Sid Ghatak draws inspiration from Henry Ford, the founder of Ford Motor Company. Just as Ford looked beyond the public’s desire for “a better horse that ate less and went to the bathroom less” to create the automobile, Sid goes beyond surface-level demands in finance and technology.
As the CEO of PivotalEdge Capital, Sid´s vision does not just address what customers say they want—he uncovers their fundamental needs and core issues to identify gaps in the market. This approach has led him to develop genuinely transformative and innovative solutions that impact customers’ lives and business’ bottom lines.
With the same spirit that drove Ford to revolutionize transportation, Sid is prepared to disrupt the asset management industry through proprietary predictive artificial intelligence solutions.
Five key principles guide Sid and his team’s approach to ensure they are focused and ready to conquer the most complex challenges. These principles are:
- Data-Centric
PivotalEdge Capital is, first and foremost, a data-centric company. Sid truly understands the power and value of data and treats it as an asset. He explains that the answer to the key business questions of: “What happened, why, and what should we do?” all lie within the data.
PivotalEdge Capital focuses on identifying the most critical and impactful data and then using only what is necessary to make the best possible decision using the simplest models. “Clean, high-quality data is the lifeblood of our entire process—from idea generation and development to testing and production,” Sid explains.
- Domain Expertise
Sid and his team tap into their 30+ years of domain expertise to create leading edge solutions. He believes the only way to solve the most challenging problems in the world is to understand them at a fundamental level. By combining his domain expertise in both Finance and AI, Sid was able to architect, build, and deploy a unique and innovative solution that has the potential to disrupt both industries. The challenge many technologists have is that they focus on becoming an expert in only their technical field; to innovate rapidly, it is critical to have expertise in both technology and its practical application in a specific industry.
- Blue Ocean
Sid does not believe in following the herd. Instead, he and his team seek to explore the unexplored. He also considers his lack of traditional academic experience in AI or computer science a strength, not a weakness. “Data behaves very differently in the ‘real world’ than it does in the lab, so I thought it was better to solve real problems for real customers than work on purely theoretical problems,” Sid said. For over 30 years, Sid has analyzed the internal and external operations of Fortune 500 companies and has translated that information into leading-edge predictive analytics systems. “I was able to apply this deep expertise in a new area and in a way that had never been done before,” Sid stated.
As PivotalEdge Capital does not have to adhere to orthodoxy or legacy systems, organizations, or cultures, it is not afraid to venture into obscure areas others might have deemed unrewarding or impossible. Sid elaborated, “We have a singular focus on solving a specific problem through any means necessary.”
- Causality
“Today, the fatal flaw in how organizations perform data science is blindly trusting machines to sift through Big Data to identify possible relationships and then simply trusting the output.” Sid explains. While algorithms may identify statistically significant – even perfect – correlations, a human can apply reason to see that there is no relationship whatsoever. The ability to reason sets humans apart from machines, and Sid believes it will take a long time, if ever before machines can reason.
For example, there is an almost perfect correlation between the amount spent on pets per capita in the U.S. and the number of lawyers in California. However, reason tells us that there is no real relationship between those two data sets. Sid highlights that it is dangerous to unquestioningly trust a machine that lacks an understanding of causality and cannot reason.
Therefore, PivotalEdge leverages financial domain expertise to identify causal relationships, instances where it is financially, statistically, and scientifically proven that X causes or impacts Y. Sid explains that although this approach is more challenging and time-consuming because it requires both domain expertise and technical expertise, the solution is much more reliable, simple, and explainable.
- Transparency
Long ago, Sid learned, “If I can’t explain it, I can’t trust it.” He points out that in critically sensitive industries such as finance, there are actual costs to being wrong. So, he is always open to explaining why his AI model made the predictions it made or better understanding why it was right or wrong. “Our solutions are designed from the beginning to have this transparency,” this is at the core of PivotalEdge and Sid´s values.
Public Sector Learnings
Throughout his career, Sid has worked in the public and private sectors. In the public sector, he had the opportunity to “think and see big” in service of his country – serving the US Government in several senior technology positions, including the Chief AI Architect for the Federal Energy Regulatory Commission.
The U.S. federal government is significantly larger in scale and size than any private sector company. It has more processes, systems, and data than anywhere else. Sid’s challenges were enormous, and his manager gave him the best career advice during his time in the public sector. “When faced with an enormous task and unable to start, my manager asked me, ‘How do you eat an elephant?’ The answer was ‘one bite at a time.'”
Sid explains that to solve big problems, one must start somewhere – break them down into smaller pieces that can be solved, which leads to innovation and breakthroughs. His approach is elegant in its simplicity: “If you can string together enough small innovations that work together as a collective whole, eventually you will have solved the big problem you started with.”
Sid also points out that his public sector roles allowed him to see the paradox of effective policy and its impact on all stakeholders. For example, while a company may benefit from collecting customer data, is that also what is best for customers? Are they merely customers, or are they also the raw materials for the product being sold – namely, advertising space for other companies? Sid shares that thinking about his work this way opened his eyes to “how similar the technologies we use every day are to the food we eat.”
“We trust the government to ensure our food is safe, so shouldn’t we expect the same from the technology and data we consume?” he asks.
