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Intelligent Products

Intelligent Products: Making Positive Change for Payments

By Slalom Build

The dramatic acceleration of the electronic payment industry has generated a ton of data. We’re talking about massive amounts of transactional and behavioral information collected across every touchpoint—search, social media posts, conversations with customer service or support agents, and the checkout process itself, to name but a few areas.

While companies have been successful in collecting data, improper setup of their data infrastructure is holding many back from obtaining actionable insights. In addition, despite the increased volume of rich data points, the payments space hasn’t fully reaped its potential. Tedious processes are still inherent in activities such as extending credit to customers, and numerous instances of compliance violations and fraud claims remain.

Let’s look at what is standing in the way of progress and explore how Intelligent Products can benefit payments.

The opportunities for intelligent processing

With an estimated $8.49 trillion total transaction value worldwide for 2022, it’s clear that there’s a considerable volume of information associated with digital payments at this scale. (1) This ever-growing amount of data is far more than humans could ever parse manually.

Artificial intelligence (AI) is better equipped to identify patterns and make predictions at a rate that keeps pace with the volume of data that’s become available. By automating manual processes, employees can focus on solving more challenging and personally rewarding problems. The operational process becomes smoother, and companies are better able to decrease the financial risk associated with human error. AI has been proven to protect data quality, ensure greater compliance, save money, enhance customer experience, and advance efficiency.

Before getting too excited, it’s important to remember that the goal is not to automate the workforce and remove people from it entirely.

Humans & Machines

Humans vs. machines? No. Humans and machines.

When AI supercomputer Deep Blue beat world chess great Gary Kasparov back in 1997, many feared this was the beginning of the end of human dominion over intelligence—or at least board games!

After the match, Deep Blue team chief Chung-Jen Tan said, “This is not about man versus machine. This is really about how we humans use technology to solve difficult problems.” Since then, we’ve radically expanded our understanding and use of AI and machine learning (ML) and found ways to use machines to complement our skills across a wide variety of industries and use cases.

Adoption of AI has been growing steadily and is at 35%, a four-point increase over 2021. Forty-four percent of companies are embedding enhanced intelligence into their current processes and applications. (2) AI has advanced so rapidly that a new generation of innovation has emerged. Intelligent products.

Intelligent products meet increasing demands

Intelligent products are the culmination of technology, intelligent operations, and experience. These dynamic products gather their own data, then analyze and transform it into knowledge that is used to continuously optimize and improve over time. Check out this article for a comprehensive look at intelligent products.

There is no better way to transform outdated payment processes and advance digital transformation than to leverage the power of intelligent products. Intelligent products are adaptive, personalized, and constantly learning. When used for payments, they help carry out time-consuming processes at scale faster, more efficiently, and with less bias than humans.

Several areas where intelligent products are making an impact within payments include:

Establishing smarter financing activities

Intelligent products using real-time considerations based on collected information give companies access to a wider variety of data sources, ensuring credit scoring is more granular, personalized, and nuanced. The result? A more positive customer experience.

Credit policies become more sophisticated with more informed credit decisions, maximizing predicted returns while retaining customer loyalty on a per-user basis. Decision-making capabilities are enhanced to determine whether to provide better pricing or offers to select customers and limit features or financing to others. AI and ML take pressure off employees and ensure staff can focus on what they do best.

Intelligent products also help enable alternative credit scoring through more sophisticated data usage and leverage of additional data points. Doing so sets up organizations to unlock new downstream opportunities and provide much-needed service to the underbanked or unbanked.

Insights gleaned from AI and ML can also empower a company to leverage payment churn to provide lines of credit to small business clients proactively. Furthermore, increased retention is possible thanks to better prediction capabilities.

Predict Future Patterns

Improving fraud detection

Facilitating the rapid analysis of a massive volume of data to better detect fraudulent activity is where intelligent products shine. They lower the cost of manual fraud investigations and increase the velocity of intervention before it’s too late, helping companies discover, investigate, and reduce transaction fraud and money laundering. Intelligent products reduce fake accounts, chargebacks, account takeovers, spam, and payments from identity thieves.

Spending time and resources reviewing problematic transactions is unnecessary since it’s easy to rely on automated predictions and immediately see changes in behavioral patterns or suspicious activity. It’s now possible to perform immediate fraud analysis on real-time payments (RTP) by assessing customer behavior in the moment.

Machine learning makes it possible to engage in active improvements, including setting up reinforcement-learning- assisted honeypots to trap sophisticated attackers. In addition, intelligent products can be set up to automatically take action to quarantine nefarious activity, collect data, and learn future attack patterns.

Reducing false positives and false declines

Related to fraud, one of the primary use cases for intelligent products is preventing false positives or false declines. False positives are the largest area of merchant losses, coming in at roughly 10-15%. (3) This same percentage can be attributed to false declines, which came in at an estimated cost of $230 billion in 2022. (4)

Beyond the economic hit taken for false declines, the impact on customer experience is equally damaging. Frustration leads to lower transaction volume and may result in a customer abandoning the rejected payment method or the merchant who declined the charge.

Ensuring compliance with complex regulations

Intelligent products are shaping the future of payments and creating positive outcomes for businesses. Our collaboration with Australian company Beem is an excellent example of how we built an integrated payment experience that delivers the goods and ensures customer satisfaction.

Together we created a new cloud-native, secure, compliant payment platform using Amazon Web Services (AWS). The app called eftpos QR (eQR) enables customers to scan a merchant’s unique QR code at the point of sale to pay with their digital wallet, redeem gift cards, secure loyalty rewards, and save digital receipts.

  • Processes billions of transactions annually
  • Transaction per second (TPS) rating of 500
  • Lambda P95 response rate of 60ms
  • Incurs only an incremental, usage-based total cost of ownership (TCO)

Are you interested in learning more about how intelligent products can help you achieve greater operational and strategic efficiencies in your payment processes? Download our whitepaper.

(1) Statista Search Department. (October 2022). Digital Payments - Worldwide. [Link]

(2) IBM. (2022). IBM Global Adoption Index 2022. [Link]

(3) The Payments Association. (2021). Using AI Intelligently: Smart ways to use Artificial Intelligence in Payments. [Link]

(4) Insights Magazine. (May 2022). The Payments Fraud Ripple Effect. [Link]

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