Mastercard: Revolutionizing Financial Technology with AI
The financial technology world is a dynamic sector, and in this circle, Mastercard has remained at the top, for implementing technologies that are innovating and ensuring operational efficiency. So, against such a backdrop, this case study looks to find ways in which Mastercard strategically harnesses AI, scales applications, and maintains robust processes of governance for the responsible and impactful use of such a transformational technology.
Mastercard’s Strategic Utilization of AI
From its origin, Mastercard embraced the game-changing potential offered by AI. As stated by Ed McLaughlin, President and CTO of Mastercard, “AI has been a vital capability for Mastercard for years and is only growing in importance and impact.” The company infuses AI into its core operations to offer even greater security and personalization. One of the main ways through which Mastercard applies AI is with the decision management platform, acting as the AI powerhouse within its network. This platform allows real-time, nuanced transaction decisions to take place, with an astonishingly high speed of identification and prevention of fraud. McLaughlin stated, “In the last 12 months, we’ve stopped over $20 billion worth of fraud.”
How to Get the Best AI Solutions
The strategic deployment of AI in Mastercard is not by chance but rather because of an intentional process of arriving at a decision. A two-tiered review process is applied to review AI opportunities through the AI Review Board, followed by a deep-dive technical review.
The AI review board consists of members from diverse functions, including legal, privacy, product, and business, who review the intent, sources of data, and ethical considerations of proposed AI projects. McLaughlin added, “Knowing the project’s objective and viability from a business, product, legal, and privacy perspective is where it all has to start.”
If a project passes this litmus test, it is then subjected to an in-depth technical evaluation. This assessment includes scalability, return on investment, and how the target AI model will function. McLaughlin emphasized the scalability of AI projects with the expression that “if it can’t scale, it’s irrelevant.”
Scaling AI Across the Organization
According to McLaughlin, the Mastercard process on how to scale AI is by validating in silent mode. In other words, new AI techniques must run concurrently with current setups of systems within the company. This will be a way to allow the organization to measure the influence and effect of AI implementation without causing a hitch to business functionality. McLaughlin said, “We can run this in production concurrently with our existing systems and then evaluate if the difference justifies the additional expense.”
Why it worked: Mastercard invests significantly in training and up-skilling employees to scale AI projects. It has workbenches for software engineering, data science, and sales, which come with specific AI tools and training. McLaughlin added, “Getting the right balance of investment in data science, in engineering workbench, in other tools is critical to building a personalized environment that’s for you.”
Governance and Ethical Guidelines
The governance aspect remains one of the broadest dimensions of the Mastercard strategy about AI. Regarding the control and monitoring of the ethical and responsible use of AI, the company has put in place quite a thorough framework concerning AI governance. The framework, therefore, incorporates elements of continuous monitoring, compensating controls, and feedback loops to ensure ongoing model efficacy without unintended consequences.
Mastercard was also one of the original members of the Harvard Council for the Responsible Use of AI, founded on a commitment to use artificial intelligence responsibly. McLaughlin told DIGIT: “We put out a data bill of rights to our customers, saying, ‘Your data is your data. You have the right to know what data we have and how we use it.”
The governance processes in place within the organization make sure that all AI applications conform to both their core principles and regulatory requirements. This encompasses continuous reviewing and tuning AI models to take care of changing challenges like concept drift and others.
Future of AI at Mastercard
MasterCard is continuously exploring newer AI technologies and their possible uses. McLaughlin further explained future plans for the company: “We are exploring quantum computing for its security benefits and as a solution to complex combinatorial problems beyond classical computing capabilities.”
Staying ahead with an eye to the future keeps Mastercard in a leadership position and inspires confidence with customers. The strategic application of AI into its operations empowers it to handle future challenges and opportunities in the fintech sector.
In conclusion, Mastercard offers a great case for how organizations can strategically implement this kind of technology. All the AI efforts from Mastercard generate immense value responsibly and are built with integrity through the sounding governance structure, rigorous review processes, and an ethical commitment. AI is never static! Hence, the proactive and strategic approach of Mastercard shall always keep it ahead of the innovation curve within the financial industry.
