Generative AI has become a prominent technology in 2023, drawing the attention of global financial institution leaders. In the realm of payments services, where systems undergo rigorous handling and regulation, responsible implementation of AI technology is crucial to manage financial, operational, and business risks while adhering to regulatory directives.
While AI has been utilized in payment processing for years, generative AI platforms like ChatGPT have brought AI to the forefront, transforming its perception and enabling users to leverage it without coding skills. This shift is anticipated to unlock new possibilities for payments use cases.
Potential applications of generative AI in payments extend to enhancing regulatory compliance, anti-money laundering, and payment processing. These applications could also streamline customer experience and improve fraud detection, benefiting both financial consumers and market participants.
Key use cases in payments include:
1. Improving Payment Initiation: Utilizing generative AI for sophisticated payment initiation solutions can automate the extraction of payment information from documents, reducing manual tasks and errors during the payment initiation stage.
2. Fraud Detection and Prevention: Generative AI could enhance fraud detection by analyzing payment data to identify patterns and develop predictive models, enabling real-time flagging of suspicious activity, particularly crucial in the era of instant payments.
3. AI-Powered Chatbots: Generative AI chatbots can provide personalized real-time responses, improving customer interactions with payment product documentation.
4. Automated Payment Reports: Generative AI can automate business and operational reports, enhancing operational efficiencies and reducing errors in payment business performance.
5. Enriching Data into a Structured Format: AI can assist in converting free text addresses into structured formats, aiding the integration of ISO 20022 into legacy bank systems.
At the Sibos 2023 event, Finastra showcased how AI and Generative AI are integrated into its payment solutions. Demonstrated use cases included:
- AI-Powered Dashboards: Leveraging historical payment data to provide actionable insights, improving business processes, reducing costs, and increasing revenue.
- AI-Powered Chatbot: Offering real-time Q&A for Finastra payments product users, reducing learning time and optimizing payment processing performance.
- Invoice-Based Payment Initiation: Automatically extracting payment information from invoices, eliminating the need for manual data entry and reducing payment delays and errors.
- Compliance-as-a-Service: A SaaS-based solution supporting instant payments regulatory compliance with real-time sanction screening and AI/ML-based transaction monitoring.
While the future of AI in payments appears promising, financial institutions must navigate risks such as data quality, ethical and legal concerns, computational resources, interpretability, explainability, and security. To mitigate these risks, careful selection of partners and the establishment of responsible AI usage policies are essential for harnessing the benefits of AI technologies in payments. Finastra, as an example, emphasizes continuous exploration and adoption of advanced technologies alongside established AI usage policies to empower customers safely and responsibly.