The Evolution of the Payments Industry: Embracing AI and Machine Learning
By Roenen Ben-Ami, Chief Risk Officer, Justt
The payments industry is on the cusp of undergoing a significant transformation.
The catalyst for this change? Artificial Intelligence (AI) and Machine Learning (ML).
As individuals navigate through a digital first era, these technologies are becoming integral parts of our everyday lives, and the payments industry is no exception.
Historically, the payments industry has been somewhat slow to adopt emerging technologies. This hesitation stems from a variety of concerns, including regulatory compliance, security risks, high implementation costs, and the challenges of widespread adoption. The industry operates within a complex regulatory environment, and any new technology must meet stringent standards to ensure secure and compliant transactions.
Not to mention that, the cost of implementing new technologies can be prohibitive, especially for smaller businesses. There's also the challenge of adoption; for a new technology to be effective, it needs to be widely accepted by consumers and merchants alike. Despite these hurdles, the industry is recognizing the immense potential of AI and ML to address these concerns and revolutionize the way we handle payments.
What causes resistance in payments innovation?
Understanding the root causes of this resistance is crucial for overcoming barriers and fostering a culture of innovation.
A study titled "The Role of Innovation Resistance and Technology Readiness in the Adoption of QR Code Payments Among Digital Natives: A Serial Moderated Mediation Model" published on Business and Management provides some insights into these factors.
Regulatory Compliance
The payments industry operates within a complex regulatory environment. Any new technology must meet stringent standards to ensure secure and compliant transactions. The fear of non-compliance and the potential legal and financial repercussions can deter companies from adopting new technologies.
Security Risks
Security is a paramount concern in the payments industry. The risk of data breaches and fraud can increase with the adoption of new technologies, especially if these technologies have not been thoroughly tested and verified.
High Implementation Costs
The cost of implementing new technologies can be prohibitive, especially for smaller businesses. These costs include not only the price of the technology itself but also the expenses associated with training staff, integrating the technology into existing systems, and maintaining the technology over time.
The Potential Power of AI and ML in Payments
All the while, AI and ML are reshaping technology tools offering unprecedented opportunities for efficiency and security.
These technologies are capable of analyzing vast amounts of data in real-time, enabling faster and more accurate transactions. From streamlining payment processing to enhancing fraud detection, AI and ML are revolutionizing the way we handle money.
Although innovation in payments moves slow, early adopters in other industries are reaping the benefits.
By leveraging AI and ML tools, merchants are able to automate processes, reduce costs, and deliver more value for both themselves and their customers. The use cases are nearly endless.
Through artificial intelligence, opportunities to develop tailored products and services using personalization to add value become possible in scenarios such as:
Enhancing Customer Experiences
By analyzing customer data, AI can personalize offerings, increase loyalty, and drive revenue growth. Whether it's through chatbots or predictive analytics identifying patterns in customer behavior, AI is at the forefront of customer-centric innovation.
Fraud Detection and Security
By analyzing massive amounts of data in real-time, AI tools can identify fraudulent activities and anomalies, enhancing the security of transactions. This capability is crucial in an era where cyber threats are increasingly sophisticated and prevalent.
We at Justt are already using AI and machine learning to help merchants manage post-transaction chargeback disputes by learning from a history of dispute results.
Can we learn from early adopters in other industries?
Early adoption of innovative technology is emerging as a key differentiator for success.
The technology adoption curve, as explained by the Diffusion of Innovation theory developed by Everett Rogers, provides a framework for understanding the success of early adopters.
This model categorizes adopters into 4 main types:
- Innovators
- Early Adopters
- Early Majority
- Late Majority
Innovators are the risk-takers, excited by new technology and willing to face the consequences of its untested potential.
Early adopters, on the other hand, are more calculated in their approach. They observe the response of the innovators, learn from their experiences, and provide the critical support needed to spread the technology.
The Early Majority adopts an innovation after a significant amount of time, but benefits less.
The Late Majority adopts an innovation after the status quo. While this is typically a safe approach, the best you can hope to achieve is parity with the average competitor.
Early Adopters: The Calculated Risk-Takers
While both innovators and early adopters embrace new technology, their risk profiles differ significantly.
Innovators are the first to implement new technology, often facing high risks due to the unproven nature of the innovation. Early adopters, however, are more strategic in their approach. They learn from the mistakes of innovators, tailoring their products and services to better serve their target audiences.
Several of today's largest companies were once early technology adopters. For instance, while Altair, developed by MITS, was the first personal computer, Apple Computer, an early adopter, cornered the market. Similarly, Google outpaced search engine innovators like Archie, Excite, Lycos, and Infoseek to become the de facto search engine.
The Advantages of Early Technology Adoption
Early technology adoption offers several benefits that contribute to a company's success. These include:
- Less Competition: Early adopters are ahead of mass-market adoption, giving them a competitive edge as their rivals scramble to catch up.
- Capture Larger Audience and Revenue: With technology stacks ready to solve user problems, early adopters can serve more customers as soon as the market is prepared for mass adoption. This early adoption position can be leveraged to build brand loyalty, leading to future revenues.
- Accelerated Growth Momentum: Despite the high risks, the rewards for innovators and early adopters can be substantial. As the market matures, the growth trajectory for these companies accelerates.
The Future of Payments
As we look to the future, it's clear that AI and ML will continue to play a pivotal role in the payments industry. Whether it's streamlining mobile payments, improving the ecommerce shopping cart experience, or automating invoice processing in B2B payments, the possibilities are endless.
The shift towards AI and ML in the payments industry is more than just a trend; it's a revolution. We should look forward to a future where payments are faster, more secure, and more customer-centric than ever before.
Despite any challenges mentioned, the potential benefits of adopting new technologies in the payments industry are immense. Companies that can overcome these barriers and become early adopters of innovative technologies can gain a significant competitive advantage. As the payments industry continues to evolve, embracing innovation will be key to staying ahead of the curve.
To learn more about how Justt’s machine learning tools are innovating for merchants, get in touch with one of our chargeback experts.
