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ISLAMABAD: The Federal Board of Revenue (FBR) has admitted that the tax machinery lacks the capacity to analyse big data to detect tax evasion.

According to a report of the FBR, the functional data bridges have been established with provincial revenue agencies and other state departments across the nation such as banks/ NADRA/ SECP/ PITB/ AGPR/ SBP/ I-LINK/ TELCOS, and Punjab Land Record.

However, the FBR lacks the capacity to analyse big data to detect tax evasion.

It said that the development of ICT infrastructure and a well-resourced data analysis and research unit to integrate and analyse big data with adequate data security can pave the way for enhancing the capacity of the organisation.

DG I&I-IR starts separating cases of tax evasion and money laundering

The FBR reforms have focused on the integration of third-party databases of NADRA, SBP, AGPR and the provincial governments with FBR’s centralized databases and a single system for filing of sales tax returns for the federal and provincial taxes.

The FBR has been analysing various reform interventions such as simplification, technological access, facilitation and communication, automation of business processes, effective compliance controls and enforcement of taxpayer obligation and institutional development to increase efficiency and accountability.

The FBR is innovating to maximize the quality and efficiency of its services. In keeping with the Government policy of enhancing automation, the FBR is enhancing its digital services to make them increasingly available to all taxpayers and traders. Realignment of all ICT services with a special focus on security, user interfaces with taxpayers and tax collectors, analytics and a comprehensive Management Information System (MIS) is the need of the hour, the FBR report added.

Copyright Business Recorder, 2023

Comments

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Hilarious Mar 28, 2023 10:51am
Begin with your own officers first, then the federation, then the provinces rather than burden the 3% that actually pay taxes you dumb unqualified smooth brained swines.
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