Many experts think that we have now officially reached the age of automation in almost every industry. Starting from Artificial Intelligence to financial robotics we’re headed towards building a strong automatic civilization. Whether it’s beneficial or damaging is up to experts to forecast and up to the global community to decide when the time comes.
Automation has played an enormous role in the ever-expanding world of finance. It changed the way businesses and companies operate and how they are managed today. The automated processes now directly affect the growth and development of the firms. Furthermore, it strongly influences nearly every level of management and position within the companies whether it is CEO, CTO, mid-level manager, specialist, or consultant.
What is Financial Automation?
Simply put, financial automation is a process of automating various financial operations ranging from simply paying the bills to designing robo-advisors. While you can encounter automation and use it in your daily life for depositing your paycheck automatically or managing your savings account, the concept is much more complex and utilized on higher levels within corporations and businesses.
Believe it or not, McKinsey Global Institute suggests that existing utilized technologies can achieve full automation of around 42% of financial activities, while an additional 19% can be partially optimized. In general, what financial automation does for large companies is that it allows the completion of technological tasks without much human intervention. It saves time for various employees for more complex tasks and reduces time and energy spent on monotonous and routine operations.
However, it does not mean that automation involves performing simple tasks only, as it often is used for analytics, self-learning, advisories, and many more programs. For instance, one of the most common uses of financial automation often encountered in various financial markets is trading automation with Forex robots, which is one of the most popular options for traders nowadays. These robots will learn numerous trading strategies, replicate existing trading styles, analyze complex trends, serve as advisory platforms, etc.
There are numerous levels to financial automation including robotic process automation, artificial intelligence, and intelligent automation. Let’s look at each of them briefly.
Robotic Process Automation (RPA)
RPA is a software technology that serves to simplify establishing, implementing, and administering software robots that assimilate human activities when interacting with digitized systems. Software robots can comprehend what is being displayed on the screen, hit the appropriate keystrokes, navigate various systems, identify and extract data, and perform a variety of pre-scheduled tasks. These machines can easily accomplish the tasks much faster and in a more consistent way than humans, since they do not need to go for breaks, don’t get distracted, and don’t make human errors. Furthermore, modern RPA platforms offer integrations within the centralized Information Technology governance and management abilities.
Artificial Intelligence (AI)
Artificial intelligence is placed on another end of the spectrum. In theory, Artificial intelligence is achieved when software uses algorithms or machine learning to make intelligent decisions whereas still adhering to controls. Machine learning algorithms represent the computers’ capability to absorb a continuous flow of data, analyze it for numerous patterns, and provide recommendations for solutions to problems humans cannot even notice, demonstrating vastly improved financial efficiency and expertise.
Intelligent Automation (IA)
Intelligent automation has a wide range of applications that simplify processes, free up resources, and improve operational efficiencies. An automotive manufacturer, for example, might use intelligent automation to speed up production or reduce the risk of human error. IA, sometimes also called cognitive automation, utilizes various automation technologies including the ones we have discussed above – RPA, AI, and business process management (BPM). Altogether they serve to scale decision-making across organizations.
