The Birth of a Technology Platform
Prior to the launch of our broker-dealer, we saw a need for a more intuitive user experience when interacting with our firm. As we sat down at a conference table overlooking Tampa Bay in the early hours of a cool March day, our team had an epiphany. A third-party technology stack was never going to provide the customization, innovative approach, or the level of direct accessibly that we prefer to provide for our financial professionals.
We’ve invested a significant amount of time and money planning out the structure and vision of our platform. We started out by determining the core components that would create a frictionless experience for our users and then worked to identify key technology and tool providers that would grant us the flexibility to continuously improve based on user feedback. Here’s how we’re building it.
We’ve built Advisor[X] on top of established, comprehensive platforms that were developed by companies spending millions of dollars and thousands of developer man hours on R&D. This allows us to focus on what really matters: streamlining the financial professional experience. Our engineering team leverages existing APIs that allow for a more efficient transmission of data across applications.
The underlying tools and methodologies we’ve chosen give us the flexibility to bring features to production more quickly, without sacrificing quality or intentionality. Python, the framework we used to build Advisor[X], is the same technology used to build Instagram. In addition, many of the components that are being used in our backend logic and data interactions are also being deployed by Facebook, Google, YouTube and Dropbox among others.
We chose this stack for a few reasons. In the short term, these tools allow us to bring features to bear far less code than other frameworks. This give us flexibility in how quickly we bring features into production.
In the long term, many of the more complex concepts that will power features within Advisor[X] are being used by the leaders in these fields. The Data Science community has brought a huge amount of knowledge and resource into Python, allowing the integration of machine learning, natural language processing and other complex algorithms to be used in platforms like ours.
Our team of stakeholders has years and years of experience in the financial industry. This combined experience has driven the vision of Advisor[X] from the beginning. That said, it is important that our users direct our roadmap. To quote our CCO, Chris Hamm: “We’re taking every financial professional’s pain point that we encounter and creating a solution for it.”
Our platform is not being built in a vacuum; instead, our financial professionals have the power to guide the development and priority of features that we provide. We have already added several improvements to Advisor[X] based on ideas from our early adoption users and we are excited for what the future holds.
We set out with the goal of creating a frictionless financial professional experience that would drive efficiency and reduce the cost of doing business. We’re building it to ensure that Advisor[X] will continue to be relevant as our industry changes and technology evolves. With all of that said, the importance of the tools isn’t in the technicalities; it’s about the flexibility that the tools provide. This flexibility allows us to hold true – now and in the future ¬– to our vision and ensure that Advisor[X] is the best tool for financial professionals.
Third party service providers (OR strategic partners) mentioned are separate entities from IFP.