PE Firms Adopt AI for Compliance but Lack Formal Policies
Private equity firms are rapidly adopting artificial intelligence for compliance and regulatory reporting but few have established formal policies governing its use in these areas, according to a survey by asset services provider Ocorian.
Adoption Levels
The survey covered private equity managers across the US and Europe with a combined $3.51tn in assets under management. Around 69% of managers said they use AI for compliance and regulatory reporting related to deals and investment decisions. Portfolio monitoring and performance analytics were cited by 57% of respondents. Some 44% use AI for due diligence and data analysis. A further 41% have adopted AI for investor communications and LP reporting. Around 37% of respondents said they are currently piloting AI tools, while just 1% said they do not use AI at all.
Policy Gap
Only 5% have formal policies governing the use of AI for compliance and regulatory purposes. That compares with 89% of firms that have established formal policies covering AI use in investment decision-making, according to Private Equity Wire.
Key Challenges
Some 70% of respondents identified integrating new technology with existing systems as their biggest technology-related compliance challenge over the next two years. Some 57% expect adapting AI systems to governance requirements to be a significant challenge, while 56% cited cybersecurity and data protection. Keeping pace with evolving regulation was identified by 50% of respondents as a key challenge, while only 28% highlighted the cost of compliance technology.
Abi Reilly, partner in Regulatory & Compliance at Ocorian, said the limited adoption of formal AI compliance policies was concerning given how extensively firms are already using the technology. She said managers that have introduced policies governing AI in investment decision-making should consider extending similar controls to compliance as adoption spreads across their operations, according to Private Equity Wire.
The findings suggest private equity managers face a growing need to establish clear frameworks covering how AI tools are selected, monitored and used in regulatory processes, particularly as firms integrate the technology with legacy systems and increasingly sensitive investor and portfolio data.
