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The financial services industry, long known for its stringent regulations and complex operations, is undergoing a transformative shift with the integration of generative artificial intelligence(GenAI). Startups are leading the charge, leveraging GenAI to redefine customer-facing operations, from onboarding to query resolution and service delivery. As adoption of these technologies accelerates and costs decline, the potential for scalability and efficiency is capturing the attention of both fintechs and traditional financial institutions.
The Rise of Agentic AI in Customer Support
Large banks and financial institutions have traditionally relied on human agents to power their contact centers and backend support teams, incurring significant operational costs. However, agentic AI is emerging as a game-changer, automating routine tasks and enabling firms to scale operations without proportionally increasing headcount. Ganesh Gopalan, CEO of Bengaluru-based Gnani AI, a conversational AI startup backed by InfoEdge Ventures, highlights the transformative potential of these technologies. “Our models can reduce costs for financial services by 40-50% while handling routine tasks,” Gopalan told Economic Times. “If a client serves 50,000 customers today, our solutions allow them to scale fivefold without hiring additional agents.”Startups like Gnani.ai, Arya.ai, Yellow.ai, and Hyperface are at the forefront, building tailored AI solutions for various financial service categories. From credit card issuance to loan processing and customer acquisition, these models are already live or under deployment, offering a glimpse into a more efficient future for the sector.
Redefining Voice and Chatbots with GenAI
Voice bots and chatbots are not new to the financial services landscape, but GenAI has elevated their capabilities to new heights. Unlike their predecessors, which relied on outdated machine learning models, today’s bots are smarter, faster, and capable of conversing in natural, human-like voices. This evolution is driven by enterprise solutions from global leaders like OpenAI and Microsoft, which are being customised to meet the specific needs of financial institutions. Rashid Khan, co-founder of Yellow AI, a startup backed by Lightspeed and Westbridge Capital, emphasises the enhanced capabilities of these bots. “Our AI models focus on accuracy, low latency, and human-like interactions,” Khan said. “They’re being used for card issuance support, loan processing, customer acquisition, and claims-related queries.”For instance, Hyperface, another Bengaluru-based startup, has deployed a model to assist customers of a fintech app who have yet to activate their accounts. The startup is also working with a bank to streamline credit card issuance, showcasing the practical applications of GenAI in real-world scenarios.
Big Players Take Notice
The potential of GenAI is not lost on larger financial institutions. Bajaj Finance, one of India’s largest non-banking financial companies, recently acquired a 12% stake in Protectt.ai, a mobile security firm, signalling its interest in AI-driven innovation. Similarly, in April 2024, banking technology provider Aurionpro acquired Arya.ai to integrate AI solutions into its offerings for banking clients. This growing interest underscores the massive opportunity for GenAI in financial services. According to a June 2024 Tracxn report, India is home to 44 GenAI companies specialising in speech and voice recognition, with 25 of them securing funding. Startups like Sarvam, Uniphore, and Augnito are also contributing to this vibrant ecosystem.
Challenges in the Path of Adoption
Despite the enthusiasm, deploying GenAI in financial services is not without hurdles. Integration with legacy banking systems and navigating stringent regulatory requirements pose significant challenges. Arjun Malhotra, General Partner at Good Capital, points out that “regulatory compliance, including ISO 27001 and GDPR standards, remains a primary obstacle. The evolving regulatory framework for AI in collections adds uncertainty to deployment timelines.”Moreover, the risk of “AI hallucination”—where models generate inaccurate or misleading responses—raises concerns about accountability. Ramanathan RV, CEO of Hyperface, notes, “AI hallucination is real, just as human agents can mis-sell products. If a bot is manipulated by a customer or makes an error leading to financial loss, industry-wide deliberations are needed to address these risks.”Industry experts also anticipate that the Reserve Bank of India (RBI) will soon release broader guidelines to provide clarity and boost confidence in AI investments. Such a framework could accelerate adoption and ensure responsible use of these technologies.
The Road Ahead for GenAI in Financial Services
The cost of running GenAI models in India is currently comparable to employing contact centre staff. However, the scalability of AI offers a distinct advantage over traditional call centres. “AI models can be scaled exponentially, unlike human-led operations,” Ramanathan explains. This scalability, combined with declining costs, positions GenAI as a cornerstone of future financial services. For small and medium enterprises (SMEs) in the fintech space, partnering with AI startups presents a unique opportunity to enhance customer experiences while optimising costs. As the technology matures and regulatory frameworks evolve, the collaboration between startups and financial institutions is poised to reshape the industry.