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5 minutes with… Phil Westcott, co-founder and CEO of Filament Syfter

by Matthias Plötz 24 May 2023

The Drawdown (TDD): First things first, what does Filament do?

Phil Westcott (PW): We partner with private equity firms to build their data infrastructure, which sits at the heart of their investment strategy. Our platform Syfter provides the engine of proprietary deal-sourcing and marketing intelligence that we craft for our clients.

A GP’s investment strategy is its IP. But they are under increasing pressure to develop a competitive advantage through digitalisation, which is where we come in. Our platform enables them to assimilate real-time insight on their addressable market, integrating financials, team info, news articles and alternative data from up to one million companies into one single in-house database. This platform is then enriched with AI to enable investors and analysts to interrogate their unique database to pull real-time signals and market insight.

Each of our clients ends up with deal-sourcing software uniquely tailored to them and their investment strategy. This bottles and embeds the firm’s IP into its platform, protecting the knowledge from leaving the firm.

TDD: What inspired you to found the company?

PW: Prior to founding Filament, I was an executive at IBM, leading the company’s rollout of the Watson AI platform across Europe. At the time, AI implementation projects were massive undertakings, often taking years to complete.

Partnering with my childhood friend and college roommate, Doug Ayres, we saw an opportunity to bring agility to this process. In 2016, we founded Filament and got to work on building custom AI-powered software for various financial institutions, including HSBC and Macquarie.

In 2018, we focused our attention on private markets, delivering our first operational system, using real-time data integration and applied AI technologies to allow our anchor client to overhaul its pipeline operations and source off-market deals that led to £140m in deployed capital.

Spotting a trend for private equity to invest in data sophistication, we doubled down on this play, releasing the first version of our Syfter platform in 2020 and establishing ourselves as a trusted technology partner across several blue-chip European PE funds.

TDD: What is the state of PE’s data sophistication?

PW: Across the industry, sophistication varies. Early movers like EQT have made data interrogation a key strategic lever. Some of our early clients have now accumulated a database with three to four years of market insight, which now informs their fund strategies. As an overarching trend, the bar has risen in recent years, particularly in the last 12 months.

Almost every firm is now adopting some form of data-driven market intelligence, and many are seeing the need to build this in-house to gain a competitive edge.

There is a crowd at the top who are indeed up to speed. Then there are large mid-market firms that are ambitious to use data as a differentiator but are still determining the right approach to adopt as an integral part of their core operations.

While all of them will use their preferred data vendors, alternative data is becoming increasingly important. However, it is challenging to interrogate it at scale.

The main issue here is that key data points that are needed are dispersed across multiple platforms and vendors, creating the need for an integrated and customised approach.

TDD: How do you think AI will fundamentally impact this?

PW: When we say AI, we are talking about the suite of technology and tools – most notable in this context are natural language processing and machine learning. While ChatGPT may have elevated AI to the front pages, in truth, it has quietly been adopted by firms as a driving force for competitive advantage.

Competition in the PE market is ever intensifying. GPs must distinguish themselves through the digitalisation and automation of their investment strategy. Significant competitive advantage can be achieved by firms that accumulate market data and train in-house algorithms to inform decisions and monitor the signals of the market.

Speaking of ChatGPT, there is no doubt that large language models (LLMs) will change how investors will query datasets. But LLMs pointed at the internet come with their own issues, namely: a lack of providence on the data, and occasional hallucinations that can lead the user astray. Furthermore, there are data security issues as investor questions released to the outside world come loaded with insight into their focus and investment strategy.

This is where small language models emerge, revolutionising how investment professionals query data internally. Translation and summation tools will additionally increase the amount of data available as they enable firms to access, for example, news in foreign languages.

Finally, they will enable better decision-making through entity matching. Pictures of potential investments and the ecosystem they sit in will become much bigger and more colourful.

This becomes an arms race. Databases take time to build and AI takes time to train. Firms that get in early will have a sophisticated fully-fledged tool when others just start the journey, giving early starters a significant competitive advantage.

TDD: What is next on the development roadmap?

PW: With the additional investment we received, we are reinforcing the product team and further extending our client advisory services. Now we want to develop Syfter in three key areas. Firstly, we will extend functionality to provide the ‘Iron Man suit for the private investor’, with additional tools to track alternative data and orchestrate the workflow of market intelligence within a GP.

Secondly, we will evolve the configurability of the platform to enable low-code/no-code tuning, reducing a GP’s reliance on IT staff to implement the platform. By enabling business analysts to tune each client platform, we will further accelerate time to value from a couple of months to a couple of weeks.

Finally, we want to continue partnering and innovating with the landscape of private market data vendors. By further enhancing our data matching across multiple vendors, we can offer an even better and slicker service for our GP clients, and also innovate with some really exciting new entrants in the private market data landscape.

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