Internet of Things vs Fintech: FIGHT!

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One of the things I enjoy in life is engineering.  Whether that’s a well written piece of code or a well thought out physical implement.  In order to understand I try to draw analogies between different types of engineering and so for this post I want to cover the many similarities between the Internet of Things and financial technology, hereafter fintech…[The title comes from the Comedian Harry Hill]
First off, what type of fintech do we mean?  Specifically, real time systems used within Electronic Trading.  And so what do we mean by “Internet of Things”.  Well, that’s a bit buzzword/VC bingo/flavour of the month but I think it’s reasonable to think of a few strands to IoT:
  1. Automotive sector – See this EU link http://europa.eu/rapid/press-release_IP-14-141_en.htm.  In short, all new cars sold in Europe will be mandated to have a mobile telecommunications device built-in, initially to allow the car to contact the emergency services in the case of a perceived incident.
  2. Household sector – the internet connected security camera, nanny camera, alarm system, heating/cooling system.
  3. Sporting/activity sector –heartbeat monitor/GPS/accelerometer/altimeter devices linked up with cameras.
  4. Smart grids – electricity grids that communicate to allow usage to be smoothed such that peak load capacity can be managed at a more affordable cost.
These are just a few things, there are many more.  So – what’s the link to finance?  Most trading systems I have worked with have had some or all of the following characteristics:
  • High availability – typically through hot/hot standby.
  • Large data throughputs – typically managed through use of high capacity network technology (10GigE/40GigE/100GigE).
  • Message based technology.
  • Stateless business logic components.
  • Geographically distributed user community.
  • Diverse user application run-time environments (fat client, web, mobile).
  • Distributed business logic – servers located in multiple regions to provide close to market support.
  • Co-location/third party datacentres.
  • Multiple database solutions – relational for static data, tick database for market data analysis, graph database for analytics.
  • Multiple development languages such as C++ for exchange gateways, C# or Java for fat client user interface, Matlab/q/R/S+/Python for quantitative models, HTML5 for web browser, iOS/HTML5 for mobile.
Now let's compare that feature set to an IoT landscape:
  • High availability – typically through hot/hot standby.==>Same for IoT.
  • Large data throughputs – typically managed through use of high capacity network technology (10GigE/40GigE/100GigE).==>Same for IoT.
  • Message based technology.==>Same for IoT.
  • Stateless business logic components.==>Same for IoT.
  • Geographically distributed user community.==>Same for IoT.
  • Diverse user application run-time environments (fat client, web, mobile).==>Not the same for IoT
  • Distributed business logic – servers located in multiple regions to provide close to market support.==>Same for IoT.
  • Co-location/third party datacentres.==>Same for IoT.
  • Multiple database solutions – relational for static data, tick database for market data analysis, graph database for analytics.==>Same for IoT.
  • Multiple development languages such as C++ for exchange gateways, C# or Java for fat client user interface, Matlab/q/R/S+/Python for quantitative models, HTML5 for web browser, iOS/HTML5 for mobile.==>Same for IoT.
So to a proposition – if you are working on an IoT project, why not hire folks who have worked on financial markets technology such as trading systems?

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