Thinking Analytically: the case of Mr Shariff Uddin

I mentioned to someone recently that I believed analytics is an application using tools of a way of thinking. To think analytically is something that can be learnt/taught, and once you have that, tools don’t matter that much; hey you still need to know what questions to ask GenAI, no?

To give an example, I look at the case of Mr Shariff Uddin, a Bangladeshi author who was living and working in Singapore and recently left Singapore under less than clear circumstances.

Who is Mr Shariff Uddin?

Did you know that someone on a work permit authored (1) a book about his experiences as a work permit holder in Singapore, and won the prize for non-fiction in Singapore (2)

A fascinating, challenging and truly important book. Not only do we now at long last have access to the most sustained and authentic narrative and record of life and work as a Bengali migrant in 21st century Singapore, but also a genuine work of art in its own right. Sharif is an unprecedented and crucial voice in Singapore writing: perceptive, joyful, critical, constructive. With his characteristic modesty, he has something of moment to tell us and he does so from the heart beautifully.

– Richard Angus Whitehead, Lecturer, English Language and Literature Department, National Institute of Education

Mr Uddin has left Singapore. The aim of this blog is to explore his case using data-driven lens, and see what you think is the issue.

 

Background on the case

Things started falling apart early this year while Mr Uddin has been working in Singapore for 16 years. His employer started receiving threats from loansharks alleging Mr Uddin had borrowed money from them and failed to repay the debts.

From threats at the work place, things escalated to informing the other tenants of the work place, and eventually also to the home of the business owner and even to the business owner’s sister. (3)

There have been a few controversies in this case. The most interesting one was that Mr Uddin argued that the police and/or the Ministry of Manpower advised his employer to terminate his employment, as stated in his termination letter

“under police and MOM officer advice ... because of the troublesome bring along from your loan shark issue for us”(4)

Something the authorities vigorously denied (4). It turned out, something that is not contested, that the police officer whom the business owners talked to at Geylang Police Post as per this official Facebook post (5) “The officer, out of concern for her family’s and her well-being, also advised her generally that harassment would usually stop after the work pass of a foreign worker being harassed had been cancelled, and the worker no longer worked for the employer.”.

There has been some confusion whether the lady involved was the sister or daughter of the business owner was the person involved, as you can see the MoM refers to daughter (5) but the business owner says sister (3).

And importantly, the Police investigation found no evidence that Mr Uddin borrowed anything from loan sharks, hence the harassment was totally unfounded as Mr Uddin had been saying all along - Investigations eventually concluded with the authorities finding no evidence that Mr Sharif had borrowed money from unlicensed lenders. -(3)

I am not a social crusader so what does this case have to do with data?

What data?

Data does not mean just things on a spreadsheet, but pieces of information

1. Mr Uddin’s details (presumably including his work permit number and employer) were used to obtain a loan from a loanshark
2. the loan shark decided, as per usual practice, to harass the debtor where he/she can be damaged, here the place of employment
3. they went further by informing other tenants
4. they went even further and obtained information on where the sister of the employer lives, and caused harassment there. This is important, it is not the employer’s home but the sister’s.
5. Mr Uddin was terminated by his employer
6. Mr Uddin found a new employer who also received threats and as per the reports (3) only the first employer and MoM were aware of this new job offer
7. Mr Uddin found no other suitable alternative employment
8. At the expiry of his extended pass, he left Singapore.

 

Who dunnit?

This is kind of the information we have, so now the question is what is likely to be the most likely interpretation?

• Mr Uddin took a loan from a loanshark and fed the him/her information, he is responsible
• Mr Uddin took a loan from a loanshark with long arms and was hell bent chasing Mr Uddin out.
• One or more people with access to government systems leaked information
• Mr Uddin’s employer wanted Mr Uddin to leave Singapore

 

Actually…

Actually, I have no idea which is the correct interpretation, but I have a fairly good idea how this can be resolved. Since it is common for loansharks to obtain photocopies of NRIC/FIN/WP in order to give a loan, all parties have some reason to have access to the data.

The keys are

-        Address of the sister of the employer; the employer claims it is via her car plate number (LTA system)

-        Details of new employer of Mr Uddin

I have no clue who has access to what data in the government systems. In a nutshell:

• MoM databases should hold data related to employees and people on various passes in Singapore, and data on the change in the passes.
• ACRA should have access to directorships, including directors’ addresses, but not family members details.
• LTA should have access to car owners’ data, and that includes vehicles owned by both individuals and corporations and as such some information on company directorships, but not comprehensively.
• The Police force database should have access to multiple databases, or even copies of their data such as ICA who controls identity of everyone in Singapore

I assume that information is siloed, but even if it is not, access to information should be on need to now basis. And since this is considered PII, should fall under PDPA (although the government if exempted (6)), and at the very least all data requests for PII information should be logged and thus traceable.

Hence, to resolve the issue and find some justice for Mr Uddin, all that is required is the logs for say April onwards for the agencies above and understand who made requests for

• New employer of Mr Uddin
• Address of the sister of Mr Uddin’s previous employer

These 2 pieces of information should suffice in resolving the issues.

It is not rocket science, it is basic analysis.

 

Conclusion

There are 2 conclusions:

The case is closed, but to me some grey areas remain. They may not be of help to Mr Uddin, but intrinsically I believe it would be important to know what data in the various agencies has not been misused without detection.

It’s not very difficult to think of simple things analytically, is it?

1. https://www.landmarkbooks.sg/md-sharif-uddin
2. https://www.landmarkbooks.sg/store/p/stranger-to-myself
3. https://www.channelnewsasia.com/singapore/uddin-sharif-loanshark-hiap-seng-piling-construction-4385606
4. https://www.channelnewsasia.com/singapore/migrant-worker-fired-loan-sharks-bangladeshi-sharif-md-uddin-4247646
5. https://www.facebook.com/sgministryofmanpower/posts/784330097132347
6. https://www.straitstimes.com/politics/parliament-public-agencies-not-governed-by-pdpa-because-of-fundamental-differences-in-how