Harnessing AI’s Potential to Transform Payment Processing

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Recent advancements in artificial intelligence (AI) have sparked a technological revolution that promises to transform numerous industries and areas of society. From healthcare to education to transportation to security, AI can quickly change how businesses operate and succeed. Nowhere is the potentially transformative power of AI more evident than in the world of payment processing.

Financial institutions already leverage machine learning (ML) algorithms and predictive analytics to reduce operational costs and increase efficiency. AI advances are also helping institutions strengthen fraud detection, enhance transaction processing efficiency, and improve customer experiences through personalized services. For all of AI’s advantages, there are also risks that, if not dealt with, could lead to AI advancements doing more harm than good by putting data at risk, creating compliance issues, and even making the customer experience worse instead of better. This is why it is imperative for the payment processing industry to strive to understand AI’s ever-evolving benefits and risks while developing a comprehensive strategy to unleash its full potential.

For example, a recent global survey of senior payment professionals indicates that AI and ML use cases are growing rapidly in several areas (Figure 1), including fraud detection, customer service, chatbots, virtual assistants, and risk management and compliance.

Redefining the Future of Financial Transactions with AI

There are many use cases that show how AI increases the speed and convenience of payment processing. For instance, Apple Pay now offers biometric authentication, which uses AI facial recognition and fingerprint scanning to authenticate users. This enables mobile payment customers to use quick and secure authentication without remembering passwords or PINs. Similarly, Apple Pay’s competitor, PayPal, uses AI for real-time fraud detection, employing ML algorithms to monitor transactions for signs of fraud and ensure that customers’ financial information remains secure. Additionally, AI innovations are transforming payment processing in the following ways:

Figure 1: How AI is Being Used in Payment Processing, results of Edgar, Dunn, & Company 2023 Industry Survey.

Personalization and customer experience: AI-driven analytics provide personalized payment experiences by analyzing customer behavior and preferences.
Operational efficiency. AI automates operational overhead by delivering efficient customer service (via chatbots), automated alerting, and monitoring.
Risk management. AI models can accurately assess credit risks and financial stability by analyzing vast amounts of data, including non-traditional data sources.
Regulatory compliance. AI helps ensure compliance requirements are met with evolving regulatory requirements through transaction monitoring and faster report generation.

Another example of AI’s role in the payment processing industry is at Walmart, which uses AI to create an omnichannel shopping system that integrates payment processing across online, mobile, and in-store channels. This unified shopping experience allows customers to use consistent payment methods no matter how they buy. Meanwhile, Google’s Assistant leverages AI to let users make payments through voice commands. While the rewards of AI adoption are high, it’s crucial for companies to realize that risks come with those rewards.

The Risk-Reward Ratio of AI

One issue is AI systems rely on massive amounts of data, including sensitive data, which can lead to data breaches, identity theft, and compliance issues. In addition, AI algorithms trained on biased data can perpetuate those biases. Making matters worse, many AI systems lack transparency, so the bias may grow and lead to unequal access to financial services. Another issue is the potential dependence on outside vendors, which is common with many AI technologies. Giving an outside vendor access to a private network can lead to compliance issues and security attacks.

The MOVEit Transfer data breach in May and June 2023 exemplifies what can happen when an outside vendor is given system access. In that attack, MOVEit Transfer, a widely used file transfer software developed by Progress Software, suffered a zero-day vulnerability exploit. The breach affected hundreds of organizations and potentially impacted millions of individuals, exposing a significant amount of sensitive personal and financial information, including social security numbers and more.

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While this attack was not directly against an AI system, it still emphasizes the risk organizations face when relying on outside vendors, including those offering AI tools and systems.

Reducing the Risks of AI in Payment Processing

To reduce the current risks associated with AI and safely unleash its full potential to improve payment processing, it is imperative for organizations to take a multi-layered approach that includes technical safeguards, organizational policies, and regulatory compliance. For example, to enhance data privacy, organizations can implement strong encryption protocols for data when at rest and being transmitted. Another positive step is to implement strict access controls, such as role-based access controls (RBAC) and multifactor authentication (MFA), to limit sensitive data access. Companies can also reduce AI risk by performing the following tasks:

Regular audits. Conduct regular security audits and vulnerability assessments to identify and fix potential security gaps.
Diverse training. Use diverse and representative datasets when training AI models to minimize the risk of bias.
Human oversight. Ensure humans are involved in reviewing AI decisions, especially when the outcome has a significant impact (for example, when denying a transaction).
Regular updates. Continuously monitor and update AI models to adapt to new patterns and threats and meet regulatory requirements.
Simulated attacks. Regularly test AI models against adversarial attacks to identify and address potential weaknesses that fraudsters could exploit.
Fraud detection. Implement AI-powered fraud detection tools that use multiple methods, like anomaly detection and behavioral analysis, to identify potential threats in real time.
Due diligence. Perform thorough due diligence when selecting outside vendors, including assessing their security practices, compliance, and track record.
Staying informed. Keep updated with evolving regulations and standards related to AI and payment processing.
Ethical guidelines. Develop and enforce ethical guidelines and practices while building AI solutions to ensure fairness, transparency, and responsibility.

Risk Mitigation Is Key to Unleashing AI’s Full Potential

As AI grows in popularity and capabilities, it is vital for organizations to recognize the risks associated with the new technology and take steps to reduce those risks while still establishing an environment that promotes innovation. Organizations that prioritize AI integration and build a protective framework will best position themselves for long-term success. This is not the time for companies to charge headfirst into change without a plan. Instead, companies can perform due diligence and cultivate a safe and responsible AI environment that allows them to minimize risk and maximize the benefits they receive from their AI adoption— like streamlined transaction processing, reduced payment processing costs, tailored customer buying experiences, and fewer fraud and compliance issues.

About the Author: Ajinkya Ghadge leads engineering teams at a top tech travel company, overseeing fault-tolerant payment services processing more than $100B annually across 155 countries. He previously helped develop an AI marketing platform for Amplero, Inc. (now Curinos), optimizing customer lifetime value for global brands. Ajinkya also has experience leading robotics research initiatives funded by the National Science Foundation. Connect with Ajinkya on LinkedIn.