Ten Successful Examples of Big Data and AI Projects in Financial Services
- Goldman Sachs utilizes AI for fraud detection to reduce false positive alerts and allow for quick action.
- BofA implemented Big Data to gather customer insights for personalized offerings, leading to a decrease in customer attrition rate by 50%.
- JPMorgan Chase introduced machine learning models to automate routine processes, with savings of $3 billion since 2018.
- US Bancorp invested in AI technology to identify customers’ needs at their branches before they have to ask, saving time and providing better service.
- Citadel Securities deployed AI-based algo trading, resulting in faster transaction time, improved order volume, and maximized market liquidity.
- CitiGroup’s algorithms prevent credit card fraud and detect inconsistencies in transactions quickly and accurately.
- Ally Bank uses its proprietary AI system (Ally Assist) to assist customers with queries while remaining compliant with regulations and policies such as AML/KYC guidelines set by regulators like FINRA or SEC.
- TD Ameritrade has developed a Natural Language Processing-powered application, ‘MyVA’ for voice recognition to help customers manage their investments more efficiently through verbal commands instead of written ones on mobile devices or PCs
- Wells Fargo is leveraging Big Data analytics from third parties like Equifax and Experian to build predictive models that anticipate customer needs and provide tailored services according to their financial habits, goals, or priorities.
- Schwab Intelligent Portfolios uses predictive analytics techniques such as pattern recognition in historical data and sentiment analysis from news sources for stock recommendations ahead of market movements.