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How Generative AI Will Change Payment Technology

One of the most exciting developments in the payment industry is the integration of Artificial Intelligence (AI) into payment technology. The dynamic response of fintechs and emerging players to technology advancements has not only pushed traditional players to adopt AI, but has also fostered an environment with fewer cumbersome legacy systems in the payments sector. This distinguishes it from the traditional financial services landscape.

The financial sector is exploring embedded finance, super apps, the metaverse, peer-to-peer wallets, cryptocurrency payments, buy now, pay later (BNPL) and more. Payments are being made at greater speed and with increased versatility. With generative AI, what are the payment possibilities of the future? How will generative AI redefine interactions within payment systems? Here is how generative AI will transform ways of doing business in the payment tech and payments industry.

Generative AI will have a revolutionary influence on payment platforms

At present, the pace of generative AI adoption is faster than internet startups, with ChatGPT reaching 100 million users within two months. According to research by Publicis Sapient, the majority (87 percent) of consumers who have used generative AI are excited about what generative AI can bring to their shopping experience. They expect brands to use the technology to improve overall customer experience.

Generative AI is emerging as a true game changer within the realm of payments. As organizations increasingly recognize its potential and seek to keep pace with the market, can payment tech companies navigate through all the hype surrounding this emerging technology and capitalize on the right opportunities?

Spearheading this transformation are AI-driven payment platforms, which harness complex algorithms to not only revolutionize but optimize payment technology. For example, super apps—multifunctional, all-in-one digital platforms—can integrate a wide range of services delivered directly to consumer smart phones. In this space, Alipay has transformed the way people make cashless payments.

But AI's impact transcends transaction processing—with generative AI, opportunities for innovation extend into fraud prevention, customer support and overall payment experience enhancement. For instance, organizations employ generative AI to analyze user purchase histories and preferences, enabling seamless, personalized payment experiences.

The imperative to strategically employ generative AI

For businesses to flourish, it is imperative to strategically employ generative AI in the following three key business dimensions:

  • Revenue enhancement
  • Financial efficiency
  • Customer experience and loyalty
Revenue enhancement

Customer acquisition and retention: Organizations must leverage generative AI to scrutinize users' buying patterns and preferences, creating smooth, tailored payment experiences to enhance customer acquisition and retention. They must establish a comprehensive strategy and roadmap covering operating models, data management, technology implementation, workforce training, compliance and responsible AI practices. Next, companies should innovate and roll out AI-driven capabilities throughout the end-to-end value chain, revolutionizing acquisition processes. This ranges from identifying intent and propensity to modeling, next-best action strategies, channel optimization, closed-loop measurement and performance enhancement, to employing generative AI for creative, communications and media initiatives. One such example is personetics. By using generative AI, personetics helps financial institutions attract new customers by offering them a more individualized and engaging banking experience.

Automated customer support: Organizations must address inquiries from agents regarding product details to expedite the application process and boost conversions. This can be achieved by the following steps:

  1. Educating a generative pre-trained transformer (GPT) chatbot with product or card-specific knowledge.
  2. Empowering the GPT model to provide real-time information tailored to the customer's data.
  3. Utilizing GPT to customize responses based on the context provided, ensuring relevance.
  4. Establishing a system to consistently update the model with the most current and validated product information for accuracy.

For example, Kasisto utilizes conversational AI to create virtual assistants for financial institutions. These virtual assistants, powered by generative AI, engage with customers in natural language, providing personalized assistance and helping with various banking tasks.

Financial efficiency

Generative AI will revolutionize operational efficiency: Generative AI stands poised to unearth substantial, contextually relevant value from expansive content reserves. This has the potential to revolutionize operational efficiency. To harness its fiscal benefits, companies should craft a strategic blueprint that prioritizes robust data governance policies. These policies should focus on ensuring data quality, integrity and regulatory compliance (such as GDPR and CCPA) across diverse business lines, with a specific emphasis on cost considerations. Organizations must integrate data classification and stringent access controls to safeguard sensitive customer information, balancing the utilization of data for marketing, loyalty and promotions with the imperative of maintaining cost-effectiveness. They should also implement auditing processes to scrutinize data usage, guaranteeing adherence to data protection regulations and optimizing cost impacts. For example, Ripples and Square incorporate AI to enhance fraud detection and risk management. Generative AI models help analyze transaction patterns, identify anomalies and improve data governance.

Generative AI will shape omnichannel analytics: Omnichannel payment solutions not only offer customers a spectrum of transactional choices but also hold the potential for operational efficiency and cost-effectiveness. Generative AI is emerging as a key player in shaping the future of omnichannel analytics, with its ability to unlock deeper insights, drive automation and enhance personalization, thereby contributing to cost savings. Examples of payment integrations include Amazon’s palm scanning technology, implemented in Amazon Go stores. Biometric payment technology uses a customer's physical characteristics to authorize payment or complete a point-of-sale transaction including face and voice recognition. Social media payments are another example of innovative payment strategies that go beyond traditional banking services.

Customer experience and loyalty

Companies will create and manage innovative designs and campaigns: As the payments landscape evolves, the role of generative AI in campaign creation and management becomes increasingly vital. Businesses can utilize AI-powered tools to analyze customer behavior, preferences and transaction histories. This data-driven approach can harness generative AI for the creation of targeted and personalized marketing campaigns that resonate with individual users. For example, a credit card company could use AI to identify users who frequently travel and design campaigns offering travel-related benefits. Additionally, AI can help businesses monitor the effectiveness of their campaigns in real time, allowing for adjustments and refinements to maximize impact.

Good copy will be powered by generative AI insights: Effective campaign design and compelling copywriting go hand in hand. As payment solutions evolve, businesses must craft visuals and narratives that resonate with their audience. Design elements such as colors, fonts and imagery should align with the brand's identity and evoke a sense of trust and innovation. Equally important is crafting copy that speaks to the customer's pain points and aspirations. For instance, a campaign promoting a secure payment app could emphasize the peace of mind customers gain from knowing their transactions are protected. Tailored messaging, powered by generative AI insights, can create a personalized connection that drives engagement and conversions.

Now is the time to evaluate where to innovate

There are many opportunities for payment tech companies to consider. How should innovation options be assessed and prioritized for maximum business impact? Publicis Sapient has developed an AI Suitability Score as a means of assessing the benefits and challenges for businesses.

The AI Suitability Score evaluates drivers and barriers and allows for the creation of a “heat map” of opportunities across the business. Drivers assess customer value, income generation and cost efficiency. Barriers evaluate the complexity of implementation, regulatory and compliance risk, as well as ethics.

 

Value Identification

AI Suitability score - Assigned to rate each area/category

Text depicting the Publicis Sapient AI Suitability score to help determine opportunities across the business

Generative AI-based technology is shaping the future of the payment tech industry. It will not only transform how customers pay for products, but it will also change customer relationships and investment decision-making. Ultimately, it will transform the very way businesses will go about innovation. This revolutionary AI paradigm breaks free from traditional rule-based systems, generating contextually relevant and creatively inspired content. Brands are already using generative AI for insights and information, questionnaires or getting past copy changes.

Dave Theran
Dave Theran
Client Partner, North America Payments Tech Lead
Rahul Agarwal
Rahul Agarwal
Senior Program Director

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