Whitepaper: empowering deal teams to make better decisions with data and generative AI

June 14, 2024

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In today’s market, the ability to quickly and confidently qualify an opportunity and build internal consensus and momentum for an asset is a key competitive advantage. The recent step-change in generative AI, when harnessed judiciously with full awareness of its limitations, and in tandem with data, can help firms realise a material edge.

Our latest whitepaper describes a method for generating an initial outside-in investment paper on a private company with dramatically reduced manual toil. Such a workflow enables investors to confidently take key decisions earlier in the deal process, maximizing precious time and attention on the right opportunities.

Augmentation of the deal process with alternative data and generative AI empowers stretched deal teams to improve the pace and quality of decision making.
Confident quality decisions made earlier in the deal process reduce the opportunity cost of pursuing an asset.
Automating production of an initial investment paper is critical path to optimizing the overall deal process and a great place for a firm to start their AI journey.
Pairing the investment paper with a conversational AI assistant enables more intuitive scrutiny of an asset by decision makers which can help to build important momentum.
Using AI to reduce repetitive toil on manual tasks creates capacity for more uniquely human value- add insight and reasoning.
To realise the benefits of AI augmentation, key challenges with the current generation of AI models must be overcome, requiring specialist know-how.
High quality, complete and correct data is a pre-requisite; AI can help with knowledge extraction from documents.
Firms should publish internal guidance on how to safely collaborate with generative AI, reinforcing the responsibility of the human user to act as editor-in-chief for all outputs.

Download the full whitepaper to learn more about leveraging data and generative AI for better decision-making.

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