Deal room platform using artificial intelligence
In embodiments, a method for managing documents in an electronic deal room associated with a document-intensive activity, the method comprising: receiving, by a processing system of a deal room platform, a request to upload a document to the electronic deal room from a user device associated with a user participating in the deal; receiving, by the processing system, the document from a document source; determining, by the processing system, a classification of the document based on one or more features of the document and a machine-learned document classification model that is trained to classify documents involved in document-intensive activities; identifying, by the processing system, one or more folders of an organizational structure having a plurality of folders corresponding to the electronic deal room based on the classification; and associating, by the processing system, the document with the one or more folders.
1. A method for managing documents in an electronic deal room associated with a multi-party transaction, the method comprising:
receiving, by a processing system of a deal room platform, a request to upload a document to the electronic deal room from a user device associated with a user participating in the multi-party transaction;
in response to an approved request, receiving, by the processing system, the document from a document source;
determining, by the processing system, a classification of the document based on content of the document and a machine-learned document classification model that is trained to classify documents involved in multi-party transactions by comparing content of a document with content of documents having known classifications;
identifying, by the processing system, one or more folders of an organizational structure having a plurality of folders corresponding to the electronic deal room with which to associate the document based on the determined classification of the document;
at least one of automatically creating a link or automatically storing, by the processing system, the document with respective ones of the one or more folders, based on the determined classification of the document; and
providing at least one of a notification of one or more risks associated with the multi-party transaction or a prediction related to the one or more risks on at least one of a user device or a graphical user interface.
2. The method of claim 1 , wherein the machine-learned classification model is trained on a plurality of training data sets, each training data set including one or more documents.
3. The method of claim 2 , wherein each training data set includes at least one labeled document, wherein the label indicates a respective classification of the labeled document.
4. The method of claim 2 , wherein one or more training data sets of the plurality of training data sets are obtained from historical data associated with the deal room platform.
5. The method of claim 4 , wherein the historical data includes classifications of previously uploaded documents that were uploaded to the deal room platform in connection with other multi-party transactions.
6. The method of claim 2 , wherein one or more training data sets of the plurality of training data sets are obtained from an expert that labeled the at least one labeled document of each of the one or more training data sets.
7. The method of claim 2 , wherein a training data set of the plurality of training data sets includes feedback data relating to a previous classification of a previously uploaded document that was classified by the system, wherein the feedback data is used to reinforce the machine-learned classification model.
8. The method of claim 2 , wherein the machine-learned classification model is trained using a training data set of the plurality of training data sets that includes one or more unlabeled documents.
9. The method of claim 8 , further comprising training the machine-learned classification model based on the one or more unlabeled documents and one or more labeled documents, wherein each respective labeled document is labeled with a respective classification of the respective labeled document.
10. The method of claim 9 , wherein training the machine-learned classification model includes clustering the one or more unlabeled documents with the one or more labeled documents based on respective features of the one or more unlabeled documents and the one or more labeled documents to determine respective classifications of the unlabeled documents.
11. The method of claim 2 , further comprising training the machine-learned classification model based on respective results of natural language processing of each document in the plurality of training data sets.
12. The method of claim 1 , wherein the multi-party transaction is one of a merger, an acquisition, a financing, or an investment round.
13. The method of claim 1 , wherein the machine-learned classification model classifies different types of contracts associated with a type of the multi-party transaction.
14. The method of claim 1 , wherein the machine-learned classification model classifies different types of documents having no contractual components associated with a type of the multi-party transaction.
15. The method of claim 1 , further comprising:
identifying, by the processing system, one or more content segments of the document;
for each content segment:
extracting, by the processing system, one or more features of the content segment; and
determining, by the processing system, a content classification of the content segment based on the one or more features of the content segment and a machine-learned content extraction and classification model that is trained to identify one or more different types of content segments.
16. The method of claim 14 , wherein the classification of the document is based at least in part on at least one of the content classifications.
17. The method of claim 14 , further comprising generating an advisory memo using a natural language generation system based on a content classification corresponding to one of the content segments.
18. The method of claim 16 , wherein the advisory memo includes a location in the document where the content segment to which the content classification corresponds is located.
19. The method of claim 16 , wherein the advisory memo includes the content segment to which the content classification corresponds.
20. An apparatus for managing documents in an electronic deal room associated with a multi-party transaction, comprising:
a processor; and
a memory having stored therein at least one program, the at least one program including instructions which, when executed by the processor, cause the apparatus to perform a method, comprising;
receiving, by a processing system of a deal room platform, a request to upload a document to the electronic deal room from a user device associated with a user participating in the deal;
in response to an approved request, receiving, by the processing system, the document from a document source;
determining, by the processing system, a classification of the document based on content of the document and a machine-learned document classification model that is trained to classify documents involved in multi-party transactions by comparing content of a document with content of documents having known classifications;
identifying, by the processing system, one or more folders of an organizational structure having a plurality of folders corresponding to the electronic deal room with which to associate the document based on the determined classification of the document; and
at least one of automatically creating a link or automatically storing, by the processing system, the document with respective ones of the one or more folders, based on the determined classification of the document; and
providing at least one of a notification of one or more risks associated with the multi-party transaction or a prediction related to the one or more risks on at least one of a user device or a graphical user interface.