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There is a common blind spot in the DeFi ecosystem that most participants are not truly aware of. Many focus solely on the accuracy of data—believing that as long as the price or parameters are calculated correctly, the system is safe. But reality often hits hard.
During volatile market swings, liquidations are usually triggered at the most extreme points; when liquidity dries up, trades still proceed as usual. The numbers on the books look fine, but in practice, it can lead to disaster. In post-mortem reviews, people habitually blame bad luck. Little do they realize, the real problem isn’t there—it's that a crucial layer of judgment is missing behind the data.
This brings us to the role of oracles. Most oracles in the industry operate with a very simple and crude logic: you ask for a price, and I give you a number. The smart contract needs real-time BTC prices? It gets a number. Needs market data for ETH? It gets a number. End of story. But what’s completely overlooked here is: is it really safe to operate based on this number now? Is the timing right? Is the market environment stable? Is the data support solid enough? The attitude of ordinary oracles toward all this is simply—remain silent.
Solutions like APRO do something entirely different. They don’t just passively report numbers; they break the silence. Instead of a bare number, they provide a data package with confidence signals. Simply put, they explicitly tell you: “This price is reliable right now, you can use it with confidence,” or conversely, “The market is a bit chaotic at the moment, handle this data cautiously.” These confidence signals are not just decorative labels—they are the actual basis for the contract to call and execute operations.
This subtle difference fundamentally changes the entire system’s behavior logic. Imagine if you can only get a number and have no idea about the underlying market conditions—what would the contract do? It would have to design protections for the worst-case scenario: increase margin requirements, add larger risk buffers, slow down risk response times. While this can reduce misoperations, what’s the cost? System efficiency drops significantly, capital utilization suffers, and user experience worsens. But in an environment of information asymmetry, it’s common practice to prefer false positives over risking a failure.
But now, things are different. Once you can see through the confidence behind the data, the strategy library opens up immediately. When market volatility isn’t too high, liquidations don’t have to happen all at once; they can be broken into multiple steps, providing more buffer space for the market. During periods of high uncertainty, immediate decisions aren’t always necessary—delaying a few seconds for final confirmation costs almost nothing but greatly enhances safety. The system shifts from a fragile, stress-reactive state to a more resilient, adaptable flexible structure.
This change may seem technical, but it actually reflects an upgrade in the entire DeFi risk control logic—from relying solely on numerical accuracy to a multi-dimensional assessment of market environment and data quality. The role of oracles evolves from passive data reporting mechanisms to active risk assessment helpers. What does this mean for the ecosystem? It signifies healthier risk management, more stable system operation, and a more sustainable market environment.
Of course, having confidence signals doesn’t mean everything is foolproof. The core still depends on whether this mechanism can truly operate effectively in practice and whether it can significantly reduce systemic risks in extreme situations. But at least in terms of concept and design philosophy, this marks a meaningful correction to the current industry status quo.