AI Applications in Banking: 18 Notable Examples
In the ever-evolving world of finance, Artificial Intelligence (AI) is making a significant impact, transforming the way banks operate and serve their customers.
FIS, a leading provider of banking and financial solutions, utilizes C3 AI in its compliance hub to aid capital markets firms in combating financial crime. The company's credit analysis solution employs machine learning to digitize financials and deliver near-real-time compliance data, while its chatbot assists customers with queries, transfers, payments, and provides payment summaries.
Ally Financial has integrated a machine-learning-based chatbot into its mobile banking application, providing instant assistance to customers. This chatbot is not limited to answering questions but also facilitates tasks like transfers and payments.
Discover, in partnership with Google Cloud, aims to integrate generative AI solutions into its customer service experience. This collaboration is expected to streamline interactions, making them more personalized and efficient.
Wells Fargo is one of the major banks leveraging AI agents extensively across customer service, internal workflows, and corporate support. These AI agents automate routine tasks, answer standard queries, and help with account lookups, thereby speeding responses and reducing human workload. Complex issues are escalated to human agents, with careful monitoring to meet financial regulations.
Ramp, a fintech company, employs AI agents to manage expense workflows at scale, integrating AI agents deeply into their financial operations.
Asian banks have also joined the AI revolution, with AI agents being used for 24/7 customer support. These AI agents provide instant responses to balance inquiries, password resets, or fraud alerts outside normal hours. By 2025, around 95% of banks are expected to use AI chatbots for fraud notifications and customer interactions.
AI agents are recognized as a new class of proactive digital assistants, capable of learning and acting with minimal human direction. In banking, these agents specialize in personalization at scale, fraud detection/prevention, operational efficiency, and future-proofing financial services.
Kensho Technologies provides machine intelligence and data analytics to leading financial institutions like J.P. Morgan, Bank of America, and Morgan Stanley. Its platform allows financial institutions to run stress test analyses and test the waters for market contagion on large scales.
Upstart uses AI to make affordable credit more accessible while lowering costs for its bank partners. Its platform includes personal loans, automotive retail and refinance loans, home equity lines of credit, and small dollar "relief" loans.
ZestFinance's AI-based software generates fairer models, essentially by downgrading credit data that it has "learned" results in unfair decisions, thus lessening the weight of some traditional (but not entirely reliable) metrics like credit scores.
AI-enabled chatbots and voice assistants are the norm at major financial institutions. Capital One released Eno, a virtual assistant that users can communicate with through a mobile app, text, email, and on a desktop. Eno lets users text questions, receive fraud alerts, and takes care of tasks like paying credit cards, tracking account balances, viewing available credit, and checking transactions.
Feedzai uses machine learning to help banks manage risk by monitoring transactions and raising red flags when necessary. It has partnered with Citibank, introducing AI technology that watches for suspicious payment behavioral shifts among clients before payments are processed.
AI is also impacting biometric authorization and AI-enabled robotic help in banking customer support. Through Google Cloud's Vortex AI platform, Discover's contact center agents have access to document summarization capabilities and real-time search assistance.
AI-powered biometrics, developed with software partner HooYu, match an applicant's selfie to a passport, government-issued I.D. card, or other official photo identification document.
Gynger is a B2B payments and financing solution that partners with both buyers and sellers of technology. Its underwriting is powered by artificial intelligence and it offers a variety of services like next-day approval for non-dilutive payment solutions and turn-key integrations with clients' existing tech stack.
Ayasdi's AI-powered AML incorporates intelligent segmentation, an advanced alert system, and advanced transaction monitoring to optimize the data-sifting process, auto-categorize alert priorities, and spot suspicious anomalies respectively.
Vectra AI assists financial institutions with its AI-powered cyber-threat detection platform, automating threat detection, revealing hidden attackers, accelerating investigations, and identifying compromised information.
DataVisor's machine learning uses big data and clustering algorithms in real time to counteract application and transaction fraud. The company has helped financial institutions save millions in losses and manual review costs.
Affectiva injected Pepper, a humanoid robot, with sophisticated abilities to read emotion and cognitive states.
Simudyne uses agent-based modeling and machine learning to run millions of market scenarios.
In conclusion, AI is transforming every banking "office" - front, middle, and back, impacting areas such as investment assistance, consumer lending, credit scoring, smart contracts, and more. The AI in banking industry is projected to reach $64.03 billion by 2030.
- Fintech companies such as Ramp and Gynger are integrating AI agents into their financial operations for managing expense workflows and underwriting, respectively.
- AI-enabled technologies are being used across various aspects of the banking industry, from AI-powered chatbots for customer service at major institutions like Capital One, to AI-powered AML systems for fraud detection and prevention like Ayasdi's. The use of AI in the finance and fintech sectors is expected to reach $64.03 billion by 2030.
