Product & Technology Explainer

What is the ShuttleOne.Network

ShuttleOne Network is the platform connecting financial services for businesses with decentralized liquidity pool.
There are 2 parts of our network:
Decentralized finance system: Platforms and businesses can enable financial services within their ecosystems, providing added values to their existing system such as remittance and loan financing using decentralized infrastructure powered by ShuttleOne.
The ShuttleOne.Network liquidity pool: The liquidity pool acts as a fund to finance services that ShuttleOne is currently providing to real-world businesses in the infrastructure. Liquidity providers (LP) can add stablecoins into ShuttleOne.Network liquidity pool in order to receive an revenue generated by real world assets collateral and SZO tokens as reward.
ShuttleOne.Network in Trade Financing

On-Chain Risk Assesment: Risk Assessment Token (RAT, ERC721)

During the process of risk assessment and verification of cargo, ShuttleOne captures basic merchant information and tokenizes the merchants’ financial data and port operational data into a non-fungible token in RAT. RAT tokens data are stored on chain and can be easily verified by parties within the supply chain logistics platform from operations to finance.
  • Data Captured:
  • Master Bill of Laden
  • Customs Declaration
  • Packing List
  • Agent Agreement
  • Buyer/Seller Details
  • Invoice of Cargo
  • Other Logistics Operational Data

Compliance in Finance


Onchain Risk Management: Standard Scorecard

The hypothesis of the credit risk weighted model is as follows:
  1. 1.
    At any given random day towards maturity, the borrower has predicted ability to repay the trade financing
  2. 2.
    The methodology is a statistical model to predict quality outcomes of
a. Default
b. No-Default
  1. 1.
    Operational Data combined with Credit assessment of merchant provides an all round analysis of fiscal performance of credit and scoring
Let be the probability that the event occurring where , the the odd ration can be defined as
Odds= p/(1-p)
Therefore, the credit risk weighted model is as follows:
log⁡(Odds)=β0+β_1 x_1+⋯+ βnxn
The Weighted Evidence (WE) is utilized by applying operational data correlation using the Kolomogorov Smirnov (K-S) as a performance measure against standard deviation of the calculated parameters given a coefficient for confidence that risk governance will decide over a given period of time.
Thereafter, the score card can be calculated with the following:
Score=(A-B* β0+∑(-WEi *β_i)
  • Β -operational data regression coefficient of data attributes
  • β0-operational data regression intercept
  • WE-Weight of Evidence value for the given operational data
Operational Data is collected via platforms of operational partners where correlations between operational data of merchants are scored alongside standard deviation of cash flow analysis and weighted into a score percentage of a maximum of 1000 basepoints as a form of risk management combining not only credit cashflow analysis but also operational data of merchant in assessment for risk.
Aside from financial data and port operational data utilized for risk assessment, ShuttleOne also ensures process control and assessment to compliment these on-chain assessments as described below under Section 8.
Credit Application Token (CAT, ERC20)
Merchants’ data as risk assessed above are thereafter issued CAT token(s) according to the invoice of cargo requesting for credit.
The applying collateral is the Credit Application Token (CAT). It has the following metrics:
Addressable Yearly Cargo Assets: US$800mil Average Yearly Interest Rate (APY): 9% APY Trade Finance Tenure: 30 Days - 60 Days Estimated Average Trade Financing Ticket Size: US$50,000

Fiat On/Off Ramps

ShuttleOne works and partners with a range of Money Service Operators that are licensed in their respective countries to facilitate and act as collection points for fiat to digital tokens. With these, users, borrowers can easily and seamless cycle in and out of the network interacting with the products.
Last modified 7mo ago