The AI Advantage: How Prithvi Chandrasekhar Harnessed Machine Learning to Transform InCred and Beyond

In the realm of artificial intelligence (AI) and machine learning (ML), few leaders boast the depth and breadth of expertise that Prithvi Chandrasekhar brings to the table. As the President and Head of Consumer Business at InCred, a leading Indian fintech player, Prithvi has been at the forefront of harnessing data science to drive transformative business outcomes. His journey from pioneering early AI/ML adoption at Capital One to spearheading InCred‘s meteoric rise offers a masterclass in the art and science of building data-driven organizations.

The Capital One Years: Pioneering Data Science at Scale

Prithvi‘s tryst with AI/ML began during his tenure at Capital One, where he held several leadership roles across the company‘s US and International Consumer businesses. As the Head of Data Science for Capital One‘s US Card division, Prithvi led a team of over 100 data scientists, engineers and analysts tasked with leveraging advanced analytics to drive customer acquisition, engagement and risk management.

Under Prithvi‘s leadership, the team developed a suite of cutting-edge ML models that transformed the way Capital One approached credit decisioning, fraud detection and marketing optimization. For instance, his team built a deep learning-based credit scoring engine that outperformed traditional scorecards by 15-20%, enabling Capital One to extend credit to millions of underserved customers while maintaining industry-leading loss rates.

Prithvi‘s team also pioneered the use of ML for real-time fraud detection, building a multi-layered system that combined rules-based filters, anomaly detection and graph neural networks to spot and prevent suspicious transactions with sub-second latency. The system processed over 1 billion transactions per day and saved Capital One over $100 million in annual fraud losses.

On the marketing front, Prithvi‘s team developed a suite of ML-powered tools for hyper-personalized offers and dynamic pricing. By analyzing terabytes of customer data across demographics, transactions, and interactions, these tools enabled Capital One to deliver the right offer to the right customer at the right time, driving a 25% lift in response rates and a 15% increase in customer lifetime value.

Scaling AI at InCred: A $1B Growth Story

In 2016, Prithvi made the bold decision to return to his native India and join InCred as the President and Head of Consumer Business. At the time, InCred was a nascent startup with just 20 employees and a vision to reimagine lending for India‘s underserved consumers and small businesses.

Over the next 5 years, Prithvi played an instrumental role in scaling InCred into a 8,500 crore ($1.1B) NBFC powerhouse with over 1,500 employees. Central to this growth story was Prithvi‘s relentless focus on building a world-class AI/ML team and embedding data-driven decision making into every aspect of InCred‘s business.

One of Prithvi‘s first initiatives was to build a bespoke credit scoring engine for InCred‘s personal loan business. With limited historical data to work with, Prithvi‘s team leveraged alternative data sources like utility bills, social media footprints and mobile usage patterns to develop a ML model that could accurately assess risk for thin-file and new-to-credit customers. The model enabled InCred to approve 40% more loans while maintaining a sub-2% NPA rate, well below the industry average of 5-7%.

Prithvi also led the development of InCred‘s AI-powered collection platform, which used natural language processing (NLP) and behavioral analytics to intelligently route delinquent customers to the most effective collection channel and agent. The platform enabled InCred to improve collection efficiency by 30% while reducing collection costs by 25%.

Beyond credit, Prithvi‘s team built a suite of AI/ML solutions to drive operational efficiency and customer experience across InCred‘s business. For instance, they developed a computer vision-based KYC (Know Your Customer) system that could automatically verify customer documents in real-time, reducing onboarding time from days to minutes. They also built a ML-powered chatbot that could handle 80% of customer queries without human intervention, freeing up InCred‘s support staff to focus on more complex issues.

The Road Ahead: AI as a Force for Good

Looking to the future, Prithvi is excited about the potential for AI/ML to not just drive business outcomes, but to also address societal challenges and drive positive social impact. He believes that by leveraging data responsibly and ethically, companies like InCred can play a vital role in expanding financial inclusion and empowering underserved communities.

To that end, Prithvi is actively exploring ways to use AI/ML to make credit more accessible and affordable for India‘s 60 million micro, small and medium enterprises (MSMEs). These businesses are the backbone of India‘s economy, but often struggle to access formal credit due to lack of collateral or credit history.

Prithvi‘s team is working on a ML-powered credit assessment tool that can analyze alternative data sources like GST (Goods and Services Tax) filings, bank statements and business transactions to generate credit scores for MSMEs. The tool is currently being piloted with a select group of MSME customers and has shown promising results in terms of expanding access to credit while maintaining healthy portfolio quality.

Beyond financial inclusion, Prithvi is also passionate about using AI/ML to tackle pressing issues like climate change and healthcare access. He serves as an advisor to several startups in these domains and is actively exploring ways to leverage InCred‘s data and analytics capabilities to drive positive impact.

Lessons for Aspiring Data Science Leaders

For aspiring data science leaders looking to follow in Prithvi‘s footsteps, here are some key lessons and best practices to keep in mind:

1. Focus on business impact, not just technical sophistication: While it‘s important to stay up-to-date on the latest AI/ML techniques, Prithvi believes that the most effective data science leaders are those who can translate these techniques into tangible business outcomes. This requires a deep understanding of the business domain and close collaboration with cross-functional stakeholders.

2. Invest in data quality and governance: AI/ML models are only as good as the data they are trained on. Prithvi emphasizes the importance of investing in robust data quality and governance frameworks to ensure that data is accurate, consistent and secure. This includes implementing data validation checks, data lineage tracking and access controls.

3. Build diverse and inclusive teams: Prithvi is a strong believer in the power of diversity and inclusion to drive innovation in data science. He has made a conscious effort to build teams that are diverse across dimensions like gender, ethnicity, academic background and industry experience. He believes that diverse teams bring a wider range of perspectives and ideas to the table, leading to better outcomes.

4. Embrace explainable and ethical AI: As AI/ML models become more complex and opaque, Prithvi believes that it is critical for data science leaders to prioritize explainability and ethics. This means developing models that can be easily understood and interpreted by stakeholders, and that are aligned with ethical principles around fairness, transparency and accountability.

5. Foster a culture of continuous learning: Finally, Prithvi believes that the most successful data science leaders are those who foster a culture of continuous learning and experimentation. This means encouraging team members to stay up-to-date on the latest AI/ML advancements, providing opportunities for skills development and knowledge sharing, and creating a safe space for experimentation and failure.

Conclusion

Prithvi Chandrasekhar‘s journey from pioneering early AI/ML adoption at Capital One to driving InCred‘s transformation into a data-driven fintech powerhouse is a testament to the transformative potential of data science. His success offers a blueprint for aspiring data science leaders looking to harness the power of AI/ML to drive business outcomes and social impact.

By combining technical expertise with business acumen, and by fostering a culture of continuous learning and experimentation, Prithvi has demonstrated that data science can be a powerful force for good. As the AI/ML landscape continues to evolve at a rapid pace, his insights and best practices will become increasingly valuable for organizations looking to stay ahead of the curve.

At a time when the world is grappling with complex challenges across domains like finance, healthcare and climate change, leaders like Prithvi offer a ray of hope. By leveraging data responsibly and ethically to drive positive change, they are charting a path towards a more inclusive, sustainable and equitable future. As we look ahead to the next frontier of AI/ML innovation, it is leaders like Prithvi who will light the way.