Companies like Google and Tesla are engaged in an arms race to control the future of AI. Not only is this new frontier the engine that will drive their respective companies, it’s changing the face of almost every industry—including the payments ecosystem.
In the years since I co-founded eMerchantBroker we’ve seen this nascent technology start to affect all parts of the payments chain. Huge investments are being made in developing the different aspects of AI to optimize how we do everything from exchange payments to detect fraud to support our customers.
The next few years will see an acceleration in developments that will alter how payment companies large and small operate their businesses. Some will be left behind. Others, those at the leading edge of the wave, will separate themselves from their competitors and emerge as industry leaders.
This is especially true in the high-risk merchant processing side of the industry, where the potential for fraud and high levels of chargebacks is rampant. Those high-risk merchants who take advantage of the growing suite of AI driven tools to reduce risk while providing a better customer experience are the ones who will thrive.
Investment in AI is growing every year
According to a CB Insights annual AI funding report, funding in AI start-ups increased from just under $600 million in 2012 to $5.021 billion in 2016. This tremendous growth is spurred by the promise for radical change that AI brings to most industries—including the payments industry. It has the potential to streamline the payment chain, reduce fraud, improve customer service and optimize risk assessment—all key success criteria for companies in the high-risk merchant space.
What is AI?
AI can be generally described as the ability of a machine to exhibit human-like intelligence—to make decisions like a person, only faster, and after considering a much greater volume of data. It is commonly used in smartphones, reservation systems, medical diagnosis and, of course, finance. It makes possible greater efficiencies, faster processing and almost complete accuracy.
Types of AI
Today’s Artificial Intelligence research centers on several key technologies. For the high-risk merchant processing industry the most important include: Machine Learning, Natural Language Processing, Verbal and Vision Recognition, and AI bots.
Machine Learning (sometimes called Adaptive Learning) is crucial to the high-risk processing industry’s ability to detect and respond to fraud. Generally speaking, Machine Learning describes a process by which a software model is constructed and vast volumes of data are compared against it. Learning algorithms enable the model to evolve in response to changes in the incoming data.
For example, financial services companies develop Machine Learning models with rules that outline typical fraudulent activity. The software can review data as it comes in and flag patterns that match the fraud model—indicating the transactions should be investigated. As more and more transactions and patterns are examined, the model can develop itself based on learning algorithms.
Such Machine Learning models can also help high-risk payment companies optimize product offerings, detect money laundering schemes, and perform online risk management.
One example of how machine learning can help the high-risk merchant industry combat fraud is Simility’s introduction of a new AI-based fraud prevention platform. The company’s Adpative 3-D Secure software uses Machine Learning to create rule-based models that can evaluate each transaction in real-time. The AI looks at device fingerprinting, behavioral analytics, proxy filtering, and geolocation to identify high risk transactions. And, because of that AI model, Simility is able to ask for secure authentication only for truly high-risk transactions where fraud could be present. This makes the payment process easier for customers, while offering chargeback protection for merchants.
Vision Recognition (VR)
Vision recognition technology is a breed of AI that allows the software to identify objects. In the high-risk payments industry this is particularly applicable to fingerprint or facial recognition as second level authentication methods. The technology enables customers to easily make mobile payments and provides security from fraud at the point of sale. Apple Pay uses this type of AI to secure POS payments by requiring fingerprint ID for each iPhone or iPad transaction. Flint and Square use the technology to allow merchants to accept payments on their mobile—using the phone’s camera and VR capabilities to confirm that the card information being processed is legit. In the high-risk processing world, VR is important because it’s authentication capabilities reduce chargeback rates for companies targeted by fraudsters.
Natural Language Processing (NLP)
NLP is already in widespread use in a number of industries. It is an AI technology that allows a machine to understand spoken commands or questions. Among the most well-known applications using NLP are Apple’s Siri and Google Translate. In the high-risk processing space NLP is being used to reduce customer service costs by taking customer questions without human interaction. As well, NLP is being used by Apple to allow iPhone users to initiate payments using voice commands. This reduces customer friction and makes the sales process easier.
How are AI bots impacting the high-risk payments industry?
AI bots are kind of a hybrid piece of software. They are apps that present the appearance of being human—in that they can understand and answer customer questions for instance—while being completely automated. They combine NLP and Machine Learning code to present effective interfaces that can handle thousands of interactions at the same time, rather than the one at a time limitations of human customer service reps.
AI bots used in chat software, messaging apps, and virtual assistants are changing the face of the high-risk payments industry. They enable better and cheaper customer service, and streamline the payments process.
They allow customers to make direct payments without leaving their preferred social media platform. For instance PayPal can integrate with Facebook Messenger, Siri and Slack—meaning you can actually initiate a payment to a co-worker just by typing in a command in Slack. And, from Messenger or Slack, it’s possible for people to use bots like Hipmunk to find, book and pay for hotels, flights and car rentals.
AI bots also make it possible to make payments via text messaging. The Mypoolin app has a mobile payments bot that lets you text an instruction to transfer money from your bank account to a phone number—enabling you to easily make payments to people in your contacts list.
Financial services firms are using AI bots to create awesome client experiences. The bots allow customers to easily monitor their spending, check account balances, make better financial decisions and pay off debt. Mastercard is developing an AI bot called Mastercard KAI that lets consumers make payments, manage finances and shop from Facebook Messenger.
In the high-risk space, AI bots are a boon because they can replace human service reps in handling customer questions and complaints. They speed up the service process and create significant savings.
The high-risk merchant processing industry is evolving. Adoption of AI solutions for improving the customer experience and reducing fraud and chargebacks is improving efficiency and profit margins. Those merchants and payments companies who are quick to adopt the latest AI solutions are more likely to succeed in the new, automated business environment. Those high-risk businesses who ignore the changes reshaping the industry run the risk of being left behind by their more nimble competitors. In an environment where competition is increasing and margins are tightening AI provides high-risk companies new opportunity to evolve and grow.
Electronic payments expert, Blair Thomas, co-founded eMerchantBroker in 2010. His passions include writing/producing music, and travel. eMerchantBroker is America’s No. 1 credit card processing company, serving both traditional and high-risk merchants.
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