Traditional online lending systems are like dolls tightly grasped by the central bank—once a ban is issued, the entire ecosystem collapses because they rely on banking channels and the judicial system to survive. But DeFi on public blockchains is different—once protocol code is on-chain, regulators can't shut it down, at most they can block fiat on-ramps and off-ramps. On-chain transactions continue to run as usual; Tornado Cash still operates after sanctions, which is proof that code is the law.

But I have to be honest: technological autonomy sounds appealing, yet in reality, oracles are manipulated, cross-chain bridges frequently have vulnerabilities—these new risks are more complex than traditional financial human governance issues and are often hard to prevent.

Risk control is even more interesting. An 80% bad debt rate in traditional online lending is basically shooting oneself in the foot. Income proofs can be forged, social data can be fabricated, and debt collection involves dealing with 22 languages—a tangled mess. DeFi uses over 150% collateralization and smart contracts for automatic liquidation, turning risk management from manual to mathematical models. It sounds perfect, but there are pitfalls—when collateral prices plummet, chain reactions of liquidations can trigger cascades of liquidations that are even more brutal and merciless than bad debts, causing systemic risk to spike instantly.

Localization is key. India’s 600 million mobile users do not equal 600 million active users with borrowing capacity. Just like some public chains boast millions of addresses, 90% are just spam bots or fake accounts. Traditional finance makes money through interest rate arbitrage; on-chain projects replace this with algorithmic interest rates, but they are easily manipulated by large capital—remember the high-yield trap of Anchor Protocol before LUNA? It fooled many people. True localization isn’t just copying and pasting; it must integrate with local realities. For example, India’s UPI payment system, combined with a small on-chain lending protocol, could be far more effective than simply copying China’s consumer loan model.

In summary, traditional finance’s human-driven risk control walls are fragile in multicultural environments, while crypto builds trust through mathematical models—yet it can over-rely on technology and overlook human nature. The teams that truly make money are those that understand local needs and know how to leverage on-chain technology, not just external players who copy with a single click. Code is law, no doubt, but culture is the true operating system.