Finsbury Growth & Income Trust plc (LON:FGT) manager Nick Train has reiterated confidence in the investment trust’s long-term strategy, arguing that recent share price weakness in several holdings reflects market sentiment rather than a deterioration in underlying business performance.
Speaking in an interview with Gavin Lumsden, Train outlined the trust’s investment approach and addressed investor concerns about the influence of artificial intelligence on companies that rely on proprietary data and analytics.
Finsbury Growth & Income Trust has been managed by Train for 25 years and the investment vehicle itself has a history of more than a century. Over Train’s tenure the trust has delivered total shareholder returns almost double those of the FTSE All-Share index, reflecting a strategy focused on owning a concentrated portfolio of durable, high-quality businesses.
While performance has been more challenging in recent years, Train said the long-term characteristics of the portfolio remain intact and continue to provide the potential for attractive returns.
The trust has historically invested in strong global consumer brands as well as established UK-listed companies with leading market positions. Over time it has also built meaningful exposure to businesses operating in data, analytics and software services. These include companies such as London Stock Exchange Group, Experian, Relx, Sage and Rightmove.
Approximately half of the portfolio is now invested in companies whose business models are built around proprietary data and technology platforms. Share prices across this segment have fallen over the past nine months as investors reassessed the potential impact of artificial intelligence on established data providers.
Train said the underlying companies continue to deliver steady growth and strong operational performance. In his view, the recent share price declines reflect uncertainty about the pace and direction of technological change rather than evidence that artificial intelligence is displacing their services.
He argued that companies owning unique datasets are well positioned within the emerging artificial intelligence ecosystem because their information cannot easily be replicated by general-purpose AI models trained on public data.
Train referred to a framework described by London Stock Exchange Group chief executive David Schwimmer, which divides the AI landscape into computing power, large language models and data. In this structure, companies with large proprietary datasets are able to benefit from advances in AI models and computing infrastructure by applying them to generate new insights from their own information.
Recent developments at London Stock Exchange Group were cited as an example. The group has announced several multi-year enterprise agreements with global financial institutions for its data and analytics services. Train said these agreements demonstrate the value of the company’s data assets and the continued demand for trusted, structured information in financial markets.
Experian was highlighted as another example of a business whose proprietary databases provide a strong competitive advantage. Train noted that more than 20 of the 25 largest US financial institutions rely on Experian’s services, which are built on confidential credit and consumer data that is not publicly accessible.
Several portfolio companies are also integrating artificial intelligence directly into their products and services. Property portal Rightmove recently launched a conversational search tool developed with Google Cloud using the Gemini AI model, aimed at improving the property search process for users.
Train also pointed to Relx, whose risk division has expanded significantly over the past two decades through the application of machine learning and artificial intelligence to its data assets. The division has grown from representing a small proportion of the company’s value to becoming a central driver of its business.
He acknowledged that artificial intelligence represents a significant technological shift but said there is currently no evidence in company results or customer demand that AI is displacing the services provided by these businesses. Instead, many are using the technology to strengthen their products and deepen customer relationships.
The trust continues to follow a highly concentrated investment approach focused on companies with durable franchises, strong margins and high returns on capital. Train said the process begins by assessing whether a business can remain profitable and relevant over a period of at least two decades.
Recent portfolio changes include building a position in shipbroker Clarkson, which Train described as the leading data provider in the global maritime industry.
The trust does not use financial gearing and instead relies on conviction and concentration to generate returns. Train said this approach has historically delivered strong long-term performance and continues to underpin the portfolio today.
While he acknowledged that recent share price weakness has been disappointing, Train said the quality and resilience of the underlying companies give him confidence in the trust’s long-term prospects.
“If the companies are right and we are right, the potential returns from these businesses remain significant,” he said.
Train added that the portfolio continues to consist of high-quality franchises similar to those that drove the trust’s earlier outperformance and that the current period of uncertainty could ultimately prove to be an opportunity for long-term investors.
Finsbury Growth & Income Trust PLC. Invests in the shares of predominantly UK-listed companies, with the objective of achieving capital and income growth.
