Distributed ledger technology utilizing cardless payments

A computing system, comprising at least one memory and at least one processor, configured to:

• receive, a sample from an individual using a sensor, the individual associated with a payment account at a provider institution, wherein the sensor is at least one of a fingerprint sensor, a facial recognition sensor or camera, an iris sensor, a hand sensor, or a sound sensor;
• compare the sample with a dataset stored on a distributed ledger network;
• identify, utilizing a first model trained to identify particular samples, the sample is a particular sample;
• determine, utilizing a second model trained to identify particular individuals based on the particular sample identified and outputted by the first model, that the sample matches an enrolled sample of the dataset, wherein each of the first model and second model corresponds to at least one of an artificial intelligence model or a machine-learning model trained to output indicating a match between the sample and the enrolled sample;
• in response to determining that the sample matches the enrolled sample, generate a cryptogram based on an encryption key and a payment instrument identifier of the payment instrument, wherein the cryptogram is unique to the sample and the cardless transaction request, wherein each cryptogram is associated with at least one sample of a plurality of samples of the dataset, wherein the cryptogram is a new cryptogram unique to the cardless transaction request based on the cardless transaction request and the sample;
• and
• execute a transaction processing application to process a cardless transaction request utilizing the cryptogram, wherein processing comprises transmitting the cardless transaction request comprising the cryptogram to a computing device associated with the provider institution.

One or more non-transitory computer-readable storage media having instructions stored thereon that, when executed by at least one processor, cause the at least one processor to:

• receive, a sample from an individual using a sensor, the individual associated with a payment account at a provider institution, wherein the sensor is at least one of a fingerprint sensor, a facial recognition sensor or camera, an iris sensor, a hand sensor, or a sound sensor;
• compare the sample with a dataset stored on a distributed ledger network;
• identify, utilizing a first model trained to identify particular samples, the sample is a particular sample;
• determine, utilizing a second model trained to identify particular individuals based on the particular sample identified and outputted by the first model, that the sample matches an enrolled sample of the dataset, wherein each of the first model and second model corresponds to at least one of an artificial intelligence model or a machine-learning model trained to output indicating a match between the sample and the enrolled sample;
• in response to determining that the sample matches the enrolled sample, generate a cryptogram based on an encryption key and a payment instrument identifier of the payment instrument, wherein the cryptogram is unique to the sample and the cardless transaction request, wherein each cryptogram is associated with at least one sample of a plurality of samples of the dataset, wherein the cryptogram is a new cryptogram unique to the cardless transaction request based on the cardless transaction request and the sample;
• and
• execute a transaction processing application to process a cardless transaction request utilizing the cryptogram, wherein processing comprises transmitting the cardless transaction request comprising the cryptogram to a computing device associated with the provider institution.