*This article is a guest post contributed by LodeStar Ecosystems.
“The Jungle is Dark but Full of Diamonds” – Arthur Miller, Death of a Salesman
The working day of a trader might seem extremely stressful and sometimes it really is. In their dynamic environment speed is crucial and a moment of delay could cost them a deal. However, modern technology allows for a dramatic decrease in the time they spend on looking for data and making decisions by integrating trade-critical systems into a unified workflow. Below is an example of how, by having all systems sharing data, a trader can have all the necessary information to close a deal at the opening of the market.
Scenario 1: No Sharing of Data
It’s 07.00 am and the markets have opened. On cue, the electronic chats tumble onto the screen like the emptying of a Christmas mail sack. The terminal is alive with green and red. “Buys”, “Holds” and “Sells” are called across the floor from research, and the latest news about yet another government outsource services company in trouble hits the desks. Your clients need your advice. PDQ.
It’s 07.20, you’re trying to copy and paste pieces of information into trading ideas for your clients that are relevant and sent in time to make a difference.
With every minute that passes, your ideas’ value is depleting as the markets react and start to price in all the data.
Your applications are in tabs across the top of your screen. You back and forth between systems that don’t talk to each other, and don’t want to.
It’s 07.40 and you are nearly there. You have pulled together credible recommendations for your top five clients. You start hitting the send button and throw in some follow up calls.
It’s 08.00 am and you start sending ideas out to your tier 2 clients, but it’s too late to make a difference. Most of your tier 2 clients are someone else’s tier 1, and they have been looked after by your competitors. And it will be the same tomorrow, and the day after that, except for one thing that is cast iron guaranteed. The only thing that changes is that it gets harder. Harder, in that the information seems to inexorably grow in volume, velocity and variety. Electronic trading systems, CRM systems, online news, blogs and articles, with Twitter shouting at the back of the room with its hand up trying to be heard.
It’s impossible to assimilate all of this data, produce trading recommendations and give tier 1 service to all your clients. No single human can do it. Many humans can, but the costs are equally impossible to sustain.
Scenario 2: Sharing and Analysis of Data Across Systems with Glue42 and LodeBot
It’s 07.00 am and the markets have opened. A computer has read every chat from IB or Symphony. It has read every financial news article, it has read every useful blog and social media stream. It has looked at price. It has looked at watchlists, client holdings and trading histories. It has read about every asset, sector or portfolio you and your clients are remotely interested in. It has assimilated all of this data at machine speed and produced trading suggestions that are relevant to individual clients (all clients, not just tier 1). All of your applications, tools and resources are held elegantly within a unifying technology that is configured to you.
It’s 07.05. You are validating the suggestions and adding your thoughts and expertise. Adding your real value. It’s 07.15 and you start hitting the send button. All of your clients are receiving great help at turbo charged pace.
LodeBot as a part of the Glue42 unifying technology does precisely that by greatly simplifying the trader workflow. The next generation intelligent chatbot LodeBot pulls and analyses all your and clients’ information, like orders, research and news and then proactively generates stories and suggestions about those assets for specific clients, ensuring that they only receive relevant and actionable information. At the same time, the Glue42 integration platform makes sure that the data between all applications flows seamlessly and helps build consolidate application screens into workspaces where unnecessary navigation and copy/paste is eliminated.
See the two systems in action:
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“Meanwhile, cognitive agents, smart work flows, and natural language processing are most useful in client services, for example, for creating customized email responses.
McKinsey recently compared the penetration of digital execution and trade processing of eight banks in the cash equities business, and found that those with the highest levels of digital execution saw front-office revenues per producer increase by as much as eight times, while those with the highest level of post-trade digitization posted four times more trades per middle- and back-office FTE than the bank with the weakest digital resources.”