Why AI is an enabler, not a disruptor, at PB Fintech

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Insurtech platform PB Fintech has steadily made generative AI, or GenAI, the cornerstone of its technology and business strategy over the past two years, using it not just to accelerate execution and improve productivity but also to uncover new growth opportunities, all while keeping customer value front and center, according to Joint Group Chief Executive Officer Sarbvir Singh.

The company’s journey with GenAI has gone beyond just experimenting with cutting-edge tools, Singh said in an interview with MIT Sloan Management Review India.

In the past two years, he said, the AI tool has begun shaping how the parent of digital insurance marketplace Policybazaar and lending platform Paisabazaar thinks about and executes strategy across teams and business lines.

“AI-driven development is accelerating our overall build cycles and enabling faster execution,” Singh said, describing how the company has moved toward decentralizing application programming interface (API)-driven problem solving as a necessary precursor to scaling solutions organization-wide.

He said PB Fintech now relies on fine-tuned, open-sourced models to resolve complex issues with speed and accuracy, while still keeping humans in the loop to ensure quality and accountability.

“We’re steadily progressing toward deeper automation while maintaining oversight,” Singh said, emphasizing that customer value remains top priority.

A key area where GenAI is already proving critical is in risk and fraud detection. Singh outlined how real-time anomaly detection, biometric authentication and deepfake identification are now part of the company’s toolkit to identify risks early.

Beyond this, he said, PB Fintech is also deploying the technology in emerging areas such as marketing and customer engagement, creating opportunities to expand into segments and markets the company hadn’t explored before.

Singh described the technology as a strategic enabler rather than an existential disruptor. “It allows us to tackle challenges and uncover opportunities that traditional technologies simply can’t,” he said.

He pointed out that integrating GenAI has already automated several business processes, reduced turnaround times, and improved customer experiences in measurable ways.

PB Fintech follows what Singh called a “risk-aware” approach to deploying GenAI, with an emphasis on internal testing before customer-facing rollouts.

All models are developed and validated in-house, usually using human-in-the-loop frameworks that incorporate feedback into iterative refinements.

The company also favors open-source models hosted on-premise, which Singh said gives PB Fintech more control over compliance, intellectual property exposure, and data security.

The shift to GenAI is also reshaping how the company thinks about its people. PB Fintech has invested in structured upskilling programs for its technology and product teams to help them work more effectively with AI-driven processes.

“It’s about doing more with less while meeting growing business demands,” Singh said, calling it a mindset that the company is instilling across teams.

On ensuring that technology initiatives stay aligned with customer value and business outcomes, Singh said every GenAI use case is jointly owned by business and technology teams, mapped to specific metrics such as turnaround time, customer satisfaction, or issuance times.

New implementations are A/B tested to measure their impact before full deployment. “Customer value always comes first,” he said. “We’ve found that business outcomes follow naturally when customer experience improves.”

GenAI is even helping PB Fintech design entirely new business lines. Singh cited the example of using deep learning models in motor insurance, where vehicle inspections that used to take days or weeks are now completed in minutes by scanning more than 40 attributes and flagging issues instantly.

He said the company is also using GenAI to detect emerging customer patterns and preferences, which in turn is driving discussions with insurers about potential new products and services.

But Singh cautioned that technology alone doesn’t guarantee results.

“GenAI’s effectiveness depends entirely on the quality, accessibility and integrity of the underlying data,” he said, noting that PB Fintech’s existing data lake architecture and ML pipelines have been instrumental in supporting its AI ambitions.

An internal AI leadership council oversees adoption to ensure governance and conduct security assessments.

Rather than create a standalone GenAI team, PB Fintech has embedded responsibility across business and tech teams, supported by an AI governance unit that ensures guardrails and keeps technology costs justified.

Singh also said the company remains mindful of ethical risks. Models are trained on diverse datasets to minimize bias, he said, with decisions ultimately made by humans and AI offering recommendations and insights.

Summing up PB Fintech’s approach, Singh said: “For us, customer value has always been the primary driver. Business outcomes follow when the customer experience improves.”