Speaker Interview: Conor Twomey, Head of Customer Success at KX

1. Please give us a little introduction on your current role and what you do

“I am currently the Head of Customer Success at KX, where I'm working to continuously generate enterprise value for our customers with a skilled team of product adoption experts. I’m also fiercely passionate about mentorship. Previously, I had the good fortune of representing Ireland at the World Economic Forum Under 30 community and, more recently, was recognized at Irish America's Business 100 and Wall Street 50.”

2. What do you consider your biggest professional achievement to date?

“I've spent the last 14 years of my career pursuing one singular goal – to help leading corporations around the world solve their most demanding data problems – and I’m particularly proud of the arc or evolution my journey has taken. I started my career in professional services where the problem-solving tended to be limited to one-to-one (one company or perhaps one application) but when I transitioned to KX, I could problem-solve at scale using our integrated software capabilities. Now, as our software business has grown, so has our problem-solving toolbox. It’s a really exciting, transformative time in my career but also in the market overall.”

3. What has been your /your firm’s top 3 priorities for the coming year?

“Our mission at KX is simple: to accelerate the speed of data and AI-driven business innovation for our customers to help them transform into real-time, intelligent enterprises. To do this, we need to ensure their data scientists and machine-learning experts get to the ‘why’ faster and more effectively, which will require a dedicated focus across a few areas. First, we need to rationalize the delivery and functionality of our technology, the world’s most performant data engine, for these data engineers, data scientists and app builders. If we’re able to do this, while simultaneously supercharging the tools they’re working with, we’ll be able to turn them into superheroes – and that’s how companies really being to unlock enterprise value.”

4. What do you think are the biggest challenges facing data scientists/AI experts/quantitative practitioners in 2023 and beyond?

“One of the biggest challenges that continues to thwart many organizations is cloud storage, compute and enterprise SaaS costs and, more specifically, the ‘cloud paradox.’ The level of scrutiny right now is incredibly high as businesses try to manage and reduce costs, but this practice can also stifle the same data-driven decision making and innovation that contributes to competitive advantage. Attributing an ROI to cloud/SaaS is a key first step (e.g., how will these activities contribute to yield improvement, alpha generation, etc.). Then by analyzing real-time and historical data can a firm make more informed decisions about how to allocate their critical technology resources.

We’ve also just seen three years of black swan events, and companies need to prepare for a regular cadence of them moving forward. Simply put, they’re the new precedent and as the frequency of these events continues to increase, you have to have something that’s capable and highly performant to guide you through the quagmire. Companies that have adopted a true data-driven approach at scale have been incredibly successful during these events; alternately, companies with a batch mindset really struggle and take years to recover. In short, if you’re not going forward, you’re going backward.”

5. To what extent do you see the use of blockchain/crypto integrating into capital markets? As crypto is becoming more mainstream, how have hedge funds responded and what could be the potential impact on capital markets?

“When you strip everything back to its bare essentials, the basics behind trading crypto are similar to how traditional capital financial markets operate, but the 'winter' we experienced revealed real schemes, fraud, and failures. There is obviously a need for protection but this trend toward greater regulation and political pressure was already beginning to grow. In capital markets, market stability breeds investor confidence and the same is likely true for crypto -- in time, the steps being taken by the SEC and other state and federal organizations to regain public trust will lay the foundation for the next round of innovation that this sector has become known for.”

6. ESG and sustainable investing is still a key topic but something that quant professionals are not always engaged with. How do you see this progressing in the coming years and influencing portfolio management?

“To ignore ESG and its influence on portfolio management would be misguided. In many ways, sustainable investing is table stakes – in fact, research suggests that total investments in global sustainable assets ballooned from $5 billion in 2018 to $2.5 trillion by mid-2022. Recent events – like the invasion of Ukraine or that which embroiled the Norwegian sovereign wealth fund and its ties to certain ports-to-power conglomerates – clearly show that there is a risk to ESG and portfolio investments. If you’re not putting an ESG lens over your data, you need to wake up and smell the coffee.”

7. Alternative data is still considered a source of alpha for many – what roadblocks do firms tend to come across in sourcing, cleaning, and using this data? How do you view the alt data market at present?

“Alt data prior to Covid was considered crucial to alpha, but the market has become so volatile since the onset of the pandemic – the GameStop debacle comes to mind – that its role has fundamentally changed. That said, it’s worth noting that the importance of data quality standards remains the same. In recent years, as alternative data evolved, we also witnessed a parallel disruption in the distribution of alt data content via the emergence of various data marketplaces. Onboarding alt data or market data has typically required a 6-week workflow, but a quant can determine it’s garbage in 6 minutes.”

8. Our research this year showed a lot more firms and practitioners talking about NLP than usual – why do you think this is? Where are seeing the optimal utility for NLP and where does it have the potential to go?

“Any increase in conversation among firms and practitioners regarding NLP is undoubtedly due to ChatGPT and its public beta release before Christmas. It has tremendous implications in the legal and financial markets and it’ll be especially interesting to see how its utility in, for example, market abuse regulation and investigation will grow as its capabilities mature. One area of real value, from my perspective, is its ability to condense manual time for processing huge documents and unstructured text quickly as a sort of index engine. This, in conjunction with the power of human knowledge and experience leads to real wisdom and that combination is unstoppable. But feel free to go straight to the source and ask ChatGPT itself!”