Transforming Due Diligence with AI: From 3 months to 3 weeks
The Challenge: AI transformation in data analytics
Our client, an Investment agency with heavy due diligence needs, approached us as they were looking to move away from their existing analytics services provider: the lengthy timelines of up to 3 months to complete data analysis and visualisation tasks, paired with a cost of $10k per company analysed were not efficient and sustainable enough to allow them to scale. They were also looking to hold the entire due diligence process in-house while reducing time and cost.
This case study is a must-read for anyone in the investment / due diligence and data analytics space, as it explains step-by-step how AI can tackle the most complex of data analytics processes.
Our Solution: Custom AI analytics
To help this investment agency, we developed a custom AI analytics solution to significantly reduce time spent on due diligence processes.
Here’s how:
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Data Ingestion: From 1 Month, down to 1 Week
The first step in any due diligence process is gathering data from various sources. Previously, this process took up to a month, as the agency manually collected large amounts of data from a lot of different sources, such as sales numbers, advertising results, and operations metrics.
The first capability of our AI Analytics Tool is to automate the data ingestion process: pulling data from various sources, cleaning it, and sorting it for analysis.
This reduces the time needed for data ingestion from one month to just one week.
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Data Transformation: From 2 Days to 5 Hours
Once all the data is gathered, it needs to be aggregated and transformed into a format suitable for analysis: something tedious when dealing with a lot of different data formats. Previously, this step involved writing SQL scripts that had to be adapted to different data sets - a process that took up to two days for each project.
Our AI Analytics solution automatically adapts SQL scripts based on the data set it’s working with, reducing the time required for data transformation from two days to just five hours.
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Analysis & Visualisation: From 2 Months to Real-Time Insights
The most time-consuming part of the due diligence process is the analysis and visualisation of the data. The agency worked with PowerPoint presentations of up to 500 slides, each filled with charts and tables, and had analysts go through these slides to choose the best format for visualisation and input data into them - a process that could take up to two months.
We changed this approach by developing an AI-driven analytics interface where users could ask specific due diligence related questions, such as “Which country should we invest more in over the next 12 months?” or “What seems inefficient in our operations process?”. The LLM that answers deeply understands the database it has access to, allowing it to provide data-validated answers, as well as a few options of charts & tables for visualisation purposes.
The Results: An absolute game-changer for Due Diligence & Data Analytics
Data Analytics is a complex, time-consuming task that often seems like a mountain to climb given the hundred types of data to deal with, and the thousands of options when it comes to data-related questions to be asked and ways of answering them.
Our AI Analytics Tool can take care of that process end-to-end, from gathering and cleaning data to analysing it to answer questions. Not only does it translate into considerable time and cost spent on analysis, but it also means better and faster decision-making, as the AI is able to answer questions and access the database in real-time, and is easy to use for anyone in the company.
By leveraging advanced AI technologies, we helped this Investment Agency significantly reduce cost and time, allowing them to build their competitive edge and grow.
In summary :
How does it work? The Tech note:
Linked to our AI Analytics tool is a customised LLM (basically, what allows our AI tool to “speak”) that can answer complex data analytics questions.
To achieve this, we use something called Chain-of-thought Reasoning: where the AI automatically creates a set of prompts for itself after being asked a question by a user, allowing it to provide high-quality answers - the same way we as humans think step by step when problem-solving!
Let’s take an example: say an analyst looking at a specific company asks the AI Analytics tool “Which country should we invest more in in the next 12 months?”
To answer that question accurately, our AI will first generate a list of 10 to 20 questions for itself, such as “Which country has the most revenue?” or “Which country has the highest marketing spend?”. For each of these questions, the AI then creates a query, runs it to pull data from the database it created, and creates the corresponding graphs or charts. It then uses all that information to make a conclusion.
Once this Chain-of-thought Reasoning process is done, the AI generates an answer for the user with a detailed explanation.
Pairing an AI Analytics Tool with a customised LLM not only saves time but also solves the problem of accessibility of data analytics. Virtually anyone can use the tool to make data-informed decisions, without needing any data analytics knowledge.