ISO 9001:2015

DATA ANALYTICS FOR NATIONAL PENSION SYSTEM OVERSIGHT REPORT INNOVATION WITH AI/ML TECHNIQUES

Sumana Chatterjee

Govt. of India, Ministry of Finance, Department of Expenditure have introduced a New Pension Scheme replacing the existing system with effect from 1.1.2004 and is applicable to all new entrants to Central Govt. service except to armed forces joining Govt. service on or after 1.1.2004. Newly joined NPS subscribers who don’t have NPS account i,e. PRAN (Permanent Retirement Account Number)number, submit CSRF forms(‘Common Subscriber Registration Form’) for the purpose of generation of PRAN number which is some unique number to maintain NPS account, all NPS related fillings, tax rebate, nominations, savings etc. Some newly joined NPS subscribers have their PRAN number already existing from before, they need to shift their PRAN number to the department, where newly joined with submission of ‘Inter Sector Shifting Form’(subscriber shifting form) .Our objective is to find the number of total NPS employee, joined within a certain month, certain quarter, how many PRAN numbers have been generated for these newly joined NPS subscribers, how many are yet pending to be generated, number of NPS employees whose PRAN have been generated within twenty (20) days and whose first NPS contribution started within time. Number of NPS employees whose nomination details, contact details are not available on NSDL CRA site, are to find out also. Time to time we have to download the CSV file, ‘subscriber_list.csv’ from NSDL CRA DDO-LOGIN, (DDO-Drawing and Disbursing Officer) to process all these NPS related data analytics, filtering and sorting of data to submit NPS oversight report on quarterly basis or when required to submit. The number of NPS employees submit ISS forms and shifted or pending to be shifted to this region, are to find out also. So here in this paper with the help of data analytics based on python code, executable on google collaborator platform, such analysis has been used to understand all these urgent insights.


DOI:

Article DOI: 10.62823/IJGRIT/03.01.7205

DOI URL: https://doi.org/10.62823/IJGRIT/03.01.7205


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