'It is a capital mistake to theorize before one has data. Insensibly one begins to twist facts to suit theories, instead of theories to suit facts.'
But using this data wisely would increase insight into internal policies and processes while providing a better understanding of the trends, behavior patterns, etcetera. This insight could then be used to increase efficiency and profitability and to prevent fraud.
In order to get the most out of your data you need to determine in advance what you want to do with it (use it for marketing, fraud prevention, sales opportunity improvement, etc.), how you want to use it (what kind of tools and skillsets are required) and how you align the data with your processes (the flow of your data should be in line with the value stream).
What do you need to use your data better?
Data quality. Data that is complete, accurate, valid and timely is essential for making the right decisions. To do this right, start at the source. The moment data is entered (manually or automatically), it is essential to have the proper controls in place and to make sure the data fits the definitions and formats. Bad data can interrupt the process of detecting fraudulent activities from external or sometimes internal origins. There are a multitude of data quality tools available including from companies like SAP, IBM and Informatica. But the key to good data management is not the particular tool, but in having the right people and processes.
Analytics. Reliable, adequate and timely data is a first step. Knowing how to properly use, interpret, and put the data into action is the next one. Effective insight comes with the right set of skills and education. In order to detect fraud the right set of statistical, IT, regulatory, financial and payment knowledge is essential. GlobalCollect customers have a tool we call Elevate, designed specifically to analyze eCommerce payments and chargebacks.
- Executing on knowledge. Next you need to turn knowledge into practice. Don't fall victim to big reports with many graphs, tables and figures that just sit on some managers’ desk and are forgotten.
- Integral data strategy. In order to properly integrate data analytics into day-to-day procedures, an overall data strategy needs to be adopted. All branches of the business need to be fully aware of the impact and potential of the data they are working with. It needs to be a key element of their everyday business.
After having established these aspects, you need to maintain the “data-mindset” among the people involved with all the processes. Staff needs to be trained and measured in order to ensure continuous improvement. This will create a competitive advantage and will further increase the profitability of your company. Fraudulent activities can be detected early, thus reducing costs from reputational loss or direct losses.