Sarvjeet Singh on how AI drives growth across the Group’s neobanking, brokerage and healthtech verticals

Sarvjeet Singh, Co-founder & Chief Managing Director of Finvasia, discusses how AI drives growth across the Group’s neobanking, brokerage and healthtech verticals, explains the cross-pollination between these fields and examines the potential of hands-free financial management.

Let’s start with the neobanking side of Finvasia’s fintech vertical. How does Jumpp, launched in 2025, leverage AI to solve customer problems and enhance the overall banking journey?

Jumpp is an AI-powered financial super app designed to streamline how users bank, save, pay, invest and borrow. It eliminates inefficiencies caused by using multiple financial apps by offering an all-in-one solution tailored to individual financial needs. Unlike traditional banking apps, Jumpp provides a hyper-personalised experience that adapts to each user’s behaviour and financial goals. One of the biggest challenges in digital banking is the language barrier, which limits financial inclusion. Jumpp solves this by delivering financial insights in a user’s preferred language, making digital banking more accessible and intuitive.

This allows users across diverse backgrounds to engage confidently with their finances, breaking down one of the biggest barriers to financial adoption. Jumpp addresses key gaps in neobanking by eliminating fragmentation, personalising financial recommendations and enhancing trust through transparency. AI plays a central role in creating a smarter banking experience. Conversational AI, powered by Large Language Models (LLMs) with Retrieval-Augmented Generation (RAG), enables users to ask questions like “How much did I spend last month?” and receive instant, data-driven responses. Predictive AI helps detect fraud, analyse spending patterns and proactively suggest savings strategies.

Explainable AI ensures transparency by showing users how financial conclusions are reached, increasing trust in AI-driven financial management. Jumpp leverages AI not just for transactions but for proactive financial guidance. The platform’s AI assistant, jAI, continuously analyses transaction history, spending behaviour and financial patterns to optimise payments, improve risk assessment and personalise financial recommendations. By integrating AI at every level, Jumpp is building an intelligent, secure and highly adaptive financial ecosystem that actively helps users achieve long-term financial stability.

On the brokerage side, Shoonya’s partnership with I Know First introduced AI-powered stock market predictions to your platform. How do these predictions improve on those made by traditional advisory services and what has been the response to them from your clients?

Shoonya’s partnership with I Know First introduced AI-powered stock market predictions, revolutionising how traders make decisions. Unlike traditional advisory services that rely on human interpretation, historical data and subjective biases, AI provides a real-time, systematic and data-driven approach. AI processes vast market data, recognising patterns and trends that human analysts might miss. By eliminating emotional biases, it ensures objective analysis and reacts instantly to market fluctuations, helping traders make informed decisions. The response from traders has been overwhelmingly positive. Many appreciate AI-driven signals for both short-term and long-term planning, allowing them to validate their own strategies and execute trades with greater confidence. Shoonya remains committed to integrating cutting-edge technology to empower investors with smarter, faster and more efficient decision-making tools.

Beyond predictions, what are the most transformative applications of AI in the brokerage industry? Are there untapped opportunities that could redefine the client experience or reshape market strategies?

AI is transforming the brokerage industry beyond market predictions by enhancing efficiency, personalisation and market intelligence. AI-driven onboarding automates KYC/AML compliance, reducing manual processing time while improving accuracy. Conversational AI enhances customer support by providing instant multilingual assistance and trade insights, making the trading experience more intuitive. AI also delivers personalised investment insights by analysing market trends, user behaviour and sentiment data to tailor strategies for traders. There are still more untapped opportunities that could redefine the client experience. AI-powered sentiment analysis can track news, earnings reports and social trends to quantify investor sentiment and predict market movements before they happen.

Real-time pattern recognition can detect high-probability trade setups across asset classes, providing traders with more precise entry and exit signals. AI-driven educational tools can simulate trading scenarios and assess risk behaviour, helping traders refine their strategies. AI is also reshaping market strategies by optimising trade execution through algorithmic trading and smart order routing. By predicting order book liquidity, AI improves pricing and reduces slippage. AI-driven risk management continuously monitors portfolio volatility and hedging opportunities, ensuring traders can manage risk more effectively. As AI advances, it will move beyond providing data to actively interpreting it, enabling traders to execute dynamically adaptive strategies that respond to market movements in real time.

We’ve already seen attempts to replace smartphones with AI-powered gadgets, like Humane’s AI Pin. Although the AI Pin ultimately failed, if such innovations gain traction, how do you think this shift in how customers interface with the digital world might reshape the entire financial landscape?

AI-powered devices like Humane’s AI Pin could revolutionise financial interactions by shifting away from app-based navigation toward voice-driven, predictive financial management. Instead of manually accessing banking apps, users would interact with AI assistants to manage transactions, check balances and receive real-time investment insights. Hands-free financial management would become the norm, where AI anticipates spending patterns, optimises payments and adjusts investment portfolios without direct user input. Payments could become fully automated, where AI reconciles transactions and proactively suggests budgeting adjustments before financial decisions are made. Security would also advance with biometric authentication and behavioural tracking, reducing fraud risks while making authentication more seamless. As embedded finance continues to evolve, AI could provide instant loan approvals, rate comparisons and seamless transactions through simple voice commands. Traditional banking and trading apps may eventually become obsolete as AI-powered financial ecosystems integrate seamlessly into everyday life. The future of finance is shifting toward proactive, AI-driven financial systems that optimise cash flow, minimise risk and anticipate user needs without requiring constant engagement.

Finally, as Finvasia operates at the intersection of healthtech and fintech, do you see advancements in one vertical influencing or inspiring innovation in the other? Are there significant opportunities for cross-pollination between these two fields?

The convergence of healthtech and fintech is transforming both industries by enhancing accessibility, affordability and efficiency. AI-driven health data analytics is improving financial planning, insurance modelling and credit assessments, while fintech solutions are making healthcare more affordable through digital payments, microloans and embedded financial services. One of the most impactful developments is in rural healthcare, where AI-powered diagnostics and remote monitoring are extending healthcare access.

Fintech plays a crucial role in this transformation by enabling payments through micro-financing, UPI transactions, digital wallets and insurance-backed financing, ensuring that financial constraints do not limit access to quality care. This convergence presents major opportunities. AI-driven risk assessment is reshaping insurance underwriting and credit scoring by integrating real-time health data, leading to more personalised policies and investment strategies. Embedded fintech in healthcare is streamlining medical payments through BNPL models, microloans and digital transactions, improving affordability for patients.

RegTech automation is enhancing secure transactions, data privacy and compliance processes for healthtech companies, while blockchain is ensuring transparency in medical billing, insurance claims and healthcare transactions. For consumers, AI-powered health insights are now shaping personalised financial planning. By analysing lifestyle and health data, financial institutions can offer tailored savings plans, lower insurance premiums and exclusive investment opportunities based on an individual’s health profile.

Healthcare affordability is improving through AI-powered credit assessments, instalment-based medical loans and flexible payment options, making essential treatments more accessible. Preventive health is also influencing financial behaviour, with financial institutions offering cashback rewards, lower interest rates or customised savings plans for users who maintain healthy lifestyles. By leveraging AI, digital transactions and real-time analytics, fintech and healthtech are creating a smarter, more inclusive financial and healthcare ecosystem. This integration benefits businesses looking to innovate in these fields while improving accessibility and efficiency for individuals managing both their financial and healthcare needs.

This article was first published in the April issue of GOLD magazine. To view it click here