Artificial Intelligence in Finance: From Zero to Hero

AI was named word of the year 2023 by Collins Dictionary, as it has impacted our lives in many aspects, including the way we develop financial processes. For a better understanding of the role AI is playing in finance, let’s go back in time to review the different tools that have come along over the years with the aim of improving efficiency and accuracy.

Barter started as an exchange method that quickly required a system to register transactions, as humans felt the need to quantify and keep records of such interactions. At some point in history, these rudimentary systems evolved into the first ledgers, which were certainly manual and based on the then available tools, like pen and paper. For many years, manual ledgers, bookkeeping, and accounting were finance’s main functions: they were used to keep track and standardize, as much as possible, the transactions being performed in companies. Clearly, the more transactions the companies achieved, the more workforce was needed to record them. 

With the access to personal computers in the early 1980s, it seemed obvious that all the financial numbers needed to be digitized. Several companies jumped at the opportunity and developed their own accounting software using the available technologies, like the programming languages Pascal, BASIC and Fortran, and the MS-DOS operating system. In September 1985, MS Excel was launched with its versatility to do everything in the financial world (and other worlds). Amazingly, even after 37 years, MS Excel is still one of the most used tools around the world for finance despite its many restrictions, like the 65,536-row limit that it used to have. 

Later, in the ‘90s, Enterprise Resource Planning (ERPs) came along – with significant  costs for the companies – and proved to be a mandatory tool for the proper administration of companies. Some ERPs worth mentioning are ORACLE, SAP, and NetSuite. For finance and accounting, ERPs meant a significant workload reduction, with the added advantage of having all the information connected and centralized in a single location, simplifying processes, and improving data quality. Nevertheless, not all companies have every ERP module, nor does every ERP software have all the tools required for every company. That’s one explanation of why MS Excel has survived as a parallel tool that complements ERP functions. 

More recently, other tools like robotic process automation (RPA) have been introduced into the financial world by companies like UiPath, founded in 2005 in Bucharest, Romania. These new so-called “robots” helped automize many processes that, even after the use of powerful and expensive ERPs, remained manual, repetitive and time consuming. On the negative side, it was found, not surprisingly, that these robots didn’t adapt to changes in processes and technologies, and high maintenance was needed. They turned out to be the opposite of a definitive holistic solution. 

In parallel to the robots, business intelligence (BI) systems were being developed; one example was Tableau, founded in 2003 in Mountain View, California. These systems helped finance people to extract and display in a colorful manner all the information coming from ERPs and other sources, bypassing Excel, and automating innumerable reports.

But BI is not the end of the financial technology transformation that added significant value to organizations. As of 2023, there are many  finance operations that can still benefit from automation. Despite advancements in the previously mentioned technologies like ERPs, RPAs and BI, complex tasks that involve numerous exceptions still require human intervention. 

This is where artificial intelligence, which had almost ZERO use in finance, comes into play. AI can emulate human logic, drawing on its extensive training data to make decisions and perform tasks traditionally reserved for human cognition. This capability represents a significant leap forward in financial technology, enabling finance professionals to tackle even more challenging and nuanced tasks efficiently.

Furthermore, in many midsize to large companies, financial data is dispersed across various systems and databases, often provided by different vendors. This fragmented data environment poses significant challenges for users who need to access and effectively utilize their data. The lack of intelligence in existing systems further complicates the task of assessing vital data and triggering necessary workflows.

Addressing these challenges, companies like ChatFin are using AI to help those in the finance world. For instance, AI tools offer a conversational user interface, enabling users to query, submit, analyze finance data, and automate tasks with ease. By harnessing the power of AI, finance teams can streamline their operations, gaining the potential to enhance their efficiency by 10 times. Imagine running reports, transforming data, or automating finance tasks through simple messages to AI. This level of efficiency and mobility not only optimizes operations but also addresses the growing talent shortage in the accounting and finance sectors, making  AI the new finance HERO.

The journey of technology evolution is a relentless pursuit of efficiency and innovation in corporate finance. As we embrace these advancements, finance professionals are better equipped to contribute strategically to their organizations, driving growth and success in an ever-evolving business landscape.