Data Analytics

Data Analitics

Big Data has become an essential asset for the payments industry players, either merchants, financial services companies, or solution providers. However, more important than data as such, is the way this data is used in order to optimize payment processing, monitor customer behaviour, detect fraud, all things considered for a safe and convenient payments environment.

The industry is aware of the benefits of Big Data complemented by artificial intelligence, more specifically, machine learning, a technology that comes to the rescue when one has to deal with a bunch of miscellaneous data. Quantity matters, but quality matters most, especially when it comes to relevance and accuracy. Systems that rely on AI need relevant data in order to provide the right result, otherwise, the system becomes irrelevant by itself. Fortunately, technological progress has brought innovative opportunities to reach across all the data and turn it into meaningful features. With the help of AI, data analytics are a primary tool to be leveraged for different actionable ways, now and in the future.

Understanding customers’ needs and Improving customer experience

Merchants can create authorization reports with variables of their choice, as well as data reports, for a better customer segmentation. Analytics driven by AI and machine learning algorithms can quickly and continuously learn a customer’s behaviour patterns, building personalised models per user. Once knowing the customers’ habits, a merchant can do so much with this information. They can customize payments methods, provide and improve loyalty programs and more importantly, be flexible even during periods with large volumes of sales. Moreover, in the ecommerce space, for instance, the way Big Data is now handled helps to track delivery times and customer satisfaction levels. Businesses can easily leverage customers’ feedback in real-time and tackle a possible issue. Personalization is also key when it comes to the online page. With AI and ML, merchants can customize the content, pricing, currency, upsells and cross-sells on product pages, and many more.

Fraud detection

Data analytics and AI have been here for a while, but technology must be constantly improved to bring better results. When it comes to fraud, a proactive monitoring of data is now crucial in detecting fraud in real-time. Predictive analytics gather data, connects it across the customers and develops a behavioural pattern. If the pattern changes at some point, it is detected as suspicious behaviour. However, the advancement of data analytics is now addressing an emergent issue: false positives. Merchants are at risk of losing customers when declining orders that only seem to be risky. For this reason, machine learning, which is able to detect potentially risky transactions is complemented by manual review. These aspects are strongly related to risk scoring and profiling which have been improved throughout time. Meanwhile, the rise of hacking bots is the issue that both merchants and financial institutions are currently working on. What’s interesting to see here is that these bots are powered by AI and their good performance also requires data. On the other hand, the ‘counteracting agent’ for this type of fraud are still data and AI.

Exploring further the potential of data and AI

There was a time when Big Data used to have an inhibitory effect, as a huge amount of data is not very useful when one has no idea what to do with it. In the meantime, a lot of research has been conducted in the area of automatic data analytics, until the right technology has been created, powerful enough to analyse information and turn Big Data into smart data. And since online business will focus more and more on customer retention, data will be for brick and mortar retailers just as valuable as it is for online retailers. In fact, AI has offered businesses the opportunity to digitalize their services, and in the future will facilitate digitalization in the offline space.

At the same time, AI has started to become an innovation driver for mobile commerce. Google, for instance, is a reliable data provider that offers multiple sources to merchants with mobile-friendly websites. Therefore, the payments industry should watch this space as well.