We all know that designing and implementing software code requires time and money, but this is just one side of the coin. As a financial services company, you also need to factor in the costs of maintaining and keeping the service running, especially at times when your operations are decreasing or increasing. That’s why scalable financial software is so crucial to any small-to-medium enterprise looking to choose its automation software.
As defined by Gartner, scalability is the measure of a system’s ability to increase or decrease in performance and cost in response to any changes in application and/or system processing demands.
Now, it may seem obvious that an application being used by one user would require different levels of technology to one being used by a hundred; and that running a single portfolio hedge fund should require less power than managing 10 hedge funds and 50 accounts. Yet, the reality is that most open-source and off-the-shelf software uses technology that does not allow for this flexibility, often leading to companies having to invest more money in creating software from scratch whenever they grow.
Python and R are coding languages that have become the darlings of the financial industry due to the vast offering of open-source libraries from the community, including to create investment strategy automation for hedge funds. Python, in particular, is much beloved due to its easy-coding language, and it is taught as the programming language of choice for processing and modelling data at most universities.
Unfortunately, one thing many financial companies don’t realise is that in the race between open-source vs enterprise bespoke financial software, the former tends to come with numerous limitations that see costs skyrocket.
For example, neither Python nor R can run 24/7 complex applications with high-availability, multiple connections, or high volume data. This limits companies using software only coded in these languages, particularly when things are going well and they are looking to scale up and run more complex processes.
One of the problems with such software is that a small financial services company’s investment manager will struggle to on-board and manage a new fund or managed account. But, worse still, the amount of energy, time, and money required to work with such technology can be huge.
As we explained in our financial software costs article, this is why it’s extremely important that an SME starts working with the right technology from the get-go.
Our partnership with global infrastructure software leaders, TIBCO®, has allowed our Framework to give SMEs the same scalable financial software larger corporations use, but at a smaller price tag.
This doesn’t mean fewer capabilities, though. Our Framework uses TIBCO Streaming®, which is an event stream processing software that can be used to build complex streaming applications that developers using Python could never reach. More than that, it has adapters that easily allow you to use Python and R modes while adding the advantage of having a more robust trading infrastructure full of already-coded financial streaming adapters.
Meanwhile, our investment strategy automation software – called CYBMIND – goes beyond this, allowing you to also use TIBCO Spotfire® technology for the front-end to easily build multiple custom GUIs.
The idea behind all this is to give you the best chance to excel against your competition and to go beyond what Python and R can offer your company. So, if you’re willing to see how the Wakett Framework could help you grow and manage that growth, get in touch with us now!