NEW YORK, Oct 4 (IPS) – Khalid Saifullah, Save Bangladesh USA Inc. researcher. The Bangla expression “taka pachar”, commonly used to refer to siphoning money abroad, is somewhat misleading. This is because Bangladeshi currency, Taka, is never taken out of Bangladesh. It’s useless anywhere else. What goes out is equivalence in foreign currencies, especially the US dollar. The technical term for these criminal activities is illicit financial flows (IFF). Mistakenly, IFF is sometimes referred to as money laundering, i.e. handling the proceeds of crime to disguise its illicit origin.
Money laundering and illegal fund transfers
Although there are some links between money laundering and IFF, they are not the same activity. The United Nations Office on Drugs and Crime defines money laundering as “the act of converting or transferring property to conceal or disguise its illicit origin or to assist another person, knowing that the property is derived from crime.” Define. ‘A person who engages in such offenses in order to avoid the legal consequences of his or her actions’.
On the other hand, illicit financial flows (IFF) refer to the illegal movement or transfer of funds or capital from one country to another. However, the source of such funds may not be illegal (e.g. corruption, smuggling).
In fact, there may be corrupt money involved in IFF, in the worst cases like in Bangladesh. Most of the billions of dollars taken out of the country were obtained through corruption and theft of public funds.
How do illegal fund transfers take place?
Approximately $3.15 billion flows illegally from Bangladesh every year. If the average person wants to travel abroad with hundreds of thousands of dollars, they can pocket it and take a plane, completely legally, as long as that amount is within the legal limits of that country. For example, you can legally export (or bring in) up to AUD10,000 out of Australia without having to declare it. In Bangladesh, it is only USD5,000.
But the cronies of Hasina’s kleptocratic regime extorted and transferred millions of dollars. According to a recent report, about $150 billion worth of funds were siphoned from the country during the 15 years of misrule of the kleptocratic Hasina regime. So they must have been carrying out highly illegal activities through legal channels. But how did it work?
Although it is very difficult to know for sure, it is believed that most IFFs occur through transactional misinvoicing or transaction-based money laundering. Let’s understand design with an example.
Let’s say you want to launder a million dollars. You or your accomplice is engaged in an import/export business. Let’s say you need to import 10,000 units of a product, each priced at $50. But instead of $50, we declare the unit value to be $150. By “securing” the support of some key figures within the authorities, you get the Bangladesh Bank to remit $1.5 million as payment for over-declared imports to a foreign company you set up for this purpose. You succeeded in paying the exporter $500,000 for the legitimate imports and in the process laundering the $1 million you were trying to get out of Bangladesh. You can do the same for exports, but in reverse. Of course, this is a simple example and there can be many creative variations on this threat.
There is reason to believe that this has happened a lot in the case of Bangladesh. why? First of all, Bangladesh has a vibrant export-import sector, which can make trade-based money laundering possible and difficult to trace. Second, many of Hasina’s close associates were involved in international trade. Third, Bangladesh stopped sharing detailed international trade data with the UN after 2015. Of course, there may be other explanations for this, but timing is nonetheless an issue. UN Comtrade, the world’s largest source of international trade data, has data for most of the world’s countries, but not for Bangladesh, which has the world’s eighth-largest population and 35th-largest economy.
You need detailed trade data
International trade data has the characteristic of being a two-sided account. Bangladesh’s exports of cotton T-shirts to the United States are also the United States’ imports of cotton T-shirts from Bangladesh. In reality there are a few different factors that come into play, but overall this is what it is. Users can easily compare international trade data and noticeable differences are immediately apparent.
It could be argued that this can still be done since the Bangladesh Bureau of Statistics (BBS), Export Promotion Bureau (EPB) and Bangladesh Bank (BB) all release external trade data. It may seem like it, but it actually isn’t. Without going into a lot of detail, the data published by these organizations lacks the detail needed for comparison. Their data is at an aggregated level and is not distributed in a similar way. EPB also does not release earnings data (probably not under EPB’s purview).
Then there is the issue of accuracy. A few weeks before Sheikh Hasina’s ouster, the BB revised its export data to say EPB’s figures were $10 billion higher than actual exports. Chief Advisor Muhammad Yunus recently promised to release accurate trade data in a public address. This is a much needed and welcome step. But that alone is not enough. We need the necessary details in our data so that we can compare it with data from our trading partner countries. In particular, you will need:
• Data by calendar year (January to December) as well as fiscal year. • Data by monthly frequency. • Classified by product code down to at least 6-digit HS (Harmonized System) level. There are approximately 6,000 HS 6-digit codes provided by the World Customs Organization (WCO). This code can specify the product with sufficient detail. • Product description. • Analysis by trading partner (ISO code for import country of origin, ISO code for country of last export destination). • Classification by country of delivery (ISO codes for third countries through which the goods may have passed). • Mode of transport (sea, air, road, rail, etc.). • Classification by customs procedure code (for what purpose the goods are imported or exported). • Classification by trade flow (exports, imports, re-exports, etc.) • Value (on board basis for exports and on cost, insurance and freight basis for imports), net weight and quantity.
Towards Modernization and Automation of Financial Intelligence
Accurate, timely and detailed transaction data is important for analyzing erroneous transaction invoices, but is not sufficient to completely prevent money laundering. What we need is the overhaul and automation of financial intelligence itself.
The backbone of these automated systems must be the Business Register (BR). BR is literally a register of all companies in a country. The core component of BR is a unique identifier. Each business or corporation is assigned a unique ID. Once established, businesses must use this ID for all types of activities, from setting up bank accounts to making transactions.
BR may include many other information about your business, including size, sector, economic activity, etc. Thanks to its unique identifier, BR can be used to link data from different domains, such as linking trade data with corporate and banking activities.
Considering the trove of linked data available from customs declarations, banks and other sources (much of which cannot be released to the public due to confidentiality), that information, thanks to statistical modeling and machine learning, can be used to build highly intelligent and sophisticated systems. Can be used. and artificial intelligence that can flag suspicious activity in real time. What I mean is, something has to be “off” in a transaction involving money laundering, and there has to be technology to detect it.
The very existence of such a system acts as a powerful deterrent and can significantly reduce money laundering problems. Building this level of data capacity will, of course, require investment. But with the estimated $150 billion laundered by Sheikh Hasina’s kleptocratic regime, the return on investment seems very attractive.
Khalid Saifullah He is an experienced statistician with 14 years of experience working in international organizations.
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