AI for Operational Efficiency and Cost Reduction in Payments

Financial institutions are beginning to harness the power of artificial intelligence to cut costs and transform payment system performance. Technology processes and results that once seemed far off are now being realised. In fact, studies show that AI and Big Data technologies can automate 70% of data processing, and 64% of data collection activities—and that’s only the beginning.

Imagine a scenario where merchants are watching their profits soar, with some achieving cost savings of up to 55% through AI-driven intelligent payment routing. And they’re seeing these benefits while enjoying reliable and stable technology, fast processing times and high authorisation rates. 

As part of Rapyd’s series, Future Ready: The Guide to AI and Payments, this article explores the AI revolution in cost reduction and operational efficiency by redefining core financial operations. 

Streamlining Operations

The number of manual tasks in payment companies is unsustainable given today’s AI capabilities. Compliance, risk operations, and transaction monitoring still require hours of manual work but can be done in minutes or seconds with AI tools available right now. 

AI isn’t just a buzzword for optimisation. It has the ability to automate repetitive processes and significantly reduces time, cost, and errors for online merchants. 

Rapyd’s CEO, Arik Shtilman, underscores the tremendous impact AI can have on back-office operations and broader financial services in a recent interview with FXCintelligence. 

“One tremendous value to Rapyd and our partners is the ability for AI to reduce the operational overhead that exists in payments and financial services.” By automating these traditionally manual tasks, Rapyd, and the broader fintech industry, can streamline operations, save significantly on labour costs, and reallocate resources to higher-value activities.

Arik explains, “We [Rapyd] took a task that used to be done in three hours and turned it into a one-minute task, and it’s not something you could have done before the AI that is available these days.” This is a game changer for any company that needs to scale. The long-term result will be “unprecedented profitability,” as AI-driven processes will let financial services companies grow without matching headcount increases at every step.

A recent report by PWC notes, “making big leaps (such as new business models) is only one source of game-changing AI value. The other is the cumulative result of incremental value at scale: 20% to 30% gains in productivity, speed to market and revenue, first in one area, then another — until the company is transformed.”  These incremental gains are precisely what the fintech industry can benefit from. 

Financial services infrastructure companies are now able to deliver more value for merchants and partners through: 

• Faster onboarding and time to revenue
• Higher authorisation rates
• Better customer experiences    

Balancing Automation and Oversight

While AI drives efficiency, oversight remains critical. As Dr. Stiene Reimer, payments and AI expert at Boston Consulting Group shares in a recent Rapyd interview: “AI systems require regular audits and human oversight to ensure they remain ethical, unbiased, and compliant with regulations. Blind reliance can lead to unintended consequences.”

Productivity and Labour Cost Savings

AI cuts costs and enhances productivity by automating manual tasks such as data entry, dispute resolution, and compliance monitoring. Research from Nielsen shows a 66% increase in employee productivity with AI, while Netsuite reports that organizations using AI support process payments 81% faster.

Benefits of AI-Driven Automation

• Labour Savings: AI reduces reliance on large teams for repetitive tasks, enabling businesses to allocate resources strategically.
• Predictive Analytics: By forecasting transaction volumes and cash flow needs, AI helps businesses plan proactively.
• Improved Accuracy: Automation reduces errors, enhancing operational reliability.

The Risk of Over-Reliance on AI

Despite its advantages, over-reliance on AI poses challenges. AI systems require high-quality data to function effectively, and incomplete or biased data can result in inaccuracies.

Key Risks to Address

• Algorithmic Bias: Ensure AI models are trained on diverse and unbiased datasets to avoid unfair outcomes.
• Human Oversight: Implement checks and balances for high-value or complex transactions to prevent errors.
• Regulatory Adaptability: Regularly update AI systems to comply with evolving legal standards.

Compliance with the European AI Act

The EU Artificial Intelligence Act applies to all AI systems deployed within the EU, including systems developed by non-EU entities, with extraterritorial reach comparable to GDPR.

• Risk Classification: Familiarize yourself with the Act’s four risk categories—Unacceptable, High, Specific Transparency, and Minimal—focusing on obligations for high-risk systems like KYB/KYC and biometric monitoring.
• Technical Compliance:
  • Prepare comprehensive technical documentation in line with Articles 8–15 of the Act.
  • Stay updated on and adhere to EU technical standards as they evolve.
• Appoint Representatives: Non-EU companies must designate an authorised compliance representative within the EU.

Operational Strategies:

• Conduct Risk Assessments: Evaluate AI systems to identify risks and compliance requirements, ensuring transparency and human oversight.
• Engage Regulators and Standards Bodies: Maintain dialogue with EU authorities and participate in consultations to stay ahead of regulatory changes.
• Leverage EU Resources: Utilise grants, workshops, and industry collaborations to reduce compliance costs and foster innovation.

Ethical AI Development:

• Prioritise Fairness and Transparency: Align AI systems with ethical standards, particularly in critical areas like hiring, credit scoring, and fraud detection.
• Foster AI Literacy: Implement training programs to enhance workforce understanding of AI compliance and governance.

Cost and Competitive Considerations:

• Support SMEs: SMEs should use EU programs and partnerships to mitigate high compliance costs.
• Adopt Scalable Solutions: Partner with vendors offering compliant AI technologies to streamline integration and minimize disruption.

AI is going to stabilise at a certain stage, and you’re going to have AI-related costs, but the ability to do things dramatically faster and pay significantly less is a big game changer. By adopting AI strategically and ensuring its ethical implementation, businesses can harness its full potential, achieving greater resilience and success in an increasingly complex global market.