Many people have fallen into the same pit while working on on-chain interest rates: chaotic standards, sample bias, and too much noise, leaving everyone uncertain. The solution provided by Treehouse is to create a kind of 'public benchmark' for interest rates, called DOR (Decentralized Offered Rates). It is not a snapshot of a single data source, but a synthetic result based on multi-party observations, verifiable samples, and published methodologies. Taking Ethereum as an example, TESR will use the actual block rewards of validators as samples, setting observation periods, annualization methods, and denoising processes, with panelists staking tokens to submit observations. Errors will be minimized, and the synthetic curve and submission records can be audited. The benefits of this approach are threefold: developers obtain a unified baseline that can be referenced, institutions can incorporate interest rates into risk control and pricing, and ordinary users will no longer be misled by comparisons such as 'Protocol A annualizes at 10% vs. Pool B annualizes at 7%'.
This 'interest rate bus' does not serve just one market. DOR encourages the formation of benchmark families: staking, lending, and re-staking each have their own sub-curves, with a unified standard first before discussing risk premiums. On the implementation side, Treehouse incorporates latency, availability, and back-testing consistency into service levels, with both the front-end and contracts included in security audits; on the governance side, who can become a panelist, how to expand the sample, and how to handle anomalies all follow on-chain processes with traceability. In summary, it is about upgrading 'I think it's this much' to a 'on-chain synthetic, auditable, and forfeitable' reference interest rate.
Focusing on practical application, the protocol connected to DOR can anchor the lending curve to TESR/TELR, while adding its own risk premium; market making and clearing can use DOR for hedging and discounting; RWA and derivatives can be treated as a discount baseline to reduce mismatch. To assess whether it is 'useful', we don't look at popularity, but rather four metrics: the number of active DORs and their citation frequency, end-to-end latency and availability, methodology update frequency, and the concentration of panelists and their penalty records. As long as these four items remain stable and improve, the issue of interest rates will shift from a 'war of words' to an 'engineering problem'.
@Treehouse Official #Treehouse $TREE
