How to use AI to support cash flow planning and management
Guillaume Spinner, Chief Operating Officer, Tikehau Investment Management, discusses cashflow modelling for private markets in the age of artificial intelligence.
Guillaume Spinner POSTED ON 9/28/2022 9:03:56 AM
This white paper originally appeared in Clear Path Analysis’s Private Market - Europe 2022 report.
Nowadays, it is pretty critical to have a cashflow model. We have lots of internal and external demands and fund managers use a cashflow model to make investment decisions and manage their portfolios. We, in operations, use it to follow the liquidity of the funds and to monitor the performance of the assets. We also use this information on the sales side as some investors request this information as well. In essence, having cashflow information is quite critical.
Unfortunately, private assets are not as transparent as public assets. The data tends to be scattered across different systems, databases, and portals which are managed externally. Private market data also tends to have inconsistencies. Formats can vary, and we even receive data in physical form, such as PDF. Suffice it to say, data for private debt, private equity and real assets are difficult to manage.
"Implementing this tool can help with sourcing data from reliable sources. The more clean the data, the better it can help investment teams make allocation decisions."
Artificial Intelligence to the fore
This is where Artificial Intelligence (AI) can be of help. Implementing this tool can help with sourcing data from reliable sources. The more clean the data, the better it can help investment teams make allocation decisions.
The work we do involves identifying specific market changes or trends which would make it quicker for our management team to take business decisions in investing or managing the portfolio.
On the operations and fund administrative side, we are looking at tools to automate some of the more tedious tasks. With the OCR tool, we are now able to take an invoice, feed it into the system, and have it pre-booked and read automatically, rather than having a huge workforce of accountants do it. This is a tremendous help in managing cashflows and monitoring what is happening with our funds and assets.
We are looking at AI on the customer service side as well [as] it will be able to help the team answer common queries from investors, many of which have to do with anticipating cashflows.
"You need to ensure that your IT and scientist’s skills can exchange information with the investment teams to identify good indicators that will be used to identify trends."
Managing this can be complex. The first challenge is in having all the information together in a data warehouse or hub. You then need to have access to technology or infrastructure to be able to process this data. You also need highly in-demand data scientists’ skills. Once these come together, the data can be processed, which can bring about change in decision-making, structure and even the composition of teams.
Implementing such a big project is complex and raises lots of issues. The first is the cost to develop the system. You need to have sufficient size to outweigh these costs and be able to use these complex systems. Implementation takes a lot of time. You also need to ensure that your IT and scientist’s skills can exchange information with the investment teams to identify good indicators that will be used to identify trends.
What you need to succeed with AI
"By relying more on data and automation, it makes your organisation potentially more subject to cyber-attacks, which are gaining momentum and becoming more sophisticated"
All in all, AI is bringing a lot of changes to how the company operates. It requires a lot of buy-in within the organisation to make sure that processes are deeply changed and that you can rely on your data system and tools to produce and improve the cashflow modelling capabilities.
It also raises some other challenges. By relying more on data and automation, it makes your organisation potentially more subject to cyber-attacks, which are gaining momentum and becoming more sophisticated. These risks need to be managed. Cloud is also something that you need to consider. Being global with 13 offices, we need our fund managers and salespeople to have access to data worldwide, with updates in real-time. This is difficult to achieve without cloud infrastructure. We must also respond to pressure from our clients, who are expecting more bespoke and reliable reporting.
This helps to make the case of automation and AI more compelling.
To read more and view the report in full, please click here.
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