AI-Powered Payments: Visa's Smart Stand-In Processing

Introduction to Visa's Payment Ecosystem

Visa is a global leader in digital payments, facilitating transactions between consumers, merchants, financial institutions, and businesses across more than 200 countries and territories. As of September 2022, Visa had issued approximately 3.9 billion cards worldwide, processing around 283 billion payment transactions annually.

The Visa network includes over 14,500 financial institutions and more than 130 million merchant locations. At its core, Visa operates on a four-party model:

1. Issuers: Financial institutions that provide Visa-branded cards and payment products to consumers.
2. Acquirers: Financial institutions that process payments for merchants and ensure they receive funds from transactions.
3. Merchants: Businesses that accept Visa payments through point-of-sale systems and online transactions.
4. Cardholders: Individuals and businesses who use Visa payment products to make purchases.

VisaNet: The Backbone of Visa's Operations

At the heart of Visa's operations lies VisaNet, a global network that connects the company's technology infrastructure to enable secure and fast digital payments. VisaNet is responsible for processing an astounding 775 million transactions per day on average.

Some key statistics about VisaNet:

• Connects 3.9 billion accounts
• Links over 130 million merchant locations
• Operates across 200+ countries and territories
• Has been in operation since the early 1970s

In recent years, VisaNet has undergone significant enhancements through the integration of artificial intelligence (AI) and deep learning technologies. These advancements have led to the development of what Visa calls "Smarter VisaNet."

Smarter VisaNet: The Next Generation of Payment Processing

The goal of Smarter VisaNet is to develop next-generation network product capabilities and deliver seamless authorization, clearing, and settlement for all parties in the Visa ecosystem. Since 2019, Visa Research has been building a series of Smarter VisaNet products to achieve this objective.

One of the most notable innovations in this space is Smart Stand-In (Smart STIP), which represents Visa's first AI-powered product in production. The successful launch of Smart STIP has garnered significant attention within the payments industry due to its potential to revolutionize transaction processing during bank outages.

Understanding Stand-In Processing (STIP)

Stand-In Processing occurs when an issuer (typically a bank) experiences an outage and cannot respond to authorization requests in real-time. During normal operations, when a cardholder makes a transaction, their issuing bank makes an immediate approve or decline decision. However, if the issuer is unavailable due to technical issues or network problems, Visa steps in to make decisions on behalf of the issuer.

Traditionally, these stand-in decisions were based on static rules, which tended to be overly conservative and resulted in a high number of declined transactions. This approach had negative impacts on all parties in the Visa ecosystem:

• Cardholders experienced poor user experiences due to unnecessary declines
• Banks and merchants lost revenue from rejected valid transactions
• Visa's reputation could be affected by customer dissatisfaction

Smart Stand-In (Smart STIP): AI-Powered Decision Making

To address the limitations of traditional stand-in processing, Visa developed Smart STIP, an AI-powered solution that mimics issuer decision-making more accurately. Smart STIP incorporates three key elements to simulate issuer responses:

1. Account information from users
2. Issuer's historical decision logic
3. Risk-related information

By leveraging these data points, Smart STIP aims to make more intelligent and accurate decisions during issuer outages.

The Technology Behind Smart STIP

Smart STIP utilizes a deep learning model based on Recurrent Neural Networks (RNN) with Long Short-Term Memory (LSTM) cells. This architecture was chosen for several reasons:

1. RNNs are widely used in natural language processing tasks due to their ability to interpret sequential data.
2. LSTM cells are designed to maintain long-term memory, addressing the vanishing gradient problem common in traditional RNNs.
3. The model structure is both effective and simple enough to implement in a production environment.

The input for the Smart STIP model consists of sequential transaction data, which is transformed into features through a feature engineering pipeline. These features then pass through embedding layers to create better representations before entering the final LSTM model for decision prediction.

Real-World Performance of Smart STIP

Visa has conducted simulations and real-world tests to evaluate the performance of Smart STIP. In one case study from 2019, a major issuing bank experienced an outage lasting several hours, affecting hundreds of thousands of transactions. By applying the Smart STIP model, Visa observed:

• A 60% improvement in approval rates
• Millions of dollars in increased approved transaction amounts
• Low risk levels for the additionally approved transactions
• Consistent out-of-time validation performance with AUC scores exceeding 0.8
• Stable performance over a six-month testing period
• Gradual self-adjustment of the model as more data was incorporated

These results demonstrate the significant positive impact of Smart STIP on transaction approvals during issuer outages while maintaining low fraud rates.

