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Finance professionals have long been technology pioneers, a fact which they rarely receive credit for. From electronic trading platforms to online payments to cryptocurrency, finance has pioneered digital technology in the workplace for decades.

To move finance forward into the next decade, finance professionals need to focus technology investments on AI-powered automation and new analytics tools and techniques to improve operations, better forecast business performance, and help the organization strategically plan for the future.

Modern finance is built on an analytics culture

Big data has been a buzzword for the past several years, so it should come as no surprise that finance leaders continue to focus efforts on data and analytics programs. In a recent KPMG report, 85 percent of CEOs reported that their CFO’s ability to gather and analyze data was key to profit growth, and in a recent study by Ernest & Young “improving analytics capabilities to transform forecasting, risk management, and understanding of value drivers” was the top priority most commonly cited by CFOs (23 percent).

As finance professionals move into strategic business leadership roles, the importance of having quality data grows, and they must increasingly rely on their technology counterparts to help them drive business intelligence. With more intelligent and powerful cloud computing, big data is finally moving into new areas, helping finance leaders close the books faster, deliver more accurate reporting, and build more intelligent business strategies.

Beyond data analysis, CFOs face another modern-day data challenge: as they take on larger roles within IT and analytics, CFOs are forced to tackle the growing issue of data management. This includes both data storage, as well as monitoring and managing data quality. These critical tasks not only enable CFOs to do their job, they also allow other functions to operate more efficiently. Without data quality control, CFOs and other business leaders risk making decisions based on flawed information.

As data and analytics play an increasingly important role in business, companies—and their CFOs—need to establish cultures of data across their organizations. This means that measurement strategies and data collection plans are the starting point and not an afterthought, as there is a high level of fluency in analytics across teams, and business leaders have access to the data they need, whenever they need it, to make informed strategic decisions.

AI-powered automation streamlines operations

As increasing transaction volumes and ever-changing regulations are making finance more complex, businesses are looking to reduce the costs of the many manual tasks required in bookkeeping and accounting. 53 percent of companies in Deloitte’s most recent Global Outsourcing Survey reportedly outsource tax functions, and 42 percent outsource certain finance functions. For compliance specifically, 56 percent of companies said the main reason they outsourced was due to lack of in-house skills, while 38 percent cited costs.

With the rise of AI, businesses are now turning to robotic process automation (RPA) to help reduce costs, speed processing, improve quality controls, and free up their employees’ time for more strategic work. A recent KPMG study reported that 88 percent of businesses projected a moderate to high demand for RPA in finance and accounting in 2018, while 66 percent reported that automated AI applications would become applicable to their finance and accounting over the next couple of years.

Automation, enhanced by AI and machine learning, can streamline finance operations in many ways and help organizations save money by completing previously manual tasks faster and more efficiently. RPA—artificially intelligent workers — can now be used for many tasks, including digital invoicing, expense management, fixed-asset accounting, conducting general ledger account reconciliation, evaluating customer risk, and auditing expense reports.

Beyond faster speeds and lower costs, automation is playing a larger role in compliance. Automated intelligent systems can review employee disclosures, open accounts, and scan paper statements to flag any trades or transfers for the appropriate level of review. They may also review employee expenditures, particularly on gifts and entertainment, to help identify potential areas of conflict or policy abuse. They can also help businesses manage financial risk through tasks like detecting changes in risk exposure and helping determine the causes for such movement, as well as evaluating customer risk and making recommendations on credit limits or maximum loan amounts.

Companies are finding that digital assistants are reducing operating costs by as much as 80 percent, and a study by Accenture showed that robots will be able to automate or eliminate up to 40 percent of transactional accounting work by 2020.  But this doesn’t mean that automation will be the end of the finance professional. To the contrary, automation, AI, and RPA are elevating the finance function, allowing workers to spend less time on tedious manual tasks and more time deriving higher-value strategic insights for their businesses. These technologies are estimated to recover between 25-75 percent of financial staff’s time, freeing them up to focus on more meaningful work like predictive analytics and performance management.  Before long, today’s manual financial processes will be a distant memory, but automation alone won’t transform finance; successful finance departments will continue to need human oversight and a knowledgeable workforce to help drive strategic business growth.

How is Microsoft helping finance leaders streamline their business?

From streamlined asset management through centralized data to real-time analytics driven by artificial intelligence, Microsoft is helping finance leaders optimize productivity and operate with intelligence.

For more information on how technology is making finance smarter and faster, read Microsoft’s 2019 Finance Trends Report.