StratiFi is a risk management platform that provides a one-stop-shop solution for portfolio risk analysis, client risk profiling and compliance so firms can manage the right risks that are essential for their success. StratiFi’s PRISM technology provides Factor-based risk analysis that is deep and robust. This allows you to distinguish between factors that increase upside potential from factors that reduce downside risk. Our client profiling questionnaire evaluates both risk tolerance and financial capacity to help you identify a suitable portfolio for your clients to meet their goals.
✅ This was the place where I learned to set realistic limits for myself. I loved the team, the product, and the mission. However, I stretched myself thin through a long commute and long hours. I learned, subsequently, how to better manage my time and manage up when it comes to leading in a product organization. This role also sparked my interest in economics and finance, which is why I’m pursuing those degrees.
StratiFi is a risk management platform that provides a one-stop-shop solution for portfolio risk analysis, client risk profiling, and compliance so firms can manage the right risks for their success. StratiFi’s PRISM technology provides Factor-based risk analysis that is deep and robust. This allows you to distinguish between factors that increase upside potential from factors that reduce downside risk. Our client profiling questionnaire evaluates risk tolerance and financial capacity to help you identify a suitable portfolio for your clients to meet their goals.
I was brought in as their Lead Product Designer to manage the day-to-day around design and building out a product experience that could win clients and Series-A funding.
Financial services firms are increasingly aware of the limitations of classical, judgment-based risk measurement and management approaches. Collectively, firms are looking to the power of data to augment their capabilities, strengthen risk management protocols, and drive business value through better risk analytics. However, many institutions have found that a significant data uplift and cleanse is required to enhance the quality of data and inputs prior to implementing these data-driven techniques in addition to evaluating and potentially supplementing the data quality controls to maintain assessment inputs.
The Approach
Build a proprietary rating technology that provides client prospects with insights about their portfolios that their current advisors simply can’t. We took a combined 30 years plus of experience in financial planning and distilled it into some of the most important concepts involved in de-risking portfolios. We went directly to financial advisors, institutional investors, and their customers to learn about the tools and methods they use. We took our deep knowledge of institutional investing and applied it to our algorithms and models. We used Dapulse (now Monday) to manage our roadmap and projects.
Understand the user
Understand current state
Identify design scope
Develop iterative, low/medium fidelity designs
Develop high-fidelity prototypes
Apply GUI standards
A lot of this is proprietary and not really meant to be shared, so take a look at some stuff that isn't protected by NDA.
We worked in 2-week design sprint cycles that lined up with development output and our trading algorithm team’s updates. During this time we built flows and wires using OmniGraffle, created prototypes using InVision, and tested our flows and screens with in-person interviews.
A product loved by clients and their customers that now provides risk analysis and monitoring for a cumulative $50,000,000,000+ in assets. Also, a completed design language and system, new UX processes, new product development processes, and a lot of high-fives.