20240046607. IMAGE ANALYSIS MACHINE LEARNING SYSTEMS AND METHODS TO IMPROVE DELIVERY ACCURACY simplified abstract (Capital One Services, LLC)

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IMAGE ANALYSIS MACHINE LEARNING SYSTEMS AND METHODS TO IMPROVE DELIVERY ACCURACY

Organization Name

Capital One Services, LLC

Inventor(s)

Leeyat Bracha Tessler of Arlington VA (US)

Tyler Maiman of Melville NY (US)

Phoebe Atkins of Midlothian VA (US)

IMAGE ANALYSIS MACHINE LEARNING SYSTEMS AND METHODS TO IMPROVE DELIVERY ACCURACY - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240046607 titled 'IMAGE ANALYSIS MACHINE LEARNING SYSTEMS AND METHODS TO IMPROVE DELIVERY ACCURACY

Simplified Explanation

The disclosed technology is about using creditworthiness tokens issued in a blockchain network to assess and secure credit risk in response to specific financial events. The technology involves storing an issuance smart contract associated with an identity in a blockchain node device, sending an event query to an external oracle device, receiving event data associated with the identity from the oracle device, determining the number of creditworthiness tokens based on allocation parameters and the event data, and allocating the tokens to the identity via a wallet address.

  • The technology uses creditworthiness tokens issued in a blockchain network to assess and secure credit risk.
  • An issuance smart contract is stored in a blockchain node device, which includes a wallet address and allocation parameters.
  • An event query is sent to an external oracle device, requesting event data associated with the identity.
  • The oracle device responds with the event data.
  • The number of creditworthiness tokens is determined based on the allocation parameters and the event data.
  • The determined tokens are allocated to the identity via the wallet address.
  • The creditworthiness tokens can be transferred or collateralized, representing creditworthiness for the identity across financial institutions.

Potential applications of this technology:

  • Assessing and securing credit risk in financial transactions.
  • Streamlining creditworthiness assessment processes.
  • Facilitating secure and efficient credit transactions in a blockchain network.

Problems solved by this technology:

  • Simplifying the assessment and securing of credit risk.
  • Enhancing transparency and trust in credit transactions.
  • Reducing the need for intermediaries in creditworthiness assessment.

Benefits of this technology:

  • Improved efficiency and accuracy in credit risk assessment.
  • Enhanced security and privacy in credit transactions.
  • Increased accessibility to credit for individuals and businesses.


Original Abstract Submitted

the disclosed technology relates to assessing and securing credit risk using creditworthiness tokens issued in a blockchain network responsive to particular financial events. an exemplary blockchain node device may store an issuance smart contract associated with an identity and including a first wallet address and allocation parameters. an event query may be sent to an oracle device external to the blockchain network. the event query may include the identity. event data associated with the identity may then be received from the oracle device in response to the event query. a number of creditworthiness tokens is determined based on an application of the allocation parameters to the event data. the determined number of creditworthiness tokens is then allocated to the identity via the first wallet address. thereafter, the creditworthiness tokens can be transferred or collateralized, e.g., and can represent creditworthiness for the identity across financial institutions.

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