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Corruption starts when a government employee deviates from the law and favors someone out of the way. It could be either for the financial benefit or the power or sometimes both.

Unfortunately, in Pakistan, this practice has engulfed the entire governmental procedures to the extent that sometimes, even the cleanest practices are also considered shady due to the extra load corrupt practices have put on every single employee.

Then how to start to end this?

There is a way around, as the technology is becoming smarter and Artificial Intelligence (AI) is playing role effectively across the globe, Pakistan can take advantage to streamline everything once for all.

All over the world, AI has proven to be more efficient in computing large pools of data. Giants like Google and Facebook use AI to organize and maintain big data so why not us? Why not use cloud computational techniques and big data processing to end this menace of corruption?

In Jan 2018, researchers from the University of Valladolid (Spain) created an Artificial Intelligent (AI) system that can predict the areas that have a higher risk of corruption. A similar system can be established in Pakistan too.

We can evolve to make a similar system by just starting with the following;

Create and Maintain Organized Database

1- Payroll data of all government employees currently stored in “Project for Improvement to Financial Reporting & Auditing” (PIFRA) System should be complete, correct and CNIC based as opposed to PIFRA account number.

2- There shouldn’t be more than one PIFRA account number assigned against a unique CNIC. Income other than the salary should explicitly be mentioned to keep the record of all known sources of income of every govt. employee.

3- Financial records of all the govt. employees, including bank account details, as well as the details of dependants, should clearly be listed in the database. CNIC and/or CRC (B-Form) based data of all dependents of every Government employee should be maintained, after cross verification from NADRA.

4- Complete Service history and data regarding transfers, postings and take home salary should also be included.

How This Data Will Help To Detect Corruption?

Digitizing such information in a database will help better organize data, and with the help of preset protocols, AI will be able to flag where the corruption occurs in the system.

1- With a large pool of data from various platforms, AI will be able to cross check the already registered data to every govt employee. For instance, Data from Land Revenue Management Information System (LRMIS) could be used to check the sale and/or purchase of property against CNIC of Government Employee or any of his/her dependents.

2- Other than this, Artificial Intelligence will also help keep a smooth flow in maintaining financial data by having access to State Bank’s Financial Monitoring Unit (FMU) and checking account balance of all bank accounts of every Government Employee and his/her dependents to ensure transparency.

3- Moreover, Data from Tenants Registration System could be pulled every month to check if any Government Employee or his/her dependent is showing up as the owner of a rented property.

4- Similarly, data from excise and taxation will help detect whether any govt employee or his/her dependent is showing up as owner of how many vehicles and if it exceeds the payroll of the employee, AI induced system will mark corruption instantly.

5- It would also be easy to keep a check on abroad travels by any govt. employees or his/her dependents by pulling out data from FIA.

With systems talking to systems, a report that identifies individuals presumed to be living beyond declared sources of income is easy to generate. But it is equally important that this aggregated data is not abused by individuals who have access to it. In this regard, it is proposed that Artificially Intelligent Bots may be used to generate this encrypted data-anomaly report every month and send it to concerned individuals, with the highest level of clearance, who could decrypt the data.

On the other hand, there should be a timeframe within which these individuals can digitally correct previously submitted information and/or add new Information. After the expiry of the allotted time, those still on the data-anomaly radar may be called in to explain the reasons for the reported anomaly, before deciding their fate.

image credit: share.america.gov

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