We who have been active in the payments industry have long sat at the crossroads of vast amounts of valuable transactional data – everything it seems touches a payment transaction. According to CapGemini and BNP Paribas, digital transaction volume (“non-cash transactions”) will top 725 billion by 2020, representing a gross processing value of USD 5.4 trillion. This transaction data is routinely appended with priceless information on products purchased, marketing programs, consumer preferences and geolocation along with mobile or computing device information.
Payment data – the 12-30+ fields of an authorization request string or settlement message – is the essential “truth data” in our digital world - where the path to purchase successfully ends with a decision to buy. And with purpose-built applications of business intelligence – specifically, machine learning algorithms – Merchant Service Providers (MSPs) and their merchant portfolios and ecosystem partners can all realize enormous benefits in the areas of customer retention, revenue growth, financial management, and a host of other operational improvements.
Global Digital Transaction Value – 2021
@Statista©
Despite managing and facilitating these constant streams of valuable data, the payments service provider industry has historically done a poor job of mining this information on behalf of customers and partners. With the exception of fraud management and chargeback operations, Merchant Service Providers (MSPs) have neglected the clear opportunity to leverage payment data to develop business intelligence solutions for themselves or their merchant portfolios.
As an industry, our product development roadmaps are constantly jammed with competing priorities – adding alternative payment options (APMs), PCI/DSS compliance, mobile SDK updates and (of course) continuous compliance with processing and scheme mandates. Real, actionable business intelligence capabilities are always on the wish list – but somehow don’t make the cut, year after year.
In the MSP’s hierarchy of needs, analytics often is categorized as a “nice-to-have” or is deferred to accommodate a new APM. Yet real business intelligence benefits, delivered through machine learning-powered algorithms, can and will be a game changer. Meaningful insights, automated decision-making and predictive modeling derived from payment data can be delivered across multiple dimensions of the MSP value chain:
Payment Operations – transactional performance optimization, recurring billing optimization
Financial Reconciliation & Automation
Fraud and Risk management
Portfolio Management – structured effectively, data from payment operations
Revenue drivers
Marketing Effectiveness
Segment Benchmarking
How do we get there?
There are several critical challenges in leveraging payments data for actionable business insights and business benefits:
Creating flexible, scalable data models
Distribution and utilization of data
Harnessing the power of Machine Learning
The fundamental challenge to harnessing the power of payment data is the creation and maintenance of flexible, scalable models. Normalizing data, which is the process of combining payment data into ‘like-minded’ profiles from different payment types, processing networks and/or other systems, is a massive undertaking. Refine the data too much, and it becomes too generic and not insightful enough. Be too lax on reconciliation, and the data becomes unruly and impossible to manage and utilize effectively.
The second challenge we face is providing access to and distribution of the data models: MSPs will need to utilize some method of distributing these insights to hundreds, thousands or perhaps tens of thousands of users. In addition, a purpose-built payment BI platform has a library of API interfaces designed for internal operations. Pre-configured solutions designed specifically for the payment industry, along with the flexibility to be customized, will save MSPs enormous amounts of time, money and headache versus a do-it-yourself approach and working with a generic BI solution.
Finally, harnessing this data to optimize and automate business operations is where the real value is delivered. At Control, we’ve been researching how machine learning can help MSPs and their merchants increase sales. For example, Control’s intelligent engines can help determine which promotional and product mixes generate the highest sales potential. We help organizations to leverage data through machine learning to determine which payment processors and payment types generate the highest authorization success rates and we can automate reconciliation of bank interfaces with payment sales history.
Global Digital Commerce Users – 2021
As the migration to digital payments accelerates – more than 2 billion people will be shopping through some form of a digital interface by 2019 – Control has embarked on a journey to become more than just the BI engine for the payment service industry. Control is building the intelligent operating system for digital commerce. Business Intelligence for the payments industry shouldn’t just be limited to insightful charts and graphs (we have those too!) – the opportunity that Control now provides to MSPs and merchants is the ability to leverage payment data to make operations more efficient, deliver more value to merchants and their consumers, and ultimately mine the digital gold that is flowing untapped through the veins of merchant payment systems.
About John McDonnell:
John McDonnell, Control CEO is a long-time payment industry executive and investor and has served in operational and board roles with start-ups and established companies including TNS, CyberSource, and Visa. He shares his thoughts on why and how payment data is becoming business intelligence gold—and how analytics are a must-have in the competitive arms race that is the payments industry.
Control Inc. is a provider of business intelligence (BI) solutions powered by machine learning. Control’s data analytics platform has been purpose-built specifically for the merchant service provider (MSP) ecosystem. Founded in 2014, the Control platform maintains integrations and partnerships with leading merchant service providers such as Stripe, Square, PayPal, iTunes and Authorize.net. More than 40,000 merchants have been connected to Control.
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