Lodebot: a new way to understand and connect data

Lodebot is an AI chatbot for the financial services industry. Founded by experts in financial services science and technology, Lodebot uses an entirely new way of understanding and connecting data.

Using up to the minute AI technology Lodebot changes relationships and improves profitability in capital markets. Lodebot identifies, and resolves, those common operational inefficiencies that lead to low productivity.

Here’s how:

The sell-side, as a result of MIFID and other external factors, is currently experiencing unprecedented and ever-increasing pressures. Margins are being squeezed like never before. Senior managers are going to have to look much more closely at how their trading businesses are operating and find ways to improve productivity. They need to do more with less, to somehow get more out of their existing assets.

The situation is pretty much the same on the buy-side. Asset managers are under increasing competition from ETFs and other factors. They can no longer afford to charge such high management fees or performance fees.

So firms on both the buy-side and the sell-side need to achieve much higher levels of efficiency across their processes and in order to achieve that they’re going to need trading specific leading- edge technology.

Lodebot

Lodebot’s developers share decades of experience on both buy and sell side. They’ve seen how those businesses run, how they operate, and they’ve seen the inefficiencies.

Lodestar Chief Scientific Officer, Dr Anthony Edwards, explains:

‘Look across your trading floor on a quiet day; nothing much is getting done, traders are chatting amongst themselves, there’s nothing happening. You think, ‘This is costing me an absolute fortune!’  What you need is technology that can make suggestions to those people; ‘whom should I call?’ ‘What should I do to try and drum up some business?’’

‘Many businesses have accumulated discrete silos of data. As they’ve grown, evolved, merged with other businesses, etc., they’ve ended up with a CRM system over here, a trading system over there and historical trade data somewhere else. There’s no easy way for the person on the desk to monitor what’s going on and, because they can’t see the whole data picture across the enterprise, it becomes very difficult for them to identify whom they should call and why.

‘If you’re the fund manager, you want something that’s monitoring your positions, your portfolio, looking at all the available data and alerting you to potential areas of threat or opportunity. A stock might have come down 5% and it might now be very oversold and there might be some statistical indications that it’s likely to rally. This kind of information is continually changing and is very difficult for the fund manager to even calculate never mind be aware of.

‘First and foremost, Lodebot is a data gatherer. It pulls data from all those disparate systems into one single database. On top of this data layer sits Lodebot’s intelligence layer – it looks across all that data and makes sense of all the various combinations of rules and so forth that are in there, identifying and making sense of all those factors that you would identify and make sense of if you were sat there at the desk and you could see all the data.

‘Let me give you an example: Let’s say a buy order comes into your trading system for a relatively illiquid stock. There may well be other information within the enterprise with regard to that particular trading opportunity and there may well be somebody in your business that has also identified this or a similar trade opportunity. There may be a piece of information within the organisation that your trader doesn’t even know exists but to which Lodebot can alert the trader. The Lodebot might say: ‘Hey, you’ve got a buyer here, you’ve got a potential buyer there, a potential seller here. Let’s try and alert the people who might get involved in this process.’  Or it might say something along the lines of, ‘Your client bought 100,000 shares in BP five weeks ago, it’s up 20% now.’  On looking into the system and seeing that there’s a risk of BP heading south again, Lodebot might say, ‘Why don’t you take some of it off the table just to bank a little bit of profit. Even if the client has sold BP anyway, he will still value that call as he will need to justify his actions. The Lodebot is there to make suggestions to the trader or the fund manager to help them to be better at their job.

‘From a client relationship point of view, Lodebot can demonstrate that a broker is managing and looking after a client’s position – which is something that brokers are usually not renowned for.  They’re usually renowned for getting a client into a position and then not really taking any ownership of it. You can use the Lodebot framework to change that negative outcome into a positive one.

‘One of the key Lodebot features is the ‘to do list’.  Let me give you an example of how that works. Let’s say I’m a research analyst. I’m logged into the Lodebot and it might inform me, in my personalised ‘to do list’ that I’ve got a house buy recommendation out on Anglo American.  We can see that there’s been some positive Twitter sentiments, some positive news, something else going on or maybe something on the sector. Lodebot can highlight that information and suggest to the analyst, ‘Why don’t you stroll down onto the trading floor, pick up the microphone, and say, “Look, we’ve been a buyer of Anglo American for the last six months, we think it’s really good from a fundamental point of view and, actually, there is some other stuff going on which reiterates that call.  So, there’s a good reason for you sales guys to go back out there and bang the drum on AAL again.”’

‘If you’re a sales trader or trader, the Lodebot might tell you: ‘Your client bought 100,000 shares in BP a few weeks ago, ring him up and ask him if wants to take some money off the table to lock-in some profits” or it might say, ‘Actually, your client has got some WPP in his portfolio.  We know that because his fund information gets published out and, actually, WPP is looking very good on a variety of different metrics, different analytics and different sources – both inside the company and externally.  So, you can suggest to him:  “We know you’ve got some WPP in your fund, do you want to buy some more? Because, we think that’s a good call.”’

‘And how do you receive and deliver all this information? Well, you can talk to Lodebot through a variety of different mechanisms. There’s an HTML5 website you can log into.  You can talk to Lodebot through Symphony, which is one of the growing messaging platforms or on Skype, Microsoft Teams, Slack, and other similar systems.  They’re all simple messaging systems and we can bolt all of those messaging systems as well as SMS and email onto the Lodebot. The idea is that you can communicate with the Lodebot however you want to.  We can build a gateway for whichever particular messaging system you might wish to use.

‘Another feature is that when your broker is communicating with clients, the Lodebot becomes an additional conversationalist in that trading room. During a bilateral conversation the Lodebot will be listening and learning and will then promote ideas around that particular conversation.

‘Finally, but importantly, Lodebot is also relevant to middle-office functions such as risk management and trade reporting. LodeBot can be configured to look for particular scenarios and report them as they occur – acting as an automatic reporting agent to help minimise risk at the portfolio and company level.’

To summarise:

Before LodeBot:

  • Disparate silos of data, research, news, CRM and trade history
  • Random analysis by individual brokers with inconsistent client relationships
  • Labour intensive processes to “find reasons” for brokers to engage clients
  • Growing pressure on brokerage costs and inefficiencies, due to MiFiD II, etc.
  • Data from client relationship stay in the hands of individual, sometimes transient, brokers

With LodeBot:

  • Joined-up data, tailored to client preferences and available via chatbot
  • Cohesive, AI analysis producing consistent signals and recommendations
  • Automated processes providing “golden reasons” to engage clients
  • More effective relationship management resulting in higher conversion rates
  • Broker-client relationships automatically tracked, so vital IP stays in your brokerage

 

To learn more contact  info@lodestar-ecosystems.com