Oracle Financial Services Software Limited

Shubham Negi

Veresh Jain

Rahul Yadav

Mridul Kumar Nath

Rahul Kiran Gaddam

Phanindra Choda

Krishna Sameera Ellendula

Abhishek Anand

Systems, methods, and other embodiments associated with identifying a document type of an unidentified document based on image features are described. In one embodiment, image pairs are formed by pairing the unidentified document with anchor images from a plurality of anchor images, wherein each anchor image is a known document type. For each image pair, first visual features are extracted from the unidentified document and second visual features are extracted from the paired anchor image. A similarity function is applied to compare the first visual features and the second visual features, and a similarity score is generated for each image pair based on the comparing. The most similar anchor image from the image pairs, which has a greatest similarity score, is identified. The document type of the unidentified document is then predicted as the known document type associated with the most similar anchor image.

Framework for identifying documents

Method includes obtaining sample records from dataset associated with user and including records associated with identifiers customers of user; executing first clustering using sample records, to obtain first set of clusters for first identifiers associated with sample records, first clustering using features associated with first identifiers; providing visualization of first set of clusters; determining whether user input for optimizing first set of clusters provided in visualization is received; when user input for optimizing first set of clusters is not received, determining first information related to first set of clusters as final result information; when user input for optimizing first set of clusters is received: executing second clustering using sample records, to obtain second set of clusters for first identifiers, second clustering using features associated with first identifiers, and determining second information related to second set of clusters as final result information; and clustering entire dataset using final result information.

Data segmentation using clustering

According to an aspect, a technology system maintains an account data specifying the details of multiple accounts including a specific set of accounts as being delinquent. Upon receiving a feature set to be used, the system clusters the multiple accounts into groups based on the feature set. The system generates a multi-classification model for assignment of agents to the accounts based on the group qualifiers associated with the groups and the feature set. The system then identifies a target group likely to present problems with debt collection, assigns, using the multi-classification model, a corresponding agent for each account of the group and determines a recommended recovery strategy for each assignment. The system provides the details of the group, the corresponding agents assigned and the recommended recovery strategy for each assignment.

Technology system for assisting financial institutions in debt collection

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Bilaspur, India

Shubham Negi