Using Generative AI in banking promises to boost operating profits and positively affect all segments and functions. It has significant potential to enhance productivity, reshape job roles, and revolutionise customer interactions within the financial industry.
And while many banks have yet to embrace this advanced technology, we’ll explore some successful examples of generative AI applications in the banking sector.
Wells Fargo: Pioneering LLMs and Multimodal Banking Experiences
Wells Fargo utilises generative AI in its virtual assistant app, Fargo, which has handled over 20 million interactions since its launch in March 2023. Fargo, powered by Google Dialogflow and Google’s PaLM 2 LLM, aids customers in everyday banking tasks like bill payments, fund transfers, and transaction inquiries.
Another Wells Fargo app leveraging LLMs offers customers advice for goal-setting and planning. Since its recent launch, this app has garnered a million monthly active users. Additionally, Wells Fargo employs open-source LLMs, including Meta’s Llama 2 model, for internal applications.
These LLM deployments operate on Wells Fargo’s AI platform that supports these initiatives, focusing on adaptability and performance. The bank anticipates the future of multimodal LLMs, emphasising their potential for enhanced user experiences.
CBA: GenAI for Enhanced Customer Experience and Combatting Financial Abuse
The Commonwealth Bank of Australia (CBA) is exploring using Generative AI to enhance customer experiences. The bank’s initiative, unveiled at South by Southwest Sydney in 2023, aims to study how GenAI chatbots can simulate customer behaviours and serve as an early experimentation tool. The goal is rapidly testing, expanding, and improving products and services.
The Australian bank is particularly interested in using GenAI to understand customer responses in challenging situations, such as natural disasters, potential scams, or family losses. The preliminary study involves creating AI-generated customer personas to test and explore customer behaviours, providing a safe and efficient method for developing improved products and services.
Also, CBA is taking a groundbreaking step in the fight against technology-facilitated abuse. A recent research revealed that one in four Australian adults have experienced financial abuse from their partners. The CBA’s AI model can spot digital payment transactions with harassing or offensive messages, helping identify cases of abuse.
The model and source code are accessible on GitHub to improve visibility and empower other financial institutions to address abuse effectively, making banking safer for vulnerable customers. This AI model works alongside CBA’s existing measures, including an automatic block filter and manual review of flagged abuse cases.
Deutsche Bank: AI-Powered Personalised Investment Guidance and Customer Service
Deutsche Bank utilises AI to enhance customer service and investment advice. Algorithms analyse customer portfolios, identifying risks and suggesting appropriate adjustments. The project employs algorithms to recommend suitable products based on similar customers’ portfolios, ensuring personalised recommendations.
Moreover, recommendations for portfolio adjustments are made only if they promise significant benefits, considering potential gains and costs. Ultimately, advisors make informed decisions based on their understanding of individual customer needs.
Dutch fintech Bunq has rolled out a user-friendly feature in its app, designed to replace the search function. The GenAI tool simplifies financial planning, app navigation, transaction searches, and more.
With 11 million users across Europe, the Amsterdam-based fintech startup says its new in-app tool has functions similar to ChatGPT. Sporting a chat-style text box, users can effortlessly inquire about their bank account, spending patterns, savings, and any other money-related queries.
Dive into practical implementation tips and use cases of generative AI in finance in our article.
Mastercard: AI-Powered Fraud Detection and Consumer Protection
Mastercard, an American payment system, is deploying a new tool powered by artificial intelligence to combat fraud. Their innovative AI model, trained on vast amounts of transaction data, aims to spot suspicious activities more effectively. The company expects to enhance fraud detection by an average of 20%, with potential increases of up to 300% in some instances.
This AI system will analyse various transaction details in real-time, such as account information, purchases, merchant data, and device identifiers, to determine the likelihood of an illegitimate transaction. The company plans to make this solution accessible starting in late 2024.
Mastercard has already been actively exploring AI solutions for its clients. One such solution, Consumer Fraud Risk, was initially introduced in the UK market around mid-2023. Nine major UK banks, including Lloyds Banking Group, Natwest Group, Bank of Scotland, and TSB, have collaborated on this project by sharing extensive payment data.
This solution prevents scams by stopping fund transfers in real time and protecting victims’ accounts. Fraudsters constantly evolve their methods, tricking individuals and businesses through transactions that appear legitimate, such as payments to familiar contacts or online shopping. Mastercard’s AI aids banks in detecting scams, particularly those involving purchase and impersonation schemes.
Visa, a major competitor to Mastercard, is actively engaged in various generative AI initiatives, showcasing its dedication to utilising this technology in the payments sector. The company has introduced its AI Advisory Practice, which offers practical insights and recommendations to assist clients in effectively harnessing generative AI in banking and financial services.
Furthermore, Visa has allocated $100 million to foster innovation in generative AI in payments and commerce, embracing transformative technologies for the future of finance.
PayPal: Empowering Checkout Efficiency and Fraud Prevention with AI
PayPal, another widely used online payment system, has recently announced new AI tools designed to streamline the checkout process, offer personalised cash-back deals, and empower retailers to reach consumers with targeted promotions. These internally developed AI tools can analyse consumer data and merchant product information to create original content similar to generative AI platforms.
Regarding fraud prevention, PayPal employs machine learning (ML) and graph technologies to establish connections and assess relationships within its data. This approach enhances payment authorisation rates and strengthens efforts to combat payment fraud.
Uncover the generative AI strategies of Goldman Sachs and Morgan Stanley in this article.
Generative AI brings numerous benefits to financial organisations, from fraud detection to improved customer service and risk assessment. While some have successfully implemented AI solutions, others are still in the early stages, proceeding cautiously.
As generative AI becomes more prevalent across industries, the financial sector may encounter significant challenges in adoption, particularly in risk assessment.
If you seek insights into the use of generative AI in banking and finance, contact Tovie AI. Our consulting services assist financial organisations in identifying tailored use cases for optimal team and customer outcomes.
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