Top of the bill today is a deep dive into how BC Partners is using generative AI in its internal processes and as a potential investment opportunity. Partner and portfolio chief technology officer Lakshman Charanjiva shares his thoughts on all of that.
BC Partners has a partner-level working group setting the private equity firm’s strategy and direction for using generative AI and is already exploring and trialling start-up companies’ tech for its own internal processes, including deal sourcing, search and retrieval and data analysis, Lakshman Charanjiva, partner and portfolio chief technology officer, portfolio operations, told me.
The London-headquartered firm is also building APIs that will let trained generative AI large language models (LLMs) combine with its unstructured and unlabelled proprietary data, which otherwise “would be hard for an associate to weed through”, said Charanjiva.
“We can certainly use GenAI for easier information gathering and filtering on news, results, conference presentations, media statements, market whispers, probability/timing of businesses we like coming to market etc,” he added. “This is work that takes our associates a lot of time and effort can be made more efficient and faster and could potentially surface something we had not been aware/thinking of.
“In our sectors and geographies, we generally know which target companies meet our investment criteria; where GenAI can be very helpful is in identifying add-on opportunities in the private markets.”
This is especially timely. Several sources have told us that making platform investments is harder than it has been for a few years thanks to the rising cost of debt, valuation gaps and other factors – meaning they have focused more on investing in and growing portfolio companies.
On due diligence, the technology “can be very useful in rapidly searching VDRs [virtual data rooms] and publicly available data via prompts, and in market scans and surfacing competitor information for our commercial diligence.
“We can apply ‘code interpreter’ to use Python to rapidly create data cuts on large data sets we receive from the target (e.g. customer cube, spend cube) – without our associates needing to learn Python coding.”
At the portfolio level, BC Partners is working with “several” of its companies to leverage generative AI in software development, legal, data analysis and other areas, to improve operational performance and efficiency.
Charanjiva listed how generative AI could create value in the sectors BC invests in:
Software/IT services: GenAI allows for the creation of new code, potentially finding errors in code, creating testing scripts etc – all of which make the code generation process more efficient
Media: Democratisation and reduced cost of content generation
Consumer: The best use-case is in customer service, where GenAI can be used to provide better, more targeted, more personalised information to call centre reps (or chatbots) as they speak to customers with complaints or service issues; potentially higher ROI on target marketing; sentiment analysis
Healthcare/Pharma: can potentially help accelerate R&D and the discovery of new drugs/molecules; in health services, automated document processing and medical image recognition are some use cases
Functions such as sales and marketing, legal, customer service, IT, knowledge management can benefit from generative AI, he added.
Other areas beyond portfolio management where generative AI could assist include the deal cycle, ownership and internal opportunities, he said.
“We will experiment and iterate with a few technologies and partners,” added Charanjiva. “GenAI technology continues to evolve and has some real risks, and we do not want to get too far ahead of our skis.”
Switching to generative AI as an investment, Charanjiva said that was more an area for big tech, venture capital and software companies embedding generative AI and LLMs into their products.
“We prefer not to take on technology obsolescence and disruption risk, so do not do venture investing as this technology is moving rapidly,” he said.
“Instead, we think that software companies that can effectively leverage and benefit from GenAI is where we should be spending our time to ride this wave; and certainly, we now ask questions about how GenAI – or even conventional AI – might benefit/disrupt target companies in all sectors we invest in.”
The companies that can leverage foundation LLM models into their products and workflows “will see a lot of interest and demand attractive multiples”, he said. “We think that the end-user facing application layer will see the most interest.
“It is possible that some of the tech-focused PE firms will lean forward and take some calculated risks on GenAI providers/services.”
KKR has made a follow-on growth investment in Swedish wealth management and corporate insurance company Söderberg & Partners.
The investment was by a Skr2.3 billion ($215 million; €197 million) share issue. The new capital will be used to support expansion across Söderberg’s markets, with a focus on building on its recent entries into Spain and the UK.
Söderberg was founded in 2004 and has its biggest footprint in the Nordic region and the Netherlands. It has more than 3,000 employees across more than 110 offices, with more than £60 billion ($76.4 billion; €70.1 billion) in assets under management and assets under advice.
Sanilea, backed by Extens, will merge with Ambler to form Amblea, a digital platform to manage and optimise medical transportation.
Amblea will operate with close to 900 healthcare institutions and 6,000 medical transportation companies.
“Sanilea provides its functional depth and expertise to the organisation of medical transportation, while Ambler adds its technology and optimisation know-how,” said Alban Douady, analyst at Extens. “This alliance will enable the group to achieve the critical mass required to accelerate digitalisation in this demanding market.”
Extens invested in Sanilea in 2019.