Transaction classification based on transaction time predictions

A non-transitory computer readable medium comprising instructions to be executed in a computer system, wherein the instructions when executed in the computer system perform a method for predicting a transaction time based on user position data, the method comprising:

• obtaining a transaction record associated with a user, the transaction record comprising a transaction description;
• obtaining one or more user positions associated with the user, wherein each user position comprises a timestamp;
• obtaining one or more business records associated with each respective user position of the one or more user positions, wherein an establishment corresponding to each business record associated with a respective user position is within a threshold range of the respective user position;
• calculating one or more similarity scores, wherein each similarity score of the one or more similarity scores is based on a similarity between a respective business record of the one or more business records and the transaction record;
• associating the transaction record with a business record of the one or more business records based on a maximum similarity score of the one or more similarity scores;
• and
• determining a predicted transaction time for the transaction record based on at least a timestamp of a user position associated with the business record associated with the transaction record.

A computer system, wherein system software for the computer system is programmed to execute a method for predicting a transaction time based on user position data, the method comprising:

• obtaining a transaction record associated with a user, the transaction record comprising a transaction description;
• obtaining one or more user positions associated with the user, wherein each user position comprises a timestamp;
• obtaining one or more business records associated with each respective user position of the one or more user positions, wherein an establishment corresponding to each business record associated with a respective user position is within a threshold range of the respective user position;
• calculating one or more similarity scores, wherein each similarity score of the one or more similarity scores is based on a similarity between a respective business record of the one or more business records and the transaction record;
• associating the transaction record with a business record of the one or more business records based on a maximum similarity score of the one or more similarity scores;
• and
• determining a predicted transaction time for the transaction record based on at least a timestamp of a user position associated with the business record associated with the transaction record.