Building the future of retirement planning
OPPORTUNITY
Denver-based startup Income Lab was founded by financial services industry veterans who had an idea they knew would revolutionize financial planning. The last revolution occurred in the early 2000s when the Financial Industry Regulatory Authority, or FINRA (then known as NASD), allowed for the use of random “Monte Carlo” analysis rather than straight line appreciation. Since that time, nearly all financial advisors have taken the same four factors into account when developing a retirement plan: the client’s risk tolerance, age, income and investable assets. From that, the planner devises a one-size-fits-all financial plan. Income Lab knew they could do better. They devised an algorithm which incorporates historical data and the current economic environment to create a tailored solution to each client’s retirement plan.
Through their research and development phase, Income Lab developed a calculation engine to prove out their algorithm. The next step was to transform their proven algorithm and approach into a user-friendly retirement planning tool that all financial advisors can use to offer improved, personalized advice. After seeking bids from multiple companies, Income Lab partnered with 27Global to help realize its vision. 27Global had the unique combination of local technology leadership and FinTech business experience combined with the ability to leverage offshore software development.
SOLUTION
The 27Global team engaged with Income Lab to define the complex requirements of the software-as-a-service tool that would deliver their vision. Key challenges in product development included identifying who the future customers might be and how they might use the product, how to run the calculation engine in the cloud, at scale, and how to deliver the product in a way that would blend into existing financial planning practices. 27Global worked with Income Lab to identify the management hierarchy of those future customers and the different needs of each tier of users, which allowed 27Global to create useful and visually pleasing user interfaces for each need.
To create the end product, 27Global:
- Converted the original calculation engine from MATLAB to a Python-based service in the cloud,
- Used AWS Lambda to run the engine in a scalable, serverless environment,
- Created the front-end customer user interfaces with Angular,
- Tied the user interface to back-end processes and the calculation engine using a containerized .NET solution,
- Built third-party integrations with a billing system and financial aggregator system,
- Hardened the solution to meet rigorous financial services industry security standards.
The project spanned 10 months, with daily collaboration between Income Lab’s founders and 27Global consultants. One of 27Global’s U.S.-based architects oversaw the technical aspects of the project and worked with the offshore team to translate the MATLAB-based engine into the scalable Python cloud-based tool and build out the full software-as-as-service product.
“Whatever the task or the problem we’ve been trying to solve, they’ve had someone who could provide a solution, and they didn’t have to go outside 27Global to find that. It felt like a one-stop shop.”
-Justin Fitzpatrick, Co-Founder & CIO, Income Lab
Results
Income Lab launched the new product in March 2020, in the middle of the coronavirus shutdown. Despite that, the tool has gained traction, and Income Lab has received very positive feedback about its analytical capabilities, ease of use and modern user interface. In fact, one financial advisor who recently gained a sizeable new client chalks it up to Income Lab’s ability to more quickly show clients a better way to plan for retirement. 27Global’s ability to help Income Lab achieve its usability goals contributed to Income Lab’s game-changing impact on the retirement plan industry.
“27Global helped us create a clear, concise, user-friendly design. As a result, Income Lab is changing the conversation around retirement.”
-Johnny Poulsen, Co-Founder & CEO, Income Lab