Key Challenges and Successes
One of Sid’s significant challenges has been identifying the variables and data sets that truly impact and accurately predict stock prices. He points out that this has been a field of study for centuries, with some of the brightest minds in history attempting to solve the problem. It is a daunting and complex task – a mountain few have successfully climbed. “As I didn’t have the same resources as others, I had to climb that mountain in a fundamentally different way than those who tried before me,” Sid realized.
To overcome this challenge, he read every book and academic paper he could get his hands on. He discovered that most followed a similar approach to solving this problem – using the same large sets of fundamental and technical data. He quickly realized there was an opportunity to solve the markets differently using overlooked niche data, tools, and techniques that only existed in theory. “I set about the arduous task of compiling and extracting completely new data, building new tools from theoretical concepts, and continuously experimenting and refining the approach until I began to see some success,” Sid explains.
However, doing things independently and differently was both a blessing and a curse. Sid felt cursed because he had no one to discuss or bounce ideas off to test his theories. He only had the raw data from his experiments. At the same time, he felt blessed because no one told him he was crazy or wrong or that what he was trying to do was impossible. “I simply had the quantitative proof of my efforts,” Sid says. By working alone, he also had the luxury of focusing entirely on the problem at hand without the pressure of external timelines, budgets, or competing projects. “I could take as long as I needed – as long as my resources lasted.”
“The only test of success was accuracy, reliability, and transparency,” he adds. “These have become the foundation of our company.”
Sid believes the varied nature of his career is the reason behind the success of PivotalEdge Capital. He has served with distinction in many diverse roles, including executive sponsor, product owner, domain expert, architect, developer, data analyst, data engineer, product tester, front-end designer, project manager, and investor. He points out that different people typically hold these diverse roles. “By doing it all myself, I was able to rapidly devise new ideas, then evaluate, build, and test them at a speed that larger, well-funded teams could not,” he adds.
“The challenge now is taking the various roles I have served and delegating them to others so we can scale effectively,” Sid says. “It would be foolish and self-limiting to continue to do everything myself.”
Executive Order on AI Safety and Trustworthiness
Sid also played a crucial role in shaping the Executive Order on AI Safety and Trustworthiness at The White House. He is immensely proud of his contribution, mainly because it focuses on user privacy.
While working on a project involving data collected by websites, he noticed that a large amount of data was being collected without people’s knowledge or consent. As someone who has always prioritized user data, security, and privacy when developing internal systems for companies, this deeply disturbed him.
“As technology evolves, criminals are also becoming more sophisticated,” he says. “Websites are collecting information that they don’t need, and it’s fairly easy to create a profile of a person through all of this data, which criminals or bad actors can then use.”
He also stresses that governance and policymaking must strike a delicate balance. While it is crucial not to hinder innovation, especially in the early stages of new technology, it is equally (if not more) important to protect individuals – particularly when they may not even be aware they are being impacted or potentially exploited.
“Similar to food standards that protect people, I think the Executive Order was a good first step in protecting people while enabling innovation in AI and other transformative technologies,” Sid elaborates.
Entrepreneurial Journey
Sid wears multiple hats these days. He is a leader, entrepreneur, and educator – all three roles are symbiotic. As he comes up with innovative ideas or approaches to problems, he has the benefit of an environment where he can test them and
implement them immediately. “Some things work, others don’t, but this allows me to explore, put my best ideas into practice, and communicate them effectively.”
He believes that teaching others is also crucial for refining these ideas. Additionally, to properly explain a concept to others, one must truly understand the subject at a granular level and analyze it from all perspectives.
Sid has authored and taught the Master’s Certificate Program in Business Intelligence at Villanova University. Although he no longer teaches formally, he still has a ready audience of students: his children. “I have three exceptionally intelligent teenagers who have heard me talk about ‘the math,’ as we call AI in our house, for many years,” he shares. “I find it incredibly helpful to explain these complex concepts to them.”
He points out that he often must create practical examples or analogies so his children can understand. That process typically reveals improvements or changes he can make in the company’s solutions.
Just Getting Started
PivotalEdge Capital’s team is just getting started. While the company was not founded to disrupt the AI and asset management industries, Sid said, “We know we are about to.”
Under his leadership, the company aims to deliver the best possible returns with the lowest possible risk profile, fulfilling its investors’ objectives through systematic AI. Sid says that they intend to demonstrate a viable way to make AI models profitable in the markets – and it is bound to dispel current doubts.
He also highlights that AI does not need to be unreasonably expensive or consume a large amount of energy to work and perform. According to Sid, combining men and machines is a powerful force that can achieve returns far exceeding what man and machine can do independently—but it is more reliable and less costly. “We feel that if we can lead the way in this and demonstrate it on one of the hardest problems there is, then others will follow,” Sid declares.
Message to Aspiring Innovators in AI
Sid advises aspiring innovators to start with domain expertise. “Understand, in plain business terms, what you are trying to solve, build, or do,” he says. “Know the subject, the industry, and the business as best as you possibly can with a focus on how it will impact people.”
Sid also encourages entrepreneurs to find real customers and solve their problems, explaining that this approach will teach them more about their ideas than they could ever learn in a lab or garage. “If the problem you are trying to solve is big enough and experienced by many people, and you have solved it, then you will be a true innovator,” he says. “Don’t innovate for innovation’s sake.”
