The second edition of 2ML: Madrid Machine Learning is fast approaching. In less than a month, on May 8-9, in Madrid, Spain, 2ML will bring together hundreds of decision makers, technology professionals, and other industry practitioners that aim to stay current with the latest in Machine Learning. During the two-day program, attendees will get a full understanding of how ML has evolved to where it is today and where the industry is headed, both from a technical and business perspective. To demonstrate the importance and benefits of adopting Machine Learning, distinguished international experts will present how Machine Learning is currently applied in different business areas, such as: cinema, sports, legal services, marketing, human resources, finance, and investments, among others.
To learn the key insights directly from each of these experts, we invite you to attend 2ML Madrid Machine Learning. In the coming days, we will post a series of blog posts authored by the speakers of #2ML18 as a warm up for the main event. Today’s post, written by Jorge Pascual, CEO at anfix, covers how ML is disrupting the accounting industry.
The accounting and finance functions of any business have traditionally been a gray world, full of gray-suited gentlemen who did things in black and white (e.g., record transactions in double entry books). These support functions garner even less attention in small and medium-sized enterprises, when compared to sales or marketing.
Although it is true that the starting point of small-business accounting has been tracking transactions that take place in the company, regular costs and revenue estimates, things have substantially changed over the last few years. Currently, the accounting industry is immersed in a moment of great transformation that will change the lives of entrepreneurs working at small and medium-sized companies, including of course, the Accounting Advisors.
The main change underway in this sector is the adoption of the cloud as a preferred means to record business transactions. This process taken by thousands of entrepreneurs and companies has given way to the existence of a large data repository. And that is where predictive models begin to provide valuable lessons. This also is ripe for Machine Learning algorithms to return actionable insights with further added value without compromising the confidentiality of the underlying information.
What exactly is meant by added value? The potential applications of ML in the accounting and financial world is practically infinite. On one hand, the entire management can be automated. With the right ML techniques, when we receive a new invoice, we can predict the expense account that this invoice belongs to. Before ML, this process could only be done by an accountant who was in control, remembered the entire accounting plan, and knew what each account was for. Now, this can be an automatic process. Additionally, if we receive invoices or other documents in paper, we can also use ML to extract information about the content, and again, we can automate the accounting process. These two simple examples currently make up approximately 80% of the work done by accountants or Accounting Advisors. The automation of these two tasks alone has already completely changed the working model, making a tremendous impact on the industry.
Management is only the first area within accounting where ML has a large impact. Once you have the accounting information, a very wide range of possibilities appear. The obvious next step is the generation of taxes from this data. However, the process of generating these tax models is usually not a linear process and it depends on the (legal) “creativity” that is applied by humans. Again, here is another example where ML can help humans apply the right criteria that is most satisfactory according to the goal we want to achieve (pay less taxes, improve company’s financial performance, etc.).
Another possibility that is somewhat related has to do with financial forecasting statements. We can predict future data based on past data, for example, we can find out in advance if we will run out of money at some point in time, which will be an insight found by our data, not by our intuitions. Here is where the Accounting Advisors can provide solutions to the companies they support, beyond the company accounting itself. For instance, the right tool can predict a situation where the company will need funding in the short, mid, or long term. Knowing this information, the company can then anticipate the negotiations with a bank to get a loan under good conditions, as the bank probably won’t pressure the company that much at this stage, so the company can get a better deal.
Machine Learning will completely transform the Accounting Advisory industry. Currently, Accounting Advisors spend 80% of their time processing data, which can be done by machines. If ML reduces this amount of time to only 10%, these professionals only need to supervise what the machines do for them, which allows them to use the 70% of their time to focus on other activities that either result in more value to their customers or help them find new customers.
To conclude, by changing this way of working, Accounting Advisors will also have to change the business model and the entire century-old accounting industry with it. Currently, this sector charges for each invoice entered, which will likely become meaningless with ML in the mix. The second big beneficiary of this transformation will be the entrepreneurs themselves. ML allows you to predict all kind of scenarios; today we have just named a few but there are many more. Knowing these situations, entrepreneurs will be able to make smarter and well thought out decisions.