Digital transformation is fast becoming the next frontier for _Finance leaders who are looking to grow and advance their careers. New digital roles, such as chief data officer (CDO), chief data scientist, and chief analytics officer, are emerging. The digital transformation trend has led to an increased emphasis on data transparency and collaboration across the organization; new tools like artificial intelligence (AI), robotic process automation (RPA), and natural language processing (NLP); as well as a greater emphasis on risk management, cybersecurity, threat intelligence, and data analytics. In response to these trends, we see a growing number of finance leaders launching initiatives around digital transformation—and in some cases even switching careers to focus primarily on this area.
What Is _Finance Transformation?
Finance transformation is the process of changing the way a company manages its financial operations and risk management. _Finance transformation generally includes technology transformation, organizational transformation, and business process transformation. This transformation can happen at the organizational level, but it may also occur at the function level. Organizational transformation usually refers to changes in how an organization is structured, how it manages its people, and how it makes decisions. Business process transformation occurs when an organization changes the way it does work, and technology transformation refers to the adoption of new technology.
Why Are So Many _Finance Leaders Emphasizing Digital Transformation?
As we outlined above, the digital transformation trend has led to an increased emphasis on data transparency and collaboration across the organization, new tools like AI, RPA, and NLP, and a greater emphasis on risk management, cybersecurity, threat intelligence, and data analytics. These are all areas where _finance leaders have traditionally focused, so it’s natural that they’d place an increased emphasis on them in this digital transformation era.
New Roles in the Digital Age
With increased investment in technology and digital transformation initiatives, _finance organizations are increasingly looking to hire new roles that are focused on technology or data. These roles are challenging traditional _finance roles by bringing a new set of skills and expertise to the table. The CDO role emerged in the early 2010s and has gained momentum in recent years as an important role for digital transformation initiatives. In _finance , a CDO is responsible for managing the data lifecycle and data governance across the organization. The CDO role is often supported by a chief data scientist (also known as a data scientist leader or data analytics leader) who leads data analytics teams focused on data discovery, data exploration, and data visualization. These teams are responsible for using data to inform business decisions.
AI and ML in _finance Transformation
Artificial intelligence (AI) and machine learning (ML) are two technologies that are spurring significant change in the finance organization due to their ability to transform data into valuable insights. AI is a technology that mimics human thinking and problem-solving by breaking down a task into smaller steps that a computer can understand through algorithms. AI has been used in _finance for many years to automate low-level tasks across the organization. ML is a specific type of AI that is often used to create predictive models. Predictive models help anticipate future outcomes based on current data. These models are widely used in finance and across many other industries, including healthcare, insurance, and e-commerce. Predictive models are used to forecast financial results, provide risk estimates, identify potential fraud, and prioritize which customers to serve first.
Robotic Process Automation (RPA) in _Finance Transformation
RPA is a type of software automation that mimics the actions that humans typically perform on a computer system. RPA is designed to work with computers rather than humans, and it is often used to replace paper- and data-processing transactions across an organization. _Finance organizations often use RPA to process manual tasks such as reconciliations and calculations, as well as paper-based tasks such as data entry and document scanning. In the past, RPA was mostly used in the back office. But it is now being applied to the front office as well. RPA can be used to send emails, collect data, create reports, or perform any other computer-based task that requires a set of instructions to be followed. In finance, RPA is often used to automate manual tasks. Such as data entry and calculations, thereby freeing up finance employees to work on higher-value activities.
The digital transformation trend has led to an increased emphasis on data transparency and collaboration across the organization. New tools like AI, RPA, and NLP, and a greater emphasis on risk management, cybersecurity, threat intelligence, and data analytics. In response to these trends, we’ve seen a growing number of _finance leaders launching initiatives around digital transformation—and in some cases even switching careers to focus primarily on this area.