From a Big 5 Bank to Retail FinTech: Why I Built Saku
Quick Answer: After 18 years of enterprise banking experience I saw the massive data disparity between Wall Street and Main Street. Here is the exact story of why I decided to level the playing field.
Eighteen Years Inside a Big 5 Bank
I spent 18 years at TD Bank Group working cross enterprise with product operations and strategy and execution for a variety of business lines. During that massive chapter of my career I worked alongside some of the smartest people in the entire financial industry.
When you sit on the institutional side of the fence you get used to a certain standard of data. I had daily access to the absolute best tools available. You expect instant execution brilliant visual topography and deep fundamental context. But every single time I went home and opened my personal retail trading accounts I was completely frustrated.
The Glaring Gaps in Retail Watchlists
For over a decade I downloaded and tested almost every single retail watchlist app on the market. It became a personal obsession of mine to find something that actually worked for a normal person. But they all shared the exact same glaring gaps.
They were ugly. They were slow. They were unreliable and they gave me absolutely zero context on what was actually happening in the broader economy. Instead of getting actionable intelligence I had to scroll through dozens of memes and fake gurus just to figure out why a specific asset was moving.
Trading in the Past
The biggest offense of these legacy platforms was the data latency. If your stock tracker refreshes every 15 seconds you are trading entirely in the past. It sounds like a small window of time but in modern financial markets it is an absolute eternity.
By the time you see the price update on your phone institutional algorithms have already bought and sold millions of shares. You are constantly acting as exit liquidity for the smart money because your tools are artificially limiting your reaction time. It is an incredibly unfair fight.
Combining Enterprise Experience with Retail Passion
Eventually I got tired of waiting for someone else to fix the problem. Taking my 18 years of enterprise banking experience and combining it with my intense passion for retail trading is exactly what led me to build Saku.
I knew exactly what the backend architecture needed to look like and I knew exactly what the retail investor deserved. I wanted to build an institutional grade watchlist that feels absolutely gorgeous to look at and actually respects the intelligence of the user.
Building the Intelligence Layer
Saku does not just solve the speed problem by updating with split second data. It actually tells you why an asset is moving in plain English within seconds. We removed the noise and replaced it with genuine signal so you never have to guess what the market is doing.
Not only are the basic functions of a watchlist fundamentally improved but the AI layers continue to be rolled out across the platform. We are building a living ecosystem that evolves with the market giving everyday traders the exact same high signal radar used by the smart money.
Why is data speed so important for retail traders?
If your tracker is delayed by even a few seconds you are making decisions based on old information. Saku uses split second data feeds to keep you on the exact same playing field as institutional algorithms.
What makes Saku different from traditional broker apps?
Traditional apps just give you numbers and leave you to figure out the rest. Saku pairs a beautiful interface with advanced AI layers that explain exactly why a stock is moving in plain English.
Will Saku continue to add new features?
Absolutely. We have already fundamentally improved the core watchlist experience and we will continuously roll out new AI layers and advanced tools as the platform grows.
Steven White
Founder & Architect, Saku Financial Inc.
Steven brings two decades of experience architecting strategies inside a Big 5 banking institution. He built Saku to level the playing field, giving retail investors the same institutional-grade AI, dark pool flow, and verified prediction ledgers used by the smart money.