Automatic document source identification systems
A document source identification system includes one or more memory devices storing instructions, and one or more processors configured to execute the instructions to cause the system to receive uploaded document(s) having at least one extractable data entry. The system may categorize the document, and extract at least one data entry from the document. The system may normalize each extracted data entry and execute a deterministic ID search to determine that the normalized data entry matches zero, one, or more than one account data entries associated with user accounts. Responsive to an exact match, the system may link the uploaded document to a user account associated with the matching data entry. Responsive to zero or multiple matches, the system may execute a probabilistic ID search identifying a highest ranked user account data entry and link the document to a user account associated with the highest ranked user account data entry.
1 . A document identification system comprising:
one or more processors; and
a memory in communication with the one or more processors and storing instructions that, when executed by the one or more processors, are configured to cause the system to:
receive a first uploaded document having a first document type of a plurality of predetermined document types;
extract first data entries from the first uploaded document based on the first document type, the first data entries comprising a first sensitive data entry comprising personally identifiable information;
identify a data entry type associated with the first data entries at least in part based on one or more of a first proximate location of the first data entries in the first uploaded document, a presence of one or more additional extractable data entries, or a second proximate location of the one or more additional extractable data entries;
determine a corresponding field associated with each of the first data entries based on a comparison between a plurality of stored user account data entries and the first data entries;
execute a deterministic identification search, comprising:
identifying a first subset of user account data entries, wherein each user account data entry in the first subset of user account data entries being associated with an existing user account; and
determining, based at least in part on the corresponding field, whether a percentage of the first data entries matches user account data entries in the first subset of user account data entries; and
in response to determining the percentage of the first data entries match user account data entries, link the first uploaded document to a first existing user account associated with the matching user account data entry in the first subset of user account data entries.
2 . The system of claim 1 , further comprising:
executing a probabilistic identification search to identify a highest ranked user account data entry in the first subset of user account data entries responsive to determining that the first data entries matches zero or more than one user account data entries in the first subset of user account data entries; and
linking the first uploaded document to the first existing user account associated with the highest ranked user account data entry in the first subset of user account data entries.
3 . The system of claim 2 , wherein executing the probabilistic identification search further comprises:
scoring each user account data entry in the first subset of user account data entries using a random forest machine learning classifier; and
identifying the highest ranked user account data entry in the first subset of user account data entries.
4 . The system of claim 1 , wherein at least one of the first data entries comprises a verifiable data entry corresponding to a verified data source, and the system is further configured to verify, based on communication with the verified data source, the verifiable data entry and wherein the verifiable data entry comprises a user's street address.
5 . The system of claim 1 , wherein the system is further configured to:
receive a second uploaded document having a second document type of the plurality of predetermined document types;
categorize the second uploaded document in a second document category based on the second document type, the second document category indicating the presence of at least a second sensitive data entry comprising additional personally identifiable information, the personally identifiable information of the first sensitive data entry and the additional personally identifiable information of the second sensitive data entry each comprising a bank statement entry, a tax return entry, a social security number, or a driver's license entry;
extract at least one of the first sensitive data entry or second sensitive data entry from the second uploaded document; and
tokenize the extracted at least one of the first sensitive data entry or the extracted at least one of the second sensitive data entry.
6 . The system of claim 5 , wherein categorizing the second uploaded document further comprises using a deep learning machine library.
7 . The system of claim 1 , wherein the plurality of predetermined document types comprises bank statements, tax returns, social security cards, and driver's licenses.
8 . The system of claim 1 , wherein extracting the first data entries from the first uploaded document further comprises utilizing optical character recognition.
9 . The system of claim 1 , wherein a first data entry used to identify the first subset of user account data entries comprises one or more of a full name associated with an existing user account, a social security number associated with the existing user account, and a soundex of the full name.
10 . A document identification method comprising:
receiving a first uploaded document associated with a first user account having a first document type of a plurality of predetermined document types;
extracting first data entries from the first uploaded document based on the first document type, the first data entries comprising a first sensitive data entry comprising personally identifiable information;
identifying a data entry type associated with at least one of the first data entries at least in part based on one or more of a proximate location of the at least one of the first data entries in the first uploaded document, a presence of one or more additional extractable data entries, or a proximate location of the one or more additional extractable data entries;
determining a corresponding field associated with the at least one of the first data entries based on a comparison between a plurality of stored user account data entries and the first data entries;
executing a deterministic identification search, comprising:
identifying a first subset of user account data entries, wherein each user account data entry in the first subset of user account data entries being associated with an existing user account; and
determining, based at least in part on the corresponding field, whether a percentage of the first data entries matches user account data entries in the first subset of user account data entries; and
in response to determining the percentage of the first data entries match user account data entries, linking the first uploaded document to the first user account associated with the matching user account data entry in the first subset of user account data entries.
11 . The method of claim 10 , wherein the plurality of predetermined document types are each associated with a corresponding document category, the method further comprising:
determining a first document category corresponding to the first document type.
12 . The method of claim 10 , wherein the at least one of the first data entries comprises a sensitive data entry, the method further comprising tokenizing the sensitive data entry before identifying a data entry type associated with the at least one of the first data entries.
13 . The system of claim 1 , wherein identifying the first subset of user account data entries from the plurality of stored user account data entries further comprises using a machine learning model trained to rank and select from the plurality of stored user account data entries.
14 . The method of claim 12 , wherein the tokenized sensitive data entry is temporarily stored in RAM to secure the sensitive data entry.
15 . The method of claim 10 , further comprising:
executing a probabilistic identification search to identify a highest ranked user account data entry in the first subset of user account data entries responsive to determining that the first data entries matches zero or more than one user account data entries in the first subset of user account data entries; and
linking the first uploaded document to the first user account associated with the highest ranked user account data entry in the first subset of user account data entries.
16 . The method of claim 15 , wherein executing the probabilistic identification search further comprises:
scoring each user account data entry in the first subset of user account data entries using a random forest machine learning classifier; and
identifying the highest ranked user account data entry in the first subset of user account data entries.
17 . The method of claim 10 , wherein at least one of the first data entries comprises a verifiable data entry corresponding to a verified data source, and the method further comprises verifying, based on communication with the verified data source, the verifiable data entry and wherein the verifiable data entry comprises a user's street address.
18 . The method of claim 10 , wherein extracting the first data entries from the first uploaded document further comprises utilizing optical character recognition.
19 . The method of claim 10 , wherein the plurality of predetermined document types comprises bank statements, tax returns, social security cards, and driver's licenses.
20 . The system of claim 5 , wherein the tokenized first sensitive data entry is temporarily stored in RAM to secure the first sensitive data entry.