Global Fintech Interview with Sudhir Jha, Mastercard SVP and Head at Brighterion

Hi Sudhir, please tell us about your journey in the technology industry. How did you arrive at Brighterion?

I have always been passionate about technology products. I started my career as a software developer but soon moved into product management, which allowed me to envision and define new products. I spent nearly nine years at Google, where I was first exposed to AI and started using it to solve complex problems — in particular, payment fraud management and ads policy enforcement. After that I got the opportunity to lead the AI platform business for Infosys and build AI applications for multiple verticals. When Mastercard was looking for a leader to expand its AI-based initiatives and leverage Brighterion assets to build compelling solutions for its customers, I was excited to take up the challenge.

Could you tell us more about your role and responsibilities at Brighterion? How is it associated with Mastercard’s global identity?

I am the global head of Brighterion and lead the team to build innovative AI solutions for our customers. Brighterion’s AI technology powers many of Mastercard’s internal solutions like Decision Intelligence, Safety Net, and Smart Authentication. We also build AI solutions directly for our customers; for example, Credit Risk Management, Acquiring Fraud Management, and Customer On-boarding. Brighterion is part of AI & Security Solutions, and the wider Cyber & Intelligence division at Mastercard, a global team of data scientists, cybersecurity experts, product engineers, identity solutions architects and AI specialists, who work every day to secure and protect the payments ecosystem and develop and scale trusted solutions with security at the forefront.

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How has the global fintech market changed in the last 2-3 years? How has the pandemic influenced the fintech market?

The global financial market was already on a rapid digitalization journey before the pandemic. Some of it was driven by customer needs and operational efficiency, but a large part was also to compete effectively with new entrants who were using their digital infrastructure to upend the incumbent players. The COVID-19 pandemic made digitalization a necessity and accelerated the journey even more. This has underscored the criticality of digital identity, online risk management, multi-channel payment ecosystem – all of which has been a focus of our team and Mastercard for last few years.

Tell us why financial companies should take regulations and compliance more seriously.

The direct financial impact of not taking regulations and compliance seriously is the fines associated with each violation. These fines can be very large, sometimes in the hundreds of millions of dollars. But there are even greater reputational costs. Every time a financial institution gets caught for violating regulations, it gives customers and investors more reasons to switch their business. Finally, many regulations are designed to make financial transactions fair and secure. These protect customers and financial institutions have a responsibility to do their absolute best for their customers. So, it is in their own best interest to take regulations and compliance very seriously and prioritize upfront and ongoing investments.

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What are the major compliance-related pain points that most companies default on? How does Brighterion help such companies meet compliance benchmarks?

Gathering and managing customer data to facilitate financial transactions can be quite complex and can create several compliance issues for companies. This gets even more challenging for companies that operate in multiple geographies due to specific regulations. The other complexity comes from linked financial transactions inside and outside one financial institution. While each transaction by itself may not pose any compliance issue, combined with other transactions in the chain can be extremely risky. Many companies struggle to connect related transactions and entities within their organization due to fragmented nature of how data and events are managed. Brighterion and Mastercard provide solutions for each of these areas. We also offer options for companies to leverage our network to offload many tasks which reduces the need for internal data collection and management.

The ethical use of data should be a top priority for FIs as they look to grow and succeed. Could you elaborate more on this?

Data has become a key differentiator in the world dominated by AI-based solutions and optimizations. AI systems need extensive data to build models and more data often means more accuracy in predictions. But how a company uses data and what kind of decisions are made with the data become critical in ensuring trust and fairness. Customers often like the convenience that companies can provide using their data, like personalization, seamless navigation, automated actions, etc. But they are also becoming very sensitive to misuse or unethical use of data as is being recently seen in the backlash over social media companies. Businesses are constantly being asked to set high standards for themselves. Companies need to make ethical (and transparent) use of data the cornerstone of their digital transformation and growth strategy. Otherwise, they will end up paying a very high price down the road when their products/services will be considered too toxic for the society.

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Please explain the ethics behind managing data and banking technology such as AI and machine learning. How can FIs embed ethical standards into their business practices to protect themselves from regulatory and compliance disaster?

An ethical AI system must be inclusive, explainable, have a positive purpose, and use data responsibly. Businesses that want to remain competitive in the digital age and retain customer trust and talent need to prioritize these standards in their use of AI. This starts with monitoring for bias during the data intake, auditing, training and deployment process of AI models. Over time, bias can be introduced as AI models are retrained – therefore, businesses need to ensure that bias does not exist in new data sets and in training techniques. Data engineering teams can prevent training bias by flipping data attributes, leveraging holistic data sets, and incorporating explainability. This allows businesses to ensure fairness and inclusion at each stage of an AI model to proactively prevent compliance issues.

Which domains within the financial technology marketplace are you keenly following and why?

Customer onboarding and digital identity, credit risk management and payment fraud management are the areas of direct interest to Brighterion. We believe them to be essential for creating a safe, secure, and inclusive financial ecosystem. They also are a natural fit for AI-based innovation, and we are hoping to play a significant role in bringing solutions to market that are built using the highest ethical standards. A seamless customer onboarding process built on top of a secure digital identity network can accelerate the expansion of financial market and reduce cost of operations. Advanced and efficient credit risk management can not only reduce cost of credit but can also allow access to capital to a wider set of people and businesses and can go a long way in expanding financial inclusion. And real-time effective fraud management will increase trust in online payment ecosystem and reduce fraudsters’ attacks as it will become less rewarding. We are working actively to achieve all these goals at Brighterion.

Thank you, Sudhir! That was fun and we hope to see you back on globalfintechseries.com soon.

[To share your insights with us, please write to sghosh@martechseries.com]