by GLENN Hopper
The historical view of the Chief Financial Officer as a fastidious bean counter detached from the nuances of operational divisions is as far removed from the reality of modern corporate finance as paper ledgers and mechanical calculators.
With the continued evolution of financial and accounting software, the nature of finance has shifted from transactional and historical to real-time and analytical. CFOs are still responsible for traditional finance activities like FP&A, audit, compliance, and treasury management, but in the era of Big Data, effective CFOs additionally must become masters of business intelligence.
The key to meaningful business intelligence is the effective use of data, which has moved out of departmental information silos and into the operational realm. Once considered little more than a byproduct of a company’s business processes, data has become fuel for innovation and improvement.
In order to make effective use of company data, the modern CFO must understand the fundamentals of her company’s business. She must be more than a financial specialist, becoming an expert at using predictive insights to harness company data to drive corporate decisions.
Finance departments have a distinct view into all aspects of the company, which puts the well-informed CFO in a unique position to combine business operations knowledge with financial insights. Further, the adoption of data analytics is a natural fit for the finance department, where analysts are accustomed to finding trends, patterns and meaning in numbers. Just as in financial analysis, business analytics reveals trends, risks and opportunities. With more information, analysts can use data to further refine not only financial models, but also to identify risk and regulatory issues, increase productivity and efficiency, and evaluate new business opportunities.
Deep Finance charts the course for modern CFOs to take the lead in digitally transforming their companies by streamlining back office processes, digitizing operations, and intelligently using customer and transactional data to increase efficiency and harness the predictive powers of artificial intelligence.