The Future of Finance Analytics

While most companies use analytics in some way, according to the 2020 FSN Future of Analytics in Finance report, only 14 percent of finance organizations are successfully using large volumes of data produced by transactional systems to produce useful business insights.

Fremont, CA: The digital transformation in finance has been going on for many years. The ability to automate manual activities and processes using digital technology has helped fund the transition from back-office processing and monitoring of past performance – to forward-looking forecasting and market analysis.

And while most companies use analytics in some way, according to the 2020 FSN Future of Analytics in Finance report, only 14 percent of finance organizations are successfully using large volumes of data produced by transactional systems to produce useful business insights. Finance teams who have been active in harnessing these data sources are in a position to ask better questions, anticipate more accurately, model scenarios and uncover actionable insights that drive enhanced decision-making.

Operational Data is Often Overlooked

Although several companies have concentrated on enhancing their analytical processes, most of them lack a valuable source of insight. With much emphasis on the Record to Report (R2R) process for generating financial results and the Budgeting, Preparing and Forecasting (BPF) process – data from the Buy to Pay (P2P) and Cash Rating (Q2C) processes are regarded as transactional and often ignored. Appropriately leveraged, these processes can provide useful telemetry and signals about consumer behavior and supplier performance that can expose important business opportunities or risks. In order to provide a full image of the market, data from these and other systems and processes should be combined and matched with financial data to provide actionable information and support decisions that could build competitive advantages.

Information Management Policy is easily overlooked

Many financial institutions are trying to keep pace with the proliferation of emerging technology available on the market. These include cloud-based ERP and Corporate Performance Management (CPM) solutions, advanced analytics, robotic process automation (RPA), predictive analytics, artificial intelligence (AI), machine learning (ML) and more. Although these technologies can be useful, a holistic information technology approach is required to successful organizations. And most of them are far from doing this.