Data science and analytics is top priority for leaders in finance

In finance, data is paramount to success. Six out of ten finance leaders place leveraging data science and analytics for strategic insights and tactical decision making as top priorities for the coming year.

The ability to utilise data analytics and “big data” to achieve a competitive advantage and manage operations and strategic plans ranks among the top issues for board members and C-suite executives worldwide. Data analytics can be applied across three key areas. In terms of planning, it can be used for effective risk profiling, the testing of data via simulation, and statistical sampling. Data analytics can also enhance the execution of audits – providing quick and effective monitoring of continuous controls, keeping watch for indications of fraud, recognising patterns to anticipate future risks, and control simulation.

Unsurprisingly, then, according to Protiviti’s latest Finance Trends Survey, the security, privacy and analysis of data are the top priorities for finance leaders going into 2019. All three top priorities identified have some link with data, with enhanced data analytics highlighted as very important by 62% of CFOs. The paper surveyed close to 400 finance leaders and professionals, including CFOs, vice presidents of finance, and a broad range of finance directors and managers, data is the dominant theme in the finance landscape.

Data is seen as important because it can help to unlock commercial insights, boosting sales, as well as boosting management reporting and decision making, but also make for better internal operations of the finance function, with 53% of respondents seeing data analytics as key for realising process improvement. However, using data analytics effectively means that several pre-requisites need to be in place.

One key area that CFOs and finance leaders are struggling to manage is data quality. As with most other groups, the analysis and reporting that finance delivers to the organisation rest on the quality and completeness of the data available. To this end, data governance is critical. CFOs and finance leaders need to ask if there is a robust data governance organisation in place, as well as who owns the data from different parts of the organisation (for example, companies must know if they have a designated data steward).

Data quality also is improved through master data management – something that can require substantial effort and expense.