need it, which significantly improves the overall experience.
Structuring RFQs intelligently using text mining, natural language processing, and machine learning
RFQs are usually unstructured messages sent via email, phone, or messaging systems to brokers.
For intelligent RFQ automation, this research integrates text mining, natural language processing (NLP), and machine learning methods.
To train and test the word-embedding model, over 2 million trading RFQ requests were processed. We use N-gram TF-IDF to extract domain keywords from RFQs. We also use text analytics to extract essential specifications such as contract, direction, and size. Each sentence is grouped by the algorithm. In order to generate a standard RFQ, Emmie AI engine identifies relevant criteria in the text. The standardization system makes it easier for trading desks to price clients faster by routing their messages to the pricing engine.
The system improves the complex trade execution and booking process in a highly competitive market.
Why Emmie Is Named Emmie?
From Wikipedia, the free encyclopedia
Amalie Emmy Noether was a German mathematician who made many important contributions to abstract algebra. She discovered Noether’s theorem, which is fundamental in mathematical physics. She invariably used the name “Emmy Noether” in her life and publications. She was described by Pavel Alexandrov, Albert Einstein, Jean Dieudonné, Hermann Weyl and Norbert Wiener as the most important woman in the history of mathematics.