wumpy crypto

head of defi @3janexyz

@yieldsandmore @cozy_fnf

[Alea Research @AleaResearch]

1) On this Proof of Vision episode, Jacob Yakovsky (@_yakovsky), Founder at @3janexyz, joins our Director of Protocol Services @0xkmack. They discuss LCC, a new primitive where participants promise capital to 3Jane and stake 7.5% of the amount as margin, with part of the margin slashed and auctioned if the capital isn’t delivered, and how credit scores are used to underwrite those commitments. They also cover 3Jane’s pivot from FICO-based unsecured credit to warehouse facilities and forward flows for fintech lenders after 10/10, the Lenswift warehouse facility, the Slope forward flow, the USD3 senior and junior structure, Morpho curators, and the Q4 TGE target for the Jane token.

[3Jane @3janexyz]

3Jane has executed a $100m forward-flow agreement with @usesettle, a leader in inventory financing for U.S. CPG brands with >$4b originated

USD3 now funds 100+ brands and scales with Settle

Another major step toward a global, onchain ABS market

[3Jane @3janexyz]

Since inception, USD3 caps have filled almost immediately, leaving friends little chance to get upside

To change that, we're going live with our referral program

Earn 40% USDC APY on your promise to deposit into USD3. Refer creditworthy friends and you both earn more $JANE ↓

[wumpy crypto @wumpycrypto]

spotted this new oracle section by @Morpho in our new PT-USD3 / USDT market by @flowdesk_co

thank you to the morpho team for making oracle reading more intuitive for all users

[3Jane @3janexyz]

Banks make a lot of money using this one weird trick:

[ya3kov @_yakovsky]

Credit scores are core economic infra powering +$18T of household debt, but never scaled in DeFi. Unfunded commitments (promises) are a +$10T asset class meeting all preconditions for a global, cryptonative FICO to thrive, letting anyone on the web monetize their creditworthiness at scale:

[Stablecoin Intern @Degenerate_DeFi]

3Jane is the Hyperliquid of credit

they just cracked the crypto funding dilemma

[wumpy crypto @wumpycrypto]

fund your promise to 3jane by taking on debt

no prenegotiated financing facilities or legal contracts

just smart contracts allowing users to tap into a decentralized balance sheet of stablecoin liquidity when needed, governed by the markets utilization / risk parameters

[3Jane @3janexyz]

U.S. banks hold $11T+ in undrawn commitments. Promise looping is live on LCC, bringing fractional reserves to capital commitments in crypto

Earn promise fees on up to 6.25x your net worth: +7.8% APY on top of your DeFi assets deployed elsewhere, funded via @Morpho debt if called

[3Jane @3janexyz]

Introducing credit scores on @3janexyz x @cred_protocol

Reputation can now be collateralized to generate higher yield within DeFi, permissionlessly and at scale, starting with undercollateralized promises on LCC

[wumpy crypto @wumpycrypto]

@uhr3al @Cryptoyieldinfo cant see post

[wumpy crypto @wumpycrypto]

@anzep13 🫡

[wumpy crypto @wumpycrypto]

3jane and usdai are tackling the same problem in different sectors: tradfi loan originations stack on high fixed costs

the full lifecycle of structuring a loan slowly adds on costs at each step, which makes the final cost of capital for borrowers higher, without necessarily passing on returns to lenders

at 3jane, we're focused on leveraging technology and cryptonative advantages to compress fixed costs

things like automated reporting, programmatic tranching, agentic loan-level data reconciliation, etc., allow for fintech originators perpetually stuck with high costs of capital to access bespoke credit facilities with 3jane

the cost of capital savings doesn't come from mispricing the risk, but rather optimizing the full loan origination stack

[David | www.usd.ai @0xZergs]

One of the biggest misconceptions about the middle market for compute is that there simply isn’t enough capital. There’s a ton of capital! It’s more the shape of it and the covenants required that’s sticky.

The more interesting problem is the per-loan cost of getting capital there.

Every loan has a stack of costs:

Origination.
Underwriting.
Technical diligence.
Legal structuring.
Warehousing.
Settlement.
Distribution.

And each layer has a real dollar cost.

Talk to private credit funds and they’ll tell you that standing up a transaction can easily mean $3-5M of fees and internal/external costs before you even get to the cost of capital itself.

On a >$500M transaction, that can work.

On a $20M or $30M transaction, the unit economics start to look absurd.

Those costs do not disappear. They surface somewhere: higher interest rates, larger minimum deal sizes, tighter covenants, more equity required, or simply a decision not to do the loan at all.

That is why the middle market can look capital-starved even when there is plenty of capital interested in the underlying exposure.

The financing machinery was built for much larger transactions.

The interesting question, then, is whether the cost of creating a loan can itself follow a technology cost curve.

Do enough transactions and you stop treating each loan as a handcrafted project.

You start building infrastructure.

And once you can systematically reduce the cost of every hop, the minimum economically viable loan size falls, borrower pricing improves, and much larger pools of capital become accessible to the middle market.

That is where https://t.co/YA04elGZaK has been focused.

We are one of the few operators actually doing this at scale. We have roughly $500M of loans on our books by end of the next month and are on track to cross $1B by year-end- not one big billion loan but a lot of smaller <100m deals

But that $1B is not one giant transaction.

It is many dozens of loans.

And that matters.

Every loan is another training example.

Every underwriting process teaches you what can be automated.

Every origination teaches you where information gets lost.

Every legal structure teaches you what can be standardized.

Every settlement teaches you where latency can be removed.

Over time, more of that process moves from artisanal execution into software, agents, standardized workflows, and tech-enabled origination.

That is the moat.

We found product-market fit around the demand for compute credit.

The next question is how you turn execution into infrastructure, and infrastructure into a platform.

You only get there by actually doing the loans, and having the reinforcement training runs on these extremely detailed processes

Getting your hands dirty, seeing where the process breaks, encoding those lessons into the system, and then doing the next loan better than the last. Our first loan took 120 days, the latest took 21.

That is how the cost curve comes down.

And that is how a fragmented middle market becomes scalable. We have a few major product updates in pretty excited to get out there that lowers the per unit cost of loan economics for not just us, but for our capital partners as well.

[wumpy crypto @wumpycrypto]

3jane spotted

[KPK @kpk_io]

3/ Live with RWAs issued by @paretocredit, @3f_xyz, @MidasRWA with more issuers to follow.

Every market carries its own risk-adjusted exposure cap, so no single issuer can dominate the vault. The vault also targets ≥50% withdrawable liquidity at all times.

https://t.co/5bN2W4rg9H

[wumpy crypto @wumpycrypto]

tldr:

- 9.5% APY with @aave usdc exposure
- leverage a global, cryptonative balance sheet to generate commitment fees

[wumpy crypto @wumpycrypto]

net 9.5% APY starting w/ @aave usdc

pt 2 of a series on LCC, showcasing the power of running your own shadow bank

[wumpy crypto @wumpycrypto]

visibility lets committers estimate new USD3 supply-side liq.

ex:
- current supply-side liq. in yieldcoins (if it fits risk appetite)
- activity patterns of those wallets (if they’re likely to rebalance)
- hurdle rate (if rebalancing is worth it)