American Express began as a freight forwarding company in the mid-19th century. Expanding over time to include financial products and travel services, American Express today reports some 114 million cards in force and $1.2 trillion in billed business worldwide.
American Express trades on the NYSE with a market cap that exceeds $136 billion, as of November 2021. For the fiscal year ended December 31, 2020, American Express reported revenues of $36.1 billion, according to its Fiscal Year 2020 10-K.
American Express generates its revenue from merchant fees, interest on outstanding balances, and fees for card membership, late payments, foreign currency conversions, and other fees like those generated from its prepaid card and Travelers Cheque services.
American Express has established American Express AI Labs, which works with business leaders to ideate and advise on AI-based products and services. Its research areas include machine learning and optimization, natural language processing, AI products, document recognition and processing, and cloud platforms.
In this article, we will look at how American Express has explored AI applications for its business and industry through two unique use-cases:
- AI-Driven Fraud Detection — American Express has used its Gen X model to combat rising credit card fraud during the pandemic.
- Automating Customer Service Through NLP — American Express uses BERT models to determine customer intent and process requests through its award-winning customer service function.
We will begin by examining how American Express has turned to its tenth-generation fraud model to identify and eliminate fraud in the billions of credit card transactions the card issuer processes every year.
AI-Driven Fraud Detection
During 2020, Americans reported over 390,000 instances of credit card fraud, an increase of more than 40% over 2019 levels, according to research published by The Ascent, a service of the Motley Fool. In fact, the research found, credit card fraud ranked #1 as the most common type of identity theft suffered by victims between 20 and 39 years of age.
As a top-five credit card in terms of active cardholders in the US, American Express has a vested interest in proactively detecting and eliminating credit card fraud. However, American Express must balance its fraud detection and prevention controls with the customer experience they provide to their cardholders. Simply put, they do not want to lose customers and disrupt customer business in order to root out fraud.
To improve the customer experience and reduce fraud risk, American Express has developed a “fraud model [that] is one of the most advanced in the industry,” said Dr. Dmitry Efimov, VP of Machine Learning Research at American Express, during a recent Emerj AI in Business podcast.
That model, called Gen X since it’s now a tenth-generation model, has grown to monitor and reduce fraud risk throughout American Express since the model’s first iteration in 2014. It’s also the biggest model within the card issuer’s operations, Dr. Efimov says.
AmEx built the model by first prioritizing the underlying business question the company wanted to answer, Dr. Efimov advises. With $1.2 trillion in worldwide billed revenue in 2019 alone, the model evaluates some 8 billion …….
Source: https://emerj.com/ai-sector-overviews/artificial-intelligence-at-american-express/