On October 29, 2024, the National Association of Certified Valuators and Analysts (NACVA) issued its first Advisory Brief on “The Use of Artificial Intelligence and Machine Learning,” which is the first such Artificial Intelligence (AI) advisory from the major business valuation organizations. The brief utilizes a principles-based approach for integrating AI and Machine Learning (ML) technologies and clarifies the role of professional judgment when engaging with AI and ML technologies.
The brief advocates for a thoughtful integration of AI and ML within the frameworks of professional valuation and/or forensic practice. While not meant to be exhaustive, it serves as a cornerstone to align emerging technologies with professional judgment and ethical standards.
Principles of AI and ML in Valuation Practice
Valuators may leverage AI and ML technologies to augment, not replace, their expertise. For instance, AI can assist in analyzing data sets for market trends but should not supersede the valuator’s analysis of how these trends affect a business’s value. The decision to utilize AI and/or ML must ensure that the technology serves as a tool rather than a determinant in valuation and forensic engagements.
Professional Judgment
Professional judgment when incorporating AI and ML into an assignment refers to the valuator’s capacity to make informed decisions grounded in knowledge, experience, education, training, and skills. An example of exercising professional judgment is when a valuator uses an ML model to predict cash flows but critically assesses and adjusts the predictions based on unique business factors that the model may not account for in the output. Valuators must scrutinize AI and ML outputs, weighing them against the nuances of each valuation context, which may include qualitative factors that cannot be calculated.
Ethical Considerations
- Analysts incorporating AI and ML into an assignment must consider ethical standards, particularly concerning confidentiality, data integrity, and non-discrimination. When utilizing AI for demographic analysis, the analyst must be cautious not to infringe upon privacy or inadvertently introduce biases that could skew valuation conclusions or perpetuate inequality. Utilizing an AI tool, such as a chatbot, produces the risk that sensitive data included in the chatbot could be recorded and later accessed by unauthorized users. Analysts should consider utilizing non-confidential information or ensure that the AI tool is designed to comply with such confidentiality standards, thus preventing data retention post-interaction. This safeguard maintains the integrity of client data while allowing the user to benefit from AI and ML efficiencies.
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Verification and Reporting
- When incorporating AI and ML technologies, it is essential to verify the AI and/or ML outputs are not misleading. If AI technologies are used to predict the future revenue streams of a company based on historical data, the valuator needs to consider professional judgement. Additional considerations may include:
- Collect the similar historical data inputs used by the AI tool;
- Apply the predictive model using standard statistical software or manually through a process such as Excel, ensuring the same variables and time frames are considered;
- Compare the manual or software-driven forecast results with those generated by the AI tool to check for consistency; and/or
- Compare local, national, and industry data to the results produced for a sanity check.
Analysts should consider disclosing the use of any automated data output that was utilized as part of the analytical process and ensuring that such technologies were applied in an ethical manner while applying professional judgment and proper due diligence. The primary objective is to uphold the transparency of the valuation process rather than an exhaustive disclosure of all tools and processes involved. Valuators should be mindful of any litigation reporting exemptions that may apply in an engagement.
Continual Learning and Adaptation
- Valuators should commit to continuous learning to stay abreast of the latest technologies and methodologies. Analysts should actively participate in professional development opportunities, engage in opportunities that discuss AI innovations, and contribute to the body of knowledge on AI in valuation. By fostering a culture of continual learning, valuators will be well-equipped to discern the appropriate application of AI tools in their work.
The integration of AI and ML in valuation and forensic practices presents exciting opportunities, but also necessitates careful consideration of professional judgment, ethical standards, and verification procedures. While these technologies can enhance data analysis and streamline processes, they should be viewed as tools that complement, not replace, the expertise of valuators. Ethical concerns, such as data privacy and bias, must be addressed to maintain the integrity of the valuation process, ensuring that AI outputs are used responsibly and transparently. As AI and ML technologies continue to evolve, valuators must prioritize ongoing education to stay informed about new developments, ensuring they can effectively leverage these tools while upholding the principles of their profession. Ultimately, a balanced approach to AI and ML adoption, grounded in professional expertise and ethical responsibility, will ensure these innovations contribute positively to the field of valuation and forensics.
If you need a valuation for tax planning and compliance, financial reporting or transaction support, we can help. Contact Gina Miller or Brett Dixon to schedule a consultation.
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Brett Dixon- Director, Dispute Valuation & Forensics
Brett Dixon – Director in Bennett Thrasher’s Dispute Valuation & Forensics practice. He focuses on performing valuations of business entities and intangible assets to assist clients with mergers, acquisitions and dispositions; taxation planning and compliance; financial reporting; and strategic planning.
