How AI can optimise the Forecasting or Budgeting Processes for Finance ?
Prashanth P.
Executive Leadership | Turnaround Strategist | Transformation enabler | Corporate Finance | FP&A | Process Optimisation | Risk & Compliance | ESG | Pharma & FMCG | Retail| Ex-Citi| Ex- Nomura| Ex-Flemingo | Ex- Aspen
Right now, your finance department is probably pretty busy. People need statements, invoices, reports, general ledgers, and many other forms of paperwork. There’s even more paper in the snail mail!
It’s a necessary evil for finance. But, artificial intelligence has the ability not only to reduce the amount of paperwork but also to help companies manage some of their most vital financial information.
Finance departments are mostly dominated by humans. However, with artificial intelligence, they can dramatically decrease the amount of paperwork they have and, more importantly, the amount of paperwork they need to have.
Finance departments have incredibly valuable and vital financial information. However, that information needs to be organized in a clear and comprehensible way. Employees also need that information stored and accessed quickly.
Ultimately, those human employees also cost money. They need to be paid, they need healthcare benefits, they need money for transportation. Companies are paying a lot of money to their employees for those jobs. However, today’s technology enables them to take on those jobs with artificial intelligence.
There are incredibly useful ways that artificial intelligence can ease the workload of employees. Here are some of the ways that AI could be of value:
AI can make the work of accountants and human resources easier. By not having to go through mundane tasks and work, they can focus more of their time on doing their jobs. It will also help companies to save time and money.
Overall, AI is incredibly helpful. It can do a variety of things to help any company. While it may not take over the entire work of the finance department, it can dramatically decrease the amount of paperwork they use and what they can do, ultimately helping your company to be more efficient.
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Can AI help organisations in Forecasting?
Imagine you are the CFO of a large enterprise and you are managing the 2018 financials. At this point in the process, you know, without a doubt, that these figures are going to be difficult to meet. Take, for example, the revenue target, this is required in the business plan and this revenue target seems tough to achieve. You have had a few problems in the past when it comes to accurately forecast revenue and this seems to be an even bigger challenge now.
Accountants have the difficult task of assessing the likelihood of specific events and forecasting outcomes. Much of this data can be found in areas such as warehouses and production facilities, but there are also issues that can be widespread across the whole company.
The problems that the finance department faces are numerous, they have to consider all of the issues that need addressing in order to properly plan for the future. The finance department collaborates with various other departments to conclude on the Budgeting and Forecasting on the basis of the insights and the available data. When dealing with forecasting performance, they have to consider several questions such as the following:
It is at this point that the questions which need to be answered can become overwhelming, especially as businesses are often growing and changing at such a rapid rate. Now, this is where AI comes into play, this supercomputer-like tool can be used to come up with statistical predictions, which can then be managed and used to see how these predictions can be improved and altered if necessary.
What exactly does AI forecasting do?
Algorithms have been slowly developed since the 1950s. These algorithms are now able to outperform human logic.
The initial stage of AI involved data feeds. Algorithms have been used for many years in stock markets and banks, using statistics to determine the probability of certain outcomes.
However, nowadays, AI is able to analyse vast amounts of data, at a much higher speed than a human being. This means that algorithms can make decisions that would previously have required humans to spend a great deal of time analysing and searching for data.
How do they decide?
Historically, machine learning has only used input from humans. However, it has evolved to a point where it is able to interpret and process large amounts of digital information, using algorithms, without the input of humans at all.
These algorithms analyse vast amounts of data, try to establish trends, analyse patterns, and calculate probabilities.
How much data is relevant to them?
More often than not, the AI system will be set up to take in data from a specific area, e.g. sports, finance, etc. It is going to be analysed using statistical data, which will then show trends and patterns.
In the case of finance, the AI system will need to analyse a large amount of data, from different departments, countries, and countries of origin.
How can I use this data?
Once you have analysed this data, the AI system will be able to predict outcomes for a given project, e.g. how many cars need to be manufactured to meet projected revenue?
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However, AI forecasting is only going to be successful when it is implemented in several areas across the business. In order for it to work properly, it needs to be used across all areas of the business. To do this, changes will need to be made so that processes in different departments (Sales, Marketing, etc.) are able to feed data to the AI system.
The Benefits to Using AI for Forecasting
Artificial Intelligence has become increasingly prevalent in all of our lives. Being bombarded by adverts on the TV, being recommended products online that are similar to ones we searched previously or receiving emails automatically from people who do not know us. All of these are examples of Artificial Intelligence.
A lot of organisations are increasingly adopting Artificial Intelligence (AI) into their businesses for a number of different purposes. The benefits of AI budgeting and forecasting has been overlooked by many organisations around the world. This is likely because AI budgeting and forecasting can be extremely daunting to the average person.
AI budgeting and forecasting can be broken down into a number of elements.
AI and machine learning for forecasting
There are 2 primary ways in which machine learning is used. Firstly, for budgeting. Rather than relying on your finance department to enter figures into your system and either maintain them manually or train your staff to maintain them.
If you adopt a machine learning platform this can help your staff to maintain those numbers automatically, based on pre-existing templates. For example, Microsoft Excel can be used to understand and manage numbers and formulas within spreadsheets.
Secondly, for forecasting. So much of the decision making that managers have to make is based on forecasts. Predicting sales, predicted ROI of marketing campaigns or predicting who is likely to leave the business etc.
If your managers have access to a machine learning platform with forecasting capabilities, they will be able to make these decisions more easily. This is because the AI would be able to predict these figures based on algorithms that have been trained previously on data related to your business.
There are of course other considerations when looking at AI for forecasting. Things like the complexity of operations or industry. However, there are some amazing tools on the market at the moment, such as https://www.cleverics.io/. That can help you to start using machine learning to predict trends in your business.
AI for cost optimisation
Cost optimisation is such a great area to look at when thinking about using AI.
A great tool for cost optimisation is https://www.visualeconomics.com/. This tool allows you to build automated cost optimisation scenarios. It allows you to plan your cost-cutting activities and then set AI to find the best way to achieve it. This is all done visually and without the need to write any code.
AI for data gathering and analysis
There are so many areas of business that rely on data. Before being able to take action on data you need to collect it. AI can really help with this process.
One of my favourite uses of AI is hiring platforms. To take the process away from manual screening and categorising of CVs, to have AI do it for us. This is amazingly beneficial to the business.
One of the main issues is that AI for data gathering has to be trained to understand the intricacies of your business. Often, this can be time consuming and tedious. You need to prepare the data and train the AI before you find it useful.
Another consideration is compliance.
As AI is built by humans, it is going to reflect the biases of those humans. You need to ensure that the AI platforms that you use reflect your industry. If the algorithms fail to match your industry regulations then they will fail.
Also, the AI needs to be updated when circumstances change. As a business owner, you may be reluctant to do this because it becomes an additional task. However, failure to update the AI could result in failure for your AI.
On the whole, I believe that using AI for budgeting and forecasting in organisations is a great idea. There are already some fantastic tools available that can automate most tasks and can be trained on your business in a few hours.
Final Thoughts
I hope this blog post has demonstrated the benefits of using AI in Forecasting and Budgeting. Although at first glance it seems like a complex process of putting data in models, it is exactly the opposite. The information provided by the Finance department is valuable however it can be manipulated and bent to show whatever data they want. AI can cut the time that Forecasters spend on other duties and help save time overall. I hope the main points from this blog post have been insightful and you will be able to improve your forecasting.
Can be reached via email - [email protected] or a private message on LinkedIn if you would like to discuss this topic further.
You can also visit my Blog for other articles: www.financepsyche.com