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Fintech Fridays: Introduction to Autonomous Finance

What is Autonomous Finance?​ Autonomous finance has become an important metric in the measurement of business success, especially over the COVID-19 pandemic where administrative and manual tasks were made difficult. In fact, research by the State of the Connected Customer shows that 68% of customers held higher expectations for companies’ digital capabilities. In addition, 59% of them raised their standards for customer service and 66% expect companies to cater to their personal needs. So what is automation in finance? Simply put, autonomous finance uses artificial intelligence (AI) to deliver personalised and optimised experiences to customers in finance. Through the use of artificial intelligence and machine learning, like specialised softwares, it aims to reduce repetitive manual administration tasks, such as bank reconciliation, credit control and expense management from employee workloads. Benefitting different stakeholders like customers and firms, this article will further explore the role and implications of automation in finance. Role and Examples of Autonomous Finance Creating a much more efficient, effective and smarter finance, autonomous finance will aid an array of avenues and stakeholders within the industry. In terms of businesses, autonomous finance has helped with facets such as: Reduction of error due to the decrease in manual data entry tasks, this is as the finance system integrated synchronises critical data between databases, thus reducing risk of human error. Moreover, increased speed in processing financial data, through automated workflow approval software, subsequently helps to decrease fraud and credit risk and improved decision making due to more efficient reports as a result of software and data analytics. In addition to general business operational help, it helps firms as they are able to understand their customers better thus allowing for competitive edge and advantage over competitors who aren't fully equipped with autonomous features. On the other hand, In regards to the benefit to customers, with increased AI, it will help in aspects like quicker more proactive help and along with simplicity for the user, these are through features like customer support chat bot/boxes. The algorithm-driven approach will be able to avoid dissatisfied users by saving time and money as the software will be able to understand needs, behaviours and goals, thus optimising help.

Implications of Autonomous Finance Despite the plethora and only increasing advantages of autonomous finance within an industry and a firms day-to-day operational work, the disadvantages associated with this are the significant initial costs for firms who are switching to autonomy, although in the long run the costs will be significantly less, the initial costs of implementing database and new algorithms for personalised services is costly. This factor therefore may prevent some finance companies from going for this big expensive model. Furthermore, although the AI works flawlessly with faster results, its accuracy depends on the algorithm it works on. Therefore, an improper algorithm or command may bring unnecessary errors and wrong results which is a huge implication and threat of autonomy.

The views expressed within this article are those of the authors and do not represent the views of the Finance Student's Association. All images and references in this article are for fair and educational purposes only. The content in this article is not intended as legal, financial or investment advice and should not be construed or relied on as such.

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