The absolute majority of large financial companies on the African continent and the Arabian Peninsula now use technological automation tools as the main technique for monitoring fraud and economic and financial crime.

A PWC study carried out last year with various financial institutions in the Arabian Peninsula highlights interesting elements if we question the best practices in terms of AML-FT (Fight against money laundering and the financing of terrorism) in Arabic-speaking countries. According to a statement in the same report:

"Technology is proving to be a powerful ally. [...] 82% of respondents agree that the use of technological solutions in real-time monitoring strengthens anti-fraud measures. "

The automation of monitoring processes has many advantages. It allows institutions to reduce the impact of controls on the customer experience while filtering transactions. These filters are necessary to meet regulatory requirements and also to limit reputational risks.

However, it is worth examining some of the specific challenges faced by Arabic-speaking and/or economically emerging countries in terms of AML-FT and KYC compliance control.

Automated checks are usually performed on the basis of a patronymic name and a first name. It is then possible to add to this a second layer of verification based on secondary identifiers.

This may seem relatively manageable in Western countries where natural persons have a surname and one or more first names clearly defined by the civil registry and transcribed uniformly on all their official documents. However, this approach presents some specific challenges for Arabic-speaking and emerging countries:

Some surnames are derived from the names of peoples, tribes and ethnicities and therefore extremely widespread in some regions.

It happens that some individuals are designated by their religious or royal title (EPP profiles) rather than by their name and surname on their identity papers in certain regions of sub-Saharan Africa (Haj, Customary Chief... etc.).

There is no international universal concordance table between the Arabic alphabet and the Latin alphabet. As long as an individual presents proof of identity in Arabic and that the transcription in the Latin alphabet is done manually, nothing prevents Mr. Jamal XYZ from falling through the cracks because his first name will have been spelled Djamel. The same reasoning can also be extended to the transcription of patronymic names as well as to that of company names.

According to the Columbia Encyclopedia, there are more than 150 million Muhamad, Mohammed, M'hamed etc... in the world while this name has only one spelling in Arabic. This presents two challenges. First, as long as this name is associated with a common surname, this can have the impact of significantly increasing the number of "false positive" alerts generated by filtering solutions. Secondly, it is important to take into account all existing spellings so as not to miss a proven alert.

 The practice of declaring births shortly after they have occurred is not common around the world and it may happen that some people do not have single dates of birth and their identity papers mention several different ones or that they are assigned January 1 as the default date of birth. The use of dates of birth as a secondary identifier is therefore not the ideal solution in all cases.

The attribution of a surname in some countries of the Arabian Peninsula as well as some countries of sub-Saharan Africa is not necessarily done according to a fixed surname. It is possible to meet people whose name is based on filiation and therefore changes with each generation. This is usually expressed by the use of the prefixes ben,bin,ibn,ould,bint,bent...(son/daughter of) or then abu, abou, bu, um, Oum... (father/mother of...). These spellings are obviously unique in the Arabic alphabet but can be transcribed in many ways in the Latin alphabet.

The various elements set out above only confirm the fact that the quality of the data against which the filtering is carried out is as important as the configuration of the filtering tools themselves to obtain the most relevant results possible. In parallel with this state of affairs, it must also be considered that the disruption constituted by the new mobile payment methods has changed the expectations of the public by offering the possibility of making almost instantaneous transactions. Providing an easy and seamless customer experience today is more than a competitive advantage and tends to become a basic customer requirement.

The risk of not detecting a criminal is not the only element to be taken into account in this reasoning. It is also necessary to take into account the considerable budget of dealing with false alarms as well as the complexity of integrating poorly structured databases. The danger is not only regulatory but also commercial because a process of entering into a relationship or verifying a transaction that is too cumbersome could divert customers to other more efficient or reactive structures as well as cause a financial institution to lose opportunities.

The implementation of truly effective detection measures by financial institutions and large groups on the African continent could also have a geopolitical impact and would make it possible to stem the de-risking policies currently pursued by Western investors. A press release from the Arab Monetary Fund, the IMF and the World Bank presents quite alarming figures on this subject and can be found here.  It would therefore be appropriate to start considering the cost and