The finance sector has been grappling with significant data security issues, ethical concerns, and the complexities of complying with stringent regulations. AI offers solutions to these problems, but the industry has been cautious about adopting AI due to the sensitive nature of the data involved, potential ethical issues in AI-generated financial advice, and the overall challenge of navigating regulatory frameworks.
However, there is a gradual shift occurring.
When it comes to sifting through vast datasets, discerning current trends, and projecting potential shifts in market dynamics and customer behaviour, AI plays a crucial role. Fintech companies are discovering practical use cases for AI in these areas.
“For a fintech entity like BharatPe, AI is instrumental in running credit-scoring models that predict credit eligibility, especially for people with limited or no credit history,” said Ritesh Srivastava, Chief Data Scientist at BharatPe. He also emphasised how these algorithms work into unconventional data, including expenditure on necessities versus luxuries, and may even analyse social media activity or online shopping habits to build a comprehensive profile of a borrower’s financial behaviour.
This comprehensive understanding of financial behaviour helps in making informed decisions about loan offers and determining the appropriate loan amount. Additionally, for BharatPe, AI facilitates the delivery of personalised offers and communication to customers, aligning with the contemporary demand for individualised services in the digital age. This customer-centric approach represents a significant departure from the traditional product-centric approach of the past.
Srivastava has been with BharatPe since last year. The IIM-Bengaluru alumni have also served in important positions as Associate Director of data science at pharma company Novartis and Head of data and analytics at travel platform Yatra.
Inside BharatPe’s Data Science Team
BharatPe’s AI and analytics team, comprising 30 professionals, including 10 specialised in AI and ML, is pivotal in the organisation, contributing significantly to innovation and data-driven decision-making, involving close cooperation with data engineers, scientists, and domain experts, ensuring technical excellence aligns with business goals.
“We employ robust AI algorithms to analyse customer behaviour, identify patterns, and generate actionable insights for strategic decision-making, facilitating a deep understanding of customer purchasing patterns, identifying cross-selling and upselling opportunities and personalising our offerings,” said Srivastava.
BharatPe’s AI/ML-driven fraud and risk engine is adept at real-time prevention of anomalies and social engineering. Leveraging a diverse set of risk factors and social-behavioural parameters, the engine adapts autonomously to evolving threats. Real-time feedback enhances the engine’s deep learning capabilities, enabling it to recognise and fight historical patterns in future transactions.
He further added that agile development practices along with collaboration with product and engineering teams ensure scalability and robustness, vital for real-world conditions serving millions of users.
“To stay ahead in this evolving landscape, we’ve established a dedicated research team focused on AI, investing in continuous upskilling of our tech teams,” he added.
Decoding BharatPe’s Generative AI Progress
In terms of how generative AI has transformed operations at BharatPe, Srivastava said that it improved their capabilities by identifying undiscovered trends and influencing our business landscape.
“Its adoption is expected to bring notable transformations to various departments in our company, giving rise to specialised units focused on generative AI,” said Srivastava. These units will play a vital role in restructuring procedures for customer service products and addressing data gaps through the collection of unstructured data from diverse sources, with the added benefit of minimising biases in data analysis.
“Leveraging cloud-based infrastructure facilitates the quick scalability of systems to accommodate business growth so the integration of ML outcomes directly informs real-time decision-making processes,” he added.
The team is currently experimenting with different generative AI tools for enhanced market analysis and a deeper understanding of customer behaviour. These tools play a crucial role in market forecasting, enabling proactive anticipation of trends and informed planning for new products or technologies.
Talking about partnerships, even though Srivastava could not take any names due to confidentiality, he said that they are actively pursuing strategic collaborations and acquisitions with institutions and tech firms in the generative AI space to enhance our data analytics capabilities.
The post How BharatPe is Harnessing Generative AI for the Future of Finance appeared first on Analytics India Magazine.
