FINANCE & BANKING

The CFO’s New World: Big Data, Analytics, AI, and the Finance Professional

Artificial intelligence (AI) and robotization will affect many elements of the human endeavor. That includes the way humans interact, how work is done, and what work need not be done by humans.

These advancements present an opportunity for finance professionals – provided they embrace these tools.

Human accountants may not be required at all in the once-major role that they traditionally played in organizations – inventory receipts, issues, stock-takes, and valuations

Businesses will still have roles in which insight, transparency, stewardship, and ethical corporate conduct are valued, and strategic finance professionals can fill these roles. Risks remain, but mainly for those who fail to appreciate the new tools and get left behind.

Finance professionals must live with this changing, disruptive, but opportune environment and explore opportunities whereby the finance function itself can harness the power of big data and analytics to significantly transform itself and the organization.

The transformed finance

Transformation can manifest itself in a number of ways across the entire finance spectrum, from the transactional space of the finance pyramid to the top end of knowledge and value generation. The two figures below contrast the traditional finance function and the emerging future.

In today’s age of digitization, there is a major shift in the way transactional data are captured, recorded, verified, and converted into information. All of this is about to change even further with the advent of technologies such as blockchain and distributed ledgers.

Inventories and inventory transactions are another case in point. Inventory receipts, issues, stock-takes, and valuations are today automated and digitally tracked using radio frequency identification (RFID), which can be reflected directly as transactions in ledgers and financial statements.

Human accountants may not be required at all in this once-major role that they traditionally played in organizations.

Add to this mix all the other data – customer, supplier, human resource, as well as myriad external data. The end game is that massive volumes of organizational data can be accurately captured more quickly and much more efficiently. The challenge now is deriving value from all these data.

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