Ash Gupta retires this month after 41 years at American Express, most recently as President for Global Credit Risk and Information Management. He has seen a lot during his tenure, and the characteristically modest Gupta has done more than his share to help shepherd the transformation of American Express into a data-driven company. For many in the industry, Gupta is seen as being the father of data-driven risk analysis, and his efforts have contributed to the increased usage of data and analytics in financial services. I recently sat down with Gupta to reflect back on his four decades with American Express and to understand how the firm transformed into a data-driven culture and a leader in the application of data and analytics within the financial services industry.
Adapting to a Changing Industry
Gupta noted how the financial services and payments industry has changed in important ways over the last four decades, notably:
- Electronic payments, which comprise credit/debit cards and online payment, have steadily gained market share over cash on a global basis, driven in part by co-brand relationships, e-Commerce, convenience, rewards, and the security offered by Electronic Payments;
- E-Commerce and cross border commerce continues to rapidly gain share over offline commerce with the rapid proliferation of internet and smartphones;
- Credit/debit card issuing has become concentrated among a few banks. In addition, multiple companies have joined the payments/e-Commerce ecosystem.
While interactions with the customer are changing from a monologue (direct mail) to dialogue (online application), customers’ online and offline identity is being synthesized for a 360-degree view. Industry-wide collaboration among data providers and marketers is driving innovation in product design and marketing, all with rising emphasis on customer privacy and responsible lending. Gupta notes that the rate of change continues to accelerate. As examples:
- Customer interactions, across the entire lifecycle, are gradually becoming app and mobile-based;
- QR codes are big enablers, especially markets like India or China that were under-served and where point-of-sale terminals are relatively expensive;
- Payments and e-Commerce have begun to merge, even as the share of merged entities currently remains small
- New and non-traditional data sources emerge, such as phone number, cookies, and digital data
- Marketplace lenders and Fin Tech companies are increasingly promoting innovations across the customer lifecycle, from targeting, to underwriting, to ongoing servicing and through credit and collections.
Gupta observes that we are nearing the end of one of the longest economic expansions since the World War II. Credit loss has begun to rise and card issuers are focusing on forward-looking economic indicators, stress testing portfolios and investing in decision science to address the potential for a recession.
Forging a Data-Driven Culture
In this environment, data and analytics (machine learning based decision science) have become central to effective marketing, servicing and risk management. Data sophistication is now essential to competitive excellence.
Since its formation 168 years ago, transformation has been a hallmark of American Express’s DNA. The firm has transformed from a freight forwarding business to a global leader in payments and personalized services. It has responded to marketplace changes and has been often an industry pioneer in customer-based risk management, membership rewards, marketing, and servicing. Gupta recalls that when he started with the firm in 1976, traveler's checks were a dominant product line and that card-services were just evolving. American Express has since launched many new products, one classic example being small business lending which launched in the late 1990s. American Express is now the number one small business card issuer in the U.S.
While the company continues to evolve at an accelerated pace, its core values remain essentially the same. Gupta describes this as “keeping the interests of the customer first in everything we do and being a good citizen in the communities which we serve”. Gupta believes that an effective data-driven organization invests in capabilities, technology and analytics, along with people, recognizing that it is the synthesis of technology and human intuition that provides superior results. Above all, it shows a very deep regard for “permissible purpose” when it comes to data use and customer privacy, ensuring that the data is used responsibly.
Gupta observes that good data-driven organizations have a “test-and-learn” culture and encourage experimentation that can challenge long-held beliefs. These organizations promote listening and learning, and adequately synthesize it with the institutional knowledge and experience. For American Express, this data-driven culture is a natural course of business. At every step, from acquisition to customer management, a large volume of insightful data is created, which is synthesized with partner and third party data to produce industry leading insights that are used for personalization and excellence in customer service and risk management. Gupta remarks, “At American Express, we take our responsibility to serve customers and the public seriously, always ensuring that solutions are best-in-class and valuable to our customers”.
Success in creating and maintaining a data-driven organization requires commitment from the top and a willingness to invest in people and capabilities in advance of customer outcomes. In addition, the organization must be attractive to the top talent. Gupta cites several examples of how American Express stays fresh and interesting:
- Risk 2020 -- American Express conceptualizes how the economy and marketplace might evolve in the coming years and what are the most important risk capabilities to maintain to proactively address the weakness in the economy, a steady move towards mobile computing, cloud, artificial intelligence and deep-learning.
- Cornerstone -- This is a global, big data ecosystem is where data is organized in one place with shared global capabilities, to democratize its use across functions and geographies, recognizing that the very essence of innovation must happen at the company’s DNA rather than exclusively from the top.
Gupta notes, “Challenges vary across institutions. The most common challenge is a willingness to invest upfront, recognizing that the benefits will be in the medium term, rather than in the immediate future”. Another challenge is recruiting. This means retaining and developing quantitative talent in an environment where the demand exceeds supply globally. According to Gupta, we are successful when we create a culture where there is “openness to listening to analysis that is at times is not in sync with one's mutual instincts.”
A Legacy of Accomplishment
In the end, though, it’s not just about having the best algorithm. Gupta comes back time and again to people as the critical ingredient to building a culture of success. He stresses the importance of cooperation and striving for collective excellence in collaborating with people. He cites examples from throughout his career:
- Three decades ago, this resulted in converting the credit and fraud risk management discipline from an ‘apprentice based’ to a ‘data and decision science-based’ organization not just for American Express, but for the entire industry. This has attracted some of the brightest people to this industry and has been an important training ground for the next generation of leaders within the industry. It has allowed credit to be offered to a far broader range of consumers and businesses promoting better economic growth. It has also been an important contributor to American Express’ industry leading credit and fraud write off rates across all economic environments;
- Two decades ago, it was creating a Center of Excellence in India as a collaborating team across all its global businesses to provide data and decision science partnership as American Express launched new products and services. This team remains an internal source of competitive advantage, an envy of competitors and often a benchmark for how to build a “knowledge center” in an international geography;
- In this decade, American Express has created Big Data and machine learning based decision science capabilities and teams, which have fundamentally transformed all aspects of its customer experience, including product design, marketing, risk control and servicing. Most importantly, it has created a foundation for excellence for the next decade as we invest in deep learning, artificial intelligence and blockchain.
Looking back, Gupta is proudest of the creation of the risk and information management team as an industry pioneer. He notes, “It is a team that consistently delivers the very best for our people, customers and shareholders. It is the place where our regard for each other and for all our American Express colleagues trumps our individual needs and desires, where the thinking from each of us has to be ‘what can I do for the company?’ rather than ‘what can the company do for me?’, where we collaborate and learn by listening and doing, where being second (in the industry) is not a choice”.
Gupta reflects, “My greatest accomplishment has been winning the hearts and minds of my colleagues that investments in data and decision science will bring lasting benefits to our brand, our customers, our people, and forever accelerate our mode to a listening and learning organization." He continues, “I hope my legacy will leave a lasting effect -- a commitment to collaboration, learning and innovation among my American Express colleagues who I’ve had the privilege of serving over the past 41 years”.
It will be the people and the culture of American Express that Gupta will miss most, and it is this culture of collaboration and excellence in data-driven customer experience which is the legacy that Gupta hopes to be remembered for.
Randy Bean is an industry thought-leader and author, and CEO of NewVantage Partners, a strategic advisory and management consulting firm which he founded in 2001. He is a contributor to Forbes, Harvard Business Review, MIT Sloan Management Review, and The Wall Street Journal. You can follow him at @RandyBeanNVP.
