Authored By Mithil Sejpal, Co-Founder, SLIQ
Lending Innovation Is No Longer Just About Speed
When people talk about innovation in lending, the conversation usually revolves around speed. How quickly can a loan be approved? How fast can funds be disbursed? How little paperwork is required? These are visible improvements, but they are not the most important change underway. The real transformation in lending is infrastructural.
Artificial intelligence and automation are rebuilding the operating system of credit. They are turning products that were once operationally cumbersome into seamless digital experiences. In the process, they are unlocking categories that have existed for years but remained underused because the customer experience was too complex.
Loan against securities is one of the clearest examples.
The Technology Paradox of Loan Against Securities
From a credit standpoint, Loan against securities should be among the most efficient products in the market. When a borrower pledges existing financial assets such as mutual funds, listed shares, or life insurance policies, the lender benefits from collateral-backed risk, and the borrower typically receives lower interest rates than on unsecured credit.
On paper, the product has always made sense. In practice, adoption has lagged.
That gap reveals an important truth about financial products, the biggest barriers are often not economic, but operational.
For years, loan against securities involved multiple disconnected processes. Identity verification, asset valuation, lien marking, documentation, and disbursal all required coordination across different systems and institutions. Even when the borrower had strong collateral, accessing credit could take days.
In finance, convenience often outweighs logic. Many investors chose to redeem mutual funds or take expensive personal loans simply because those options felt easier.
That is the problem technology is now solving.
AI Is Solving the Orchestration Problem
One of the most significant contributions of AI in fintech is not credit scoring. It is orchestration.
The challenge in lending is rarely a single decision. It is coordinating dozens of interdependent actions in the correct sequence, while minimizing manual intervention. AI and automation can now validate customer data, assess collateral quality, detect exceptions, generate documents, and trigger the next step in the workflow in real time.
What previously required several handoffs, and multiple days can increasingly be completed in a matter of hours. But the more meaningful breakthrough is predictability.
Borrowers gain a more transparent and consistent experience. Lenders can scale operations without increasing headcount at the same pace. And the product becomes practical for mainstream adoption.
India’s Asset Base Is Creating a Massive Opportunity
This shift is particularly relevant in India, where the underlying pool of financial assets has grown dramatically. According to the Association of Mutual Funds in India (AMFI), the Indian mutual fund industry’s assets under management stood at ₹80 lakh crore as of March 2026, nearly six times higher than a decade ago. The number of mutual fund portfolios reached 27.39 crore, reflecting the rapid expansion of retail participation.
This growth has created a large base of investors who own financial assets that can potentially serve as collateral. At the same time, recent regulatory changes have made loan against securities more practical. Updated norms have enabled loan-to-value ratios of up to 65% against equity mutual funds and 85% against debt mutual funds, increasing the amount of liquidity borrowers can access against their holdings.
India’s Real Challenge Is Collateral Utilization
Yet despite these structural tailwinds, Loans Against Securities remain a fraction of their potential. In my view, India does not have a credit access problem alone. It has a collateral utilization problem.
Millions of investors hold substantial financial assets, but very few think of those assets as an active source of liquidity. Investments are viewed purely as long-term wealth creation tools, rather than as instruments that can also support short-term funding needs.
This is where technology changes customer behaviour, not just operational efficiency
From Processing Loans to Guiding Decisions
Modern lending platforms are becoming increasingly contextual. Instead of merely processing applications, they can help borrowers identify more efficient choices.
A customer considering the redemption of mutual funds, for instance, can be shown that pledging those units may provide the required liquidity while preserving long-term compounding. That is a fundamentally different role for technology.
It is no longer just enabling credit. It is helping consumers make better financial decisions
The Next Wave of Fintech Will Be Intelligence-Led
The first wave of fintech focused on making credit accessible. The next wave will focus on making credit intelligent. Intelligent credit is not just faster. It helps consumers borrow in ways that are more cost-effective, more transparent, and less disruptive to long-term wealth creation.
Loan against securities is well positioned to benefit from this shift because its value proposition was always strong. What it lacked was a technology layer capable of making the experience simple enough for mass adoption. That gap is closing.
The Future of Borrowing
The most important innovation in lending may not be a new product category. It may be the technology that makes existing products dramatically easier to understand and use.
When that happens, borrowing becomes more than a transaction. It becomes a smarter financial decision.
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