Challenges and Future Developments

Despite the success of Smart STIP, Visa has encountered several challenges as the product has scaled and more clients have adopted it. One of the primary issues has been the need for better interpretation of model decisions.

Explainable AI for Smart STIP

To address the "black box" nature of deep learning models, Visa has developed an explainable AI framework called X-STIP (Explainable Smart Stand-In Processing). This system combines various methodologies commonly used in industry, such as:

• LIME (Local Interpretable Model-agnostic Explanations)
• SHAP (SHapley Additive exPlanations)
• Proprietary explanation techniques

By integrating these approaches, X-STIP generates more robust, automatic, and objective explanations for Smart STIP model decisions. This helps Visa's data scientists and business analysts provide clearer insights to clients about why specific decisions were made during stand-in processing.

Incorporating Advanced AI Technologies

Looking to the future, Visa is exploring ways to incorporate more advanced AI technologies into its payment products. Some potential areas of development include:

1. Integrating large language models and generative AI to enhance X-STIP:

   • Utilizing GPT-like models to create more user-friendly interfaces
   • Developing chatbots that can provide human-readable explanations of model decisions

2. Applying reinforcement learning with human feedback to improve Smart STIP performance

3. Investigating the use of other advanced AI techniques to further enhance payment processing and fraud detection

Data Challenges and Model Adaptation

One of the significant challenges Visa faces in utilizing AI for payment processing is dealing with data quality and distribution shifts. The COVID-19 pandemic, which began shortly after Smart STIP's launch in 2020, caused significant changes in consumer spending patterns and transaction distributions.

To address these issues, Visa has implemented several strategies:

1. Regular model refreshes to incorporate new data and adapt to changing patterns
2. Introduction of new features that better capture pandemic-related spending behaviors
3. Implementing a 21-day warm-up period for new models in production to ensure consistency and stability

These measures help ensure that Smart STIP remains effective and accurate even in the face of significant global events and changing consumer behaviors.

Handling AI Hallucinations and Ensuring Accuracy

As Visa explores the integration of generative AI and large language models into its products, the company is acutely aware of the potential for AI hallucinations – instances where AI models produce incorrect or nonsensical outputs. To mitigate these risks, Visa is taking several precautions:

1. Investigating open-source language models like LLaMA to understand their capabilities and limitations
2. Enhancing public models with Visa's proprietary data to improve their relevance and accuracy in the payments domain
3. Implementing rigorous testing and validation processes to identify and eliminate potential hallucinations
4. Developing guardrails and safety measures to prevent the dissemination of incorrect information to clients or consumers

By carefully managing the integration of these advanced AI technologies, Visa aims to harness their potential while maintaining the high levels of accuracy and reliability required in the payments industry.

Competitive Landscape and Market Share

While Visa maintains a dominant position in the global payments market, the competitive landscape varies by region. In the United States, Visa holds a significant market share advantage over its primary competitor, Mastercard. However, the situation may differ in other regions such as Europe, where different companies may have stronger footholds due to varying business strategies and regulatory environments.

Visa's continued investment in AI and advanced technologies like Smart STIP helps the company maintain its competitive edge and expand its market presence globally.

Conclusion: The Future of AI-Powered Payments

Visa's development and implementation of Smart STIP demonstrate the transformative potential of AI in the payments industry. By leveraging deep learning and advanced data analysis techniques, Visa has created a system that significantly improves transaction approvals during issuer outages while maintaining high levels of security and fraud prevention.

As the company continues to explore new AI technologies and refine its existing models, we can expect to see further innovations in areas such as:

• More sophisticated fraud detection and prevention systems
• Enhanced personalization of payment experiences for consumers
• Improved real-time decision-making capabilities for issuers and merchants
• Greater integration of AI-powered chatbots and virtual assistants in customer service

The success of Smart STIP and Visa's ongoing research into AI applications showcase the company's commitment to staying at the forefront of payment technology. As AI continues to evolve and mature, it will undoubtedly play an increasingly central role in shaping the future of global financial transactions and services.

By embracing these technological advancements and addressing challenges head-on, Visa is well-positioned to continue its leadership in the digital payments space, providing faster, more secure, and more intelligent payment solutions for businesses and consumers worldwide.

Article created from: https://www.youtube.com/watch?v=DcUjQxzKeNE