CreditorNetCase Management System

CreditorNet System Components
  • Cases: These are the different types of cases which are dealt as case management.
  • Status: Status signifies the stage of the system.
  • Outside Servicer: This case management system will provide services irrespective of the site.
  • Security/Password: Authentication details for the system.
  • Lender Portal: One who will manage and invest for the system.
  • In-House Service: Providing services within the portal.
  • Loss Mitigation (portals): Loss mitigation is used to describe a third party helping a homeowner, a division within a bank that mitigates the loss of the bank
  • OS: Windows
  • Server Side Language: ASP.Net
  • Client Side Technology: Java Script, Jquery
  • Architecture: MVC
  • URL:

CreditorNet system is a case management system designed to facilitate the communication and management, by a collection company or a law firm of mortgages in default/foreclosure.

It displays varied client data in a managed way, which in turn helps client to search, filter and analyze the data.

This application consists of a windows parser which imports client’s data and stores it in relative tables using a web service, after parsing it according to format specified by the client. Client can schedule this parser with the help of Windows Scheduler.


Client was facing issues in managing his credit and debt data and also a timely communication was a great miss. May it be a mortgage company, a law firm or a collection company, handling data accurately has always been a challenge. It was a challenge for us too, to automate the whole process.

We had to parse the encrypted flat files containing very complex set of records. The challenge was to keep the web application functional while the other part of the application downloading, parsing and dumping all the data into the database.

Another challenge was to minimize the response time of the application while processing and rendering huge data payload.


We used a windows Parser to import client’s data and to store it in relative tables using a web service. Using a scheduler client can filter data accordingly.

We created schedulers for the first problem. Also we used asynchronous calls to REST api in order to load the data into reports on web page.


We divided the app in several components to make things easily accessible. Response time of the application was also reduced.

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