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    Generative AI for Payments: 5 Use Cases to Address Business Challenges and Mitigate Risks

    calendar Updated November 06, 2024
    Ivan Pohrebniyak
    Chief Delivery Officer
    Generative AI for Payments: 5 Use Cases to Address Business Challenges and Mitigate Risks

    As a very popular technology, Generative AI did not bypass the payments sector. Such industry giants like Visa and innovative platforms like Form3 and Wex showcase the impact of Gen AI. We have gathered their most impactful strategic investments, collaborative ventures, and technological advancements.

    This article explores the possible business use cases, risks and successful stories of leveraging Artificial Intelligence. Since you are interested in tangible outcomes of Generative AI within the payment ecosystem, read to the end to discover how it can benefit your company.

    Core Generative AI Use Cases in Payments Can Impact Your Business

    Generative AI Use Cases in Payments

    The financial sector faces numerous challenges in today’s digitalized life. As payment systems have strict regulations, they should be handled accordingly. To demonstrate how innovative technologies can help, let’s take a look at business use cases for Generative AI.

    Payments Process Management

    Incorporating new technologies changes how businesses handle transactions. By leveraging advanced algorithms, systems can optimize various stages of payment processing, from invoice handling to reconciliation. This automation minimizes human errors, ensuring greater accuracy in business operations. Additionally, AI streamlines payment routes for efficiency in various interactions. This way, models select the most efficient methods, thereby reducing processing times and costs.

    This digitized approach leads to faster payment processing, providing increased cash flow management. Moreover, the reduction in errors mitigates potential expanse losses due to inaccuracies. At last, smoother procedures will give you better customer satisfaction.

    Real-Time Fraud Prevention

    Global digital fraud losses are expected to exceed $343 billion between 2023 and 2027. For that reason, more financial institutions are considering using Generative AI. For instance, AI can monitor transactions and swiftly identify any suspicious activities. By using machine learning algorithms, tools analyze large volumes of data in real-time. Such software will flag fraudulent transactions based on unusual patterns or deviations from established behavior. This fast detection allows businesses to take immediate action, preventing significant harm.

    Generative AI benefits for business lie in ensuring the security of their transactions, and growing trust and confidence among customers. For instance, fraud detection systems stay ahead of evolving fraud techniques, thus safeguarding the business against emerging threats.

    Redefine Finance with AI Strategy Guide

    Generative AI Chatbots Adoption

    Do you know that 69% of consumers prefer to use chatbots for service-related questions? These programs, equipped with natural language processing capabilities and provide instant responses 24/7. In such a way, users get personalized assistance, as bots guide clients through transactions, resolving their issues. Moreover, Generative AI chatbots offer tailored product or service recommendations based on buyers’ preferences.

    This adoption benefits businesses with higher retention rates. Additionally, you will experience significant cost savings by cutting down the need for customer support. Furthermore, virtual assistants gather valuable data on client interactions for more targeted marketing efforts.

    Reports Automation

    An interesting fact is that around 61.5% of companies with 11-1000 employees are using Generative AI in the workplace. What’s even more exciting is that 75% of users aim to automate tasks at work by implementing this technology. Gen AI eliminates manual tasks in comparison to the time it would take a human. This technology efficiently processes vast amounts of data from various sources, generating insightful reports. Moreover, AI algorithms can identify trends, anomalies, and correlations within the data.

    The advantages are obvious — time and resource savings, previously spent on manual tasks. Additionally, the speed and accuracy of AI-generated reports will help businesses make informed and timely decisions, enhancing their competitiveness.

    Structured Data Enchantment

    Generative AI algorithms are capable of cleaning, organizing, and augmenting data. With enhancement like these, businesses can ensure data accuracy, consistency, and completeness. Such data quality is pivotal in deriving meaningful insights and making informed decisions.

    The evident advantages like data improvement lead to more accurate analytics, better strategic planning and forecasting. Summing up, your business intelligence will be more reliable. Hence, this structured data enrichment empower organizations to uncover hidden patterns or trends.

    How to Mitigate Gen AI Risks in Payments

    Gen AI Risks in Payments

    The use of Generative AI in payments is causing worries about its inherent risks. These worries involve bias, privacy issues, unclear outcomes, reliability problems, cybersecurity, and impacts on business sustainability.

    Data Privacy

    Generative AI usage and storage of personal data raise concerns about potential breaches and unauthorized access. It’s essential to protect data with stringent encryption and access controls to mitigate this.

    Embedded Bias

    Biased data for training AI models can lead to discriminatory outcomes in payment processes. This bias could affect decision-making, leading to unequal treatment among customers or businesses. Addressing this risk involves constant monitoring, auditing, and diversification.

    Synthetic Data

    The creation and use of synthetic data by Generative AI poses accuracy concerns. While it aids in training AI models, its accuracy compared to real-world data remains unclear. Consequently, businesses must validate the authenticity of synthetic data to ensure its reliability.

    Cybersecurity

    Technology integration heightens cybersecurity risks due to potential vulnerabilities in AI algorithms and systems. Cybercriminals might utilize these dangers to launch sophisticated attacks, compromising payment data integrity and confidentiality. Therefore, there’s a necessity for continuous security updates, robust authentication measures, and strict testing.

    Financial Stability

    Overreliance on AI systems without adequate fail-safes could lead to systemic failures or errors in payment transactions. Sudden disruptions in AI-powered systems could have widespread ramifications, affecting financial markets and stability. Accordingly, companies should have contingency plans that are crucial to mitigate such risks and maintain the stability of payment infrastructures.

    Discover Generative AI Examples in Payments

    In this section, we would like to demonstrate successful examples of how renowned brands benefit from leveraging the technology. Since some companies are already using Generative AI and shared first results, we have thoroughly gathered them for you. However, there are also those who only plan to integrate Gen AI into their operations in the future.

    Visa

    Visa, a global leader in payments, announced a $100 million Generative AI ventures initiative. These costs will be invested in companies focused on developing Gen AI technologies and applications.

    With generative AI’s potential to be one of the most transformative technologies of our time, we are excited to expand our focus to invest in some of the most innovative and disruptive venture-backed startups building across generative AI, commerce and payments

    David Rolf,

    Head of Visa Ventures, Visa Inc.

    Visa believes Generative AI is a transformative force in the world of commerce and payments, as the technology enables faster access to critical information, and better decision-making. The company has been supporting such projects since 2007. This time, Visa Venture will lead the initiative.

    We want to mention that Visa has been a pioneer of AI use in payments since 1993. Organization considers Generative AI for payments as an extension to boost innovation, make value for partners and clients, and empower global commerce.

    Form3

    Form3, the cloud-native account-to-account platform, got investment from Visa. This partnership provides Visa’s clients access to their best-in-class payment platform. As A2A transactions continue to grow, their collaboration aims to provide modern, cloud-native access to real-time payment infrastructures.

    They plan to combine Form3’s financial crime orchestration service with Visa’s deep-learning artificial intelligence and real-time risk scoring. This method will help financial institutions’ clients with risk management.

    Form3 implemented AI in payment processing, which scans data to identify patterns within datasets. This assistance provides risk scores to beneficiary accounts, helping banks decide whether to contact the payer or hold the payment. Still, nowadays, banks find it hard to add extra steps to fraud detection because more and more people expect payments to happen instantly. This is how Generative AI in the banking industry transforms business operations.

    Wex

    Wex is a leading provider of payment and business solutions in a wide range of sectors. Company shared how they applied machine learning and artificial intelligence models to the processes. They significantly improved tools in credit adjudication and monitoring. This approach gives the brand more details to adjust credit decisions based on risk and profitability. In a while, these enhancements showed initial results, also offering improved insights into their portfolio.

    Additionally, the organization started implementing LLM AI tools for software engineers. The business has already seen significant improvement in increased productivity. Wex has experienced the benefits of increased speed to market and reduced costs of developing new products.

    Earlier, Wex in partnership with AI.io launched WEX’s virtual payments’ technology into Halo Travel. It’s an intelligent, voice-activated chatbot for travel.

    Stripe

    Stripe, a financial infrastructure platform, has announced a collaboration with OpenAI. This partnership will help to power payments and subscriptions for such tools as ChatGPT and Dall-E. Stripe is also integrating GPT-4, into its own products and services. The global fintech will provide features such as billing, checkout, and tax compliance services.

    Beyond payments, Stripe is helping us with everything from recurring billing and tax compliance to automating our financial operations.

    Peter Welinder,

    Vice President of Product and Partnerships at OpenAI.

    Stripe has already used GPT-4 to improve its products and user experiences, helping its clients with fraud management and conversion rate growth. The company found various ways of using technology to streamline operations and help customers.

    Conclusion

    To sum up, Generative AI implementation can help with seamless transactions, which will enhance customer experiences. Your business can ensure accuracy in operations, by automating invoices and providing immediate updates. The technology’s ability to optimize payment processes reduces errors, fostering trust among consumers.

    The importance of these innovations lies in their capacity to streamline tasks, minimize discrepancies, and ultimately elevate the quality of services. Therefore, using AI ensures smoother transactions and demonstrates a commitment to modern finance.

    At Master of Code Global we care about your brand reputation and know how important it is to meet customers’ needs. MOCG is a leading Generative AI development company with a team of experts. We will assist with Generative AI chatbot adoption to offer round-the-clock support, raising client satisfaction.

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