See the original article on Finance Magnates.
Cloud9 develops solution with Quantiphi and Google Voice that will help to transcribe traders’ voices within milliseconds.
Cloud9 Technologies, a cloud communications service provider that delivers voice and collaboration services for institutional traders, has announced the development of a voice trading transcription solution which deciphers trader talk.
For a long time, traders’ voices had been difficult to decipher due to their use of slang, their intermittent nature, and their use of difficult trading jargon. This is similar to the problem that is faced in highly specialised work environments like air traffic control, hospitals, etc.
But by using Google Open Source technology in collaboration with Quantiphi, the report says that Cloud9 technologies has been able to convert the complex trader voice into text. The company recently secured $30 million in funding and this development should please its investors.
German Soto Sanchez, Global Head of Corporate Development at Cloud9, said: “Today, PMs, traders, and analysts utilize only 5% to 10% of voice data for analysis – with Cloud9’s Voice Transcription Solution, they can now use 100%”.
The report goes on to add that a live demonstration was held among hundreds of representatives from major financial services firms and it was largely successful in converting all traders’ voices, complete with jargon, into text in a matter of milliseconds.
Conversion of the voices into text within milliseconds is a challenge which many existing transcribing solutions have failed to crack. This development from Cloud9 will help a great deal in moving to an advanced stage as far as compliance, surveillance and trader voice analytics goes.
Cloud9 believes that by pushing through with the adaptation of this breakthrough development, if and when that happens, the industry will be able to advance further in its quest for better compliance and trading standards which will only enhance the trading ecosystem as a whole.
See the original article on Finance Magnates.
See the full article on Institutional Investor.
Cloud9 Technologies partnered with Google and Quantiphi to build a machine learning-powered voice transcription service for traders.
For forty years, traders have called each other up to price potential transactions. Now, a fintech firm wants to turn those calls into market data.
Through a partnership with Google and data science firm, Quantiphi, New York-based Cloud9 Technologies has developed a transcription service that can translate verbal communications between traders into text data using machine learning. This data, the firm believes, can revolutionize compliance as well as offer new insights into trading activity.
“It’s going to be transformative for the industry,” said German Soto Sanchez, Cloud9’s Global Head of Corporate Development.
See the rest of the article from Institutional Investor.
German Soto-Sanchez, Global Head of Corporate Development at Cloud9, recently sat down with Benzinga to share an average day in his life, including some of his top productivity tips.
Read the Original Article on Benzinga
What’s a day in your life like as the Global Head of Corporate Development for Cloud9 Technologies?
5:15 a.m. — Wake up and read my daily affirmation from a book called “Jesus Calling.” Check email (only respond to urgent items) and check daily schedule. Then I head to the gym for some cardio. My gym is eight blocks away, so it takes some motivation to get there (especially when it is 10 degrees outside), but I always enjoy listening to my Birthday Playlist, which is made up of my favorite songs going as far back as my elementary school days!
7 — Arrive back at home in time to see my son off to school and my daughter, who we homeschool. I also have breakfast, which is the same each day — a shake and health bar.
8–8:15 — Leave for work. I live in Harlem, and I am a proud native New Yorker, so I take the subway every day. I normally use my commute to read the news. First I look at the New York Times and Wall Street Journal for general news, then I move on to Bloomberg, Benzinga and CB Insights for financial and fintech news.
8:45–9 — The subway is always a little unpredictable, but I try to get to the office before 9 a.m.
9–9:15 — I plan my entire week on Sunday night, and then I reassess each night of the week, so I have a good idea of what my day and my week will look like when I arrive in the morning. I take the first 15 minutes to half hour of the morning to get my bearings and finalize my To Do List. Every day around this time I also fire up our flagship communications platform, the C9 Trader. I usually use it for calls with our partners.
9:15–12:30 p.m. — I reserve the first half of the day for meetings. I am usually meeting with various fintech companies or participating in one of several recurring touchpoint meetings for one of my teams. One example is the meeting for our transcription project. I love using the C9 Trader to conduct meetings—it’s transformed the way I communicate with our clients and partners. The call quality in our meetings with project team members (some of whom are in India) used to be terrible, so we set them up on the C9 Trader in a lab environment, which greatly improved the call quality and our level of interaction. Nowadays, a lot of our partners and vendors ask us for Cloud9 subscriptions in order to interact with us. The experience is that much better.
12:30–1 — My days tend to be very busy, so I always work through lunch.
1–2 — I’ll start the early afternoon by wrapping up any meetings I may have not gotten to in the morning.
2–7 — I like to reserve most of the afternoon for work — I may schedule or attend a meeting here and there (usually a “meet for tea” since I don’t drink coffee), but I like having this time to focus on work. Before the end of the day, I always completely clean out my inbox and make sure all those To Do List items are accomplished.
7–8:15 — I leave the office around 7 p.m. every day except for Fridays, when I leave a little after 6 p.m. to pick up my daughter from her ballet class. On a typical weekday, my son is off at tennis and my wife is taking my daughter to ballet, so I’m the only one home if I arrive before 8:30 p.m. My family likes my cooking, so I make dinner when I can.
8:15–9 — The kids and my wife start arriving home and we all sit around the table and eat. We tend to eat healthy meals — no-fats food and we don’t eat out a lot — but I always make a big, unhealthy brunch on weekends. Kids are in bed by 9 p.m.
11 — I check a few emails before bed and confirm or revise my schedule for the next day, but I prefer not to work from home at night. After spending some time with the family, I tend to go to sleep by 11 p.m. every night.
Read the Original Article in Benzinga