Back in 2013, IBM told the world that 90% of its data had been created during the previous two year period. Three years later, it is clear that the era of Big Data is here to stay. What is less certain, however, is what the average business should be doing to take advantage of the situation.
For those of us in the omnichannel payments industry, however, there can be no hesitation. Data science gives us the chance to offer a new standard of payment services to merchants, with solutions that adapt based on systematic analysis of the oceans of key data accrued from the long list of potential sources: from sales channels to public government information to social media data and more.
Merchants have a right to demand solutions from PSPs that use every possible tool to improve revenue and reduce risk. If you are not taking data science seriously, you simply can’t claim to be doing everything in your power to support your clients. So, how does data science fit into the modern payment mix? And what should merchants be expecting from PSPs in the Big Data age?
The power of information
While the potential uses of data in the payments industry are many, two areas in particular stand out as benefiting the most from intelligent data science: security and authorisation. Let’s take the latter issue first.
In the past, a merchant would receive reports back from their PSP with a list of transactions, noting which ones were declined and which ones were approved. No insight was offered into why declines were happening or how they could be prevented from happening again. The results were inflexible facts leaving the merchant with no clue as to how to use them.
PSPs are now crunching the data behind the numbers, breaking down the patterns and motivations of consumers, as well as how this relates to whether a transaction was approved or declined. This way, rather than hand back a long list of complex information, they can return concrete advice on technical tweaks that will eliminate obstacles in the authorisation process.
From a security point of view, data science is equally valuable. By tracking and studying the patterns and activities that surround past fraudulent transactions, we can optimise the processes we use to prevent future fraud with a revolutionary level of efficiency and accuracy.
Data in action
Though the results of data science are compelling, in action it is a rigorous, exacting and time consuming process. That’s why the only way to employ it in your business is as part of a strict monitored and strategic approach. Plus, you need some specialists on board who are passionate about payments and willing to devote hours to extensive data mining.
At Acapture, we have deployed our Data Science Team to work on maximising the revenue of our clients. Through deep analysis, the team identify what card types or banks might be commonly at the root of declined transactions and assess the potential causes.
Then, it allows the merchant to route future transactions differently, so they are more likely to gain acceptance. They can also report back to the merchant with advice on technical changes that is backed up not only by experience but also by a solid, scientific breakdown of their recent transaction history.
As well as improving the chances of legitimate buyers being accepted, data is equally useful to ensure that fraudsters are kept at bay. Since the dawn of ecommerce, PSPs have struggled to strike the right balance when it comes to risk management: keeping things loose enough to protect conversion rates while providing enough protection to eliminate fraud.
By approaching risk scientifically, we can identify customers and track behaviour based on website profiles, device usage, network usage, customer behaviour and more. This makes it increasingly difficult for online scam artists to operate from their traditional hiding places, while guaranteeing that honest customers are rarely locked out by mistake.
Data science may even make it possible to minimise many of the costs that merchants face when handling card payments, which are determined by thousands of complex and everchanging rules. In many cases, we are educating our clients on elements of their payment processing that they didn’t know about. That is the real power of data science – it allows us to tinker with parts of the payment dynamic that were previously off limits. The results? Better authorisation rates, improved security and happier merchants.
As I have already mentioned, data science is not simple. Yet, as the amount of data grows, it will be the PSPs and acquirers that truly understand and utilise information that will take the advantage in the increasingly competitive omnichannel payments arena.
About Nathan Trousdell
Nathan is Director of Strategy & Corporate Development at Acapture, a Payvision company. He works with the founders and department managers across all areas of the firm, including sales strategy, data science and product. He is also responsible for the valuation and analysis of strategic investments and merger & acquisition activity.
Acapture is a global omnichannel PSP whose system features SlicePay for simplified allocation of funds to multiple parties from a single transaction, data science management for improved authorization rates, a one day integration using one RESTful API, consolidated reporting, streamlined reconciliation process and global card acquiring and processing.
This article is part of the exclusive Ecommerce Payment Methods Report 2016, an educational overview of the global payments industry. For more insights into the latest trends in ecommerce and e-payment methods developments please download a free copy here.
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