When it comes to analytics, finance is often the first department in a company to push for transformation. Business intelligence (BI) and analytics can improve operations and provide the distinct advantages to finance departments.
In this article, we take a closer look at the benefits of BI and analytics in finance. There are at least 4 key reasons why successful a CFO should implement BI in the daily work of the finance department.
Reason #1: merging data from various sources
As the amount of data grows, we can no longer rely on Excel files to make decisions. To build effective forecasts, leaders need as much information they can get. This information must be updated regularly to reveal new insights and opportunities. Otherwise, the old information may lead to wrong decisions.
All this data comes from various information sources. What BI tools are great at is extracting data from different places. Be they text-based documents, databases, cloud, CRM systems, R scripts or JSON files. Upon extraction, BI tools can easily put them together in a data model for further examination.
In the past, finance departments often merged dozens of Excel files. Errors easily happened when an old copy was merged or re-merged by accident. Modern BI tools have solved this problem. Power BI, for example, can automatically draw information from folders, one only needs to drop the right file in a folder.
Reason #2: working with large files
File sizes grow quickly. It’s always been a problem for finance professionals who knew that Excel, for example, cannot handle more than a million rows. Even while working with a few hundred thousand rows, it’s challenging to use some functions, such as the lookup and match functions. Computers often freeze, work progress can get lost when not saved, and nerves are racking. This was the reality of the finance departments not long ago.
BI tools have modern data compression engines that effectively reduce the file size. Power BI’s Power Query, for example, works on the M code and uses the table and column level calculations instead of rows. This allows the program to handle large amounts of data, as much as 10GB, making it an effective formatting and storing tool.
Reason #3: using AI for better and faster analysis
Being able to work with large files is only the first step. Once all this data is loaded then it ought to be examined, modified, and analyzed. Even the smartest human analysts will struggle with massive volumes of transaction, especially when a job that needs to be completed is menial.
AI-powered BI tools can be an effective solution to this. They can efficiently process very large amounts of financial information and extract useful insights from those documents. After the useful information is extracted, human analysts can examine the areas, in which the human brain can do a better job. This kind of teaming up between finance teams and AI is the way of the future.
Reason #4: better fraud monitoring
Closely related to the previous point is the use of AI in solving fraudulent activities. Fraud monitoring may have not been the primary concern for CFOs in the past. However, with the increase of fraudulent activities, leaders ought to start paying more attention to this issue.
Fraud detection is essentially the process of identifying, classifying, and evaluating unusual information in an organization. In the finance department, it often involves the tracking of abnormally low or high numbers whether written purposefully or due to a mistake.
BI tools can be used as fraud monitoring solutions. One way would be to get all relevant datasets into a BI software, analyze data and reveal all essential trends. After that, take a closer look at all the “unusual” cases, identify patterns, find fraudulent activities and then establish rules to catch future cases.