Controllable AI for private markets: how do we open the black box?

As Private Equity (PE) markets experience strong growth, FINBOURNE explores how advancements in data analytics are shaping a more promising future for PE companies.

Nicholas Wood, Product Manager at FINBOURNE Technology, joined industry experts at the recent Private Equity Forum in London to discuss compelling use cases and opportunities for Artificial Intelligence (AI) within the private equity space. Below are some key insights from the session.

Key benefits of AI adoption in Private Equity (PE)
AI is rapidly becoming an integral part of financial services, redefining industry standards and creating new opportunities for PE firms. Early adopters, innovative General Partners (GPs) and portfolio managers are exploring ways to blend AI with human intelligence across key PE processes most notably deal origination, due diligence, negotiation and value creation.

With AI offering both conceptual and practical benefits, this can help PE firms better understand and improve the value creation journey for portfolio companies, while also identifying potential risks (“landmines”) for investors. Some firms are already leveraging AI for specific processes such as DDQs (Due Diligence Questionnaires).

The impact of data quality on AI effectiveness
Inconsistent or incomplete data can directly impact the effectiveness of AI, and this lack of transparency (the “black box” problem) can reduce trust in AI-driven insights. Advanced AI models, especially deep learning algorithms are often difficult to interpret, and inconsistent data means firms struggle to optimise workflows and ensure traceability over their data.

AI requires large amounts of sensitive data from portfolio companies, employees, and customers. This can also make them targets for cyberattacks, leading to potential data breaches that expose sensitive financial or personal information. This highlights the importance of implementing strong cybersecurity measures to prevent data breaches and ensure data integrity.

Due to differing data disclosure requirements, PE firms require a robust data model to support the decision-making process. This ensures that investment decisions are well-documented and validated, giving companies a clearer view of their processes.

AI is being used to enhance traditional due diligence by analysing “dark data” (unstructured and less-accessible data sources) to quickly detect risks and opportunities as well as analyse performance, all while preserving critical human oversight.

This approach allows users to uncover insights such as merger and acquisition activity, financial performance trends, leadership changes, and industry developments, all of which can inform better investment decision-making.

The FINBOURNE view
AI has the potential to transform the Private Equity space. Organisations can benefit from enhancing their data, realising a robust data science platform, and integrating these components seamlessly, to foster the effective use of AI.

FINBOURNE’s AI platform includes full traceability of every decision made by the model. This ensures that that users can fully understand and recreate the actions performed to ensure full explainability, and eliminating the “black box” data problem.

At FINBOURNE, we’re excited to make this technology a reality. Speak to an expert today to learn more.