Smarter finance with AI-driven automation
They rarely receive recognition for it, but people working with finance and accounting have long been, and still are, technological pioneers. In many ways, the financial sector has for decades, with electronic trading platforms, online payment methods, crypto currency, paved the way for the development of digital technology in the workplace.
Optimization of daily operations
If the technological innovation is to continue into the next decade, everything suggests that it is technology as AI-driven automation and new analysis tools and techniques companies should invest in. These technologies can potentially optimize the company's day-to-day operations, create increased insight into the company's capacity and capabilities and help the company's management with strategic planning for the future.
Collection of large amounts of data, known by the term Big Data, have for many years been a significant conversation topic. And collecting of data has in itself great value, but only when this value is uncovered. Therefore, the subsequent organization and analysis of the collected data is at least as important as the collection and for obvious reasons, decision makers have focus on applications that handle and analyze data.
Collecting and analyzing data
For many financial managers, the ability to collect and analyze data is critical and can be no less than the key to starting and maintaining the business profit growth. Also, enhancing analytical functionality designed to transform and improve forecasting, risk management and understanding what drives business value is a high priority among financial decision-makers and managers.
The right data
As accounting and financiers take greater part in the strategies for the company and thus enter management roles in the company, the importance of having the right quality data presented has become essential. Therefore, it has become increasingly necessary that the business partners who are required to run the company's business intelligence are competent and deliver the right solutions and present the right data. With increasingly powerful and intelligent cloud services, the bulk of data is moved and made available faster, which means that management is more capable of closing accounts, delivering better and more accurate reporting and not least, business strategies based on insight and intelligence.
However, the analysis part is not the only challenge modern business management faces when working with data. Also the increasing problem that concerns the ever-growing challenge with data handling, which includes data storage, monitoring, security and data quality management are challenges to be solved. These often business-critical tasks are of great importance to whether management can perform their work optimally, but also has great significance for other functions to operate as efficiently as possible. In short, without the proper handling of data, business executives will make decisions and develop strategies that are based on incomplete or, in the worst case, incorrect information.
Analysis of data
Since data analysis is becoming increasingly more important for companies, data disclosure becomes a business-strategic starting point rather than merely the basis for after-rationalization. Therefore, it is also extremely important that business executives have access to the data they need when they need it, so that the strategic business decisions are taken on an informed basis. In other words, the Big Data investments first yield real returns when the new insights that have emerged from the data analyzes are distributed across the company's departments, data models with machine learning and artificial intelligence are made and ultimately decisions and actions are taken.
Optimize operations in the company with AI driven automation
Due to the lack of internal competences and significant costs, a large part of the companies choose to outsource some of their financial functions. Also, an increasing amount of transactions and ever-changing rules make the economy administration increasingly complex. Therefore, many companies are striving to reduce the costs associated with the many manual tasks associated with accounting and bookkeeping.
With the emergence and spread of artificial intelligence technology, RPA (Robotic Process Automation) has now become interesting for the companies. RPA can potentially reduce costs, increase process speed, improve quality control and, not least, free up employees' time so they can spend their time on, for example, analytical or business strategic work, rather than trivial and manual tasks.
Automation, strengthened and optimized by AI and Machine Learning, can streamline and optimize the operations of the finance administration and generally free up resources by automating tasks that previously had to be performed manually both faster and with a lower margin of error. Today, RPA, artificially intelligent workers, can be used for a wide range of tasks, including digital invoicing, cost management, accounting reconciliation and auditing cost reports.
Automation of compliance
In addition to automation being able to perform a large number of tasks faster and therefore at lower costs, the new technology plays an even greater role when it comes to compliance. With the intelligent and automated systems, it is for example possible to review information about your employees or to review employee expenses, which can be used to identify potential abuse or conflict areas. Intelligent and automated systems can also help manage and reduce the financial risks associated with assignments, for example by determining the causes of an eventual risk exposure and help to uncover the causes of such an exposure, as well as to assess and limit customer risks and make suggestions on credit limits or maximum loan amounts.
Larger business value
Automating manual tasks and processes carried out by the so-called digital employees can thus reduce business operating costs substantially and will probably in just a few years be able to automate and completely eliminate large parts of the accounting tasks. However, this does not mean that automatic intelligence is the end of the accounting staff, on the contrar. Automation, AI and RPA can lift the finance function and operation and release time and resources, which means that employees can spend less time on trivial manual tasks and instead spend time on, for example, strategic or analytical work, thereby creating greater value for the company. departments as well as a knowledgeable staff that can help analyze data and determine strategies to drive business growth.
Artificial Intelligence in Business Central
One of the companies that invest heavily in artificial intelligence (AI) and machine learning (ML) is Microsoft, for example with Cortana Intelligence and Cognitive Services. Like so many other companies offering business software, they are fully aware that the potential of the new technologies is a critical element of their future services and products.
An example of the outcome of this effort is that at present there are three AL and ML powered functionalities in Business Central and there is no doubt that we will see even more intelligent and automated technology in future releases.
The AI and ML powered features in Business Central are:
1. Product setup assisted by image recognition
2. Delayed payment prediction for sales orders
3. Inventory forecasting
Microsoft has designed the AI and ML features based on a principle of making their applications intelligent and personalize the data processing, which ultimately aims to make the workflows more efficient. AI and ML together have greater capacity than traditional reporting methods and can give the user insight that would otherwise not be made visible. Ultimately, these insights can give companies that use artificial intelligence and machine learning a competitive advantage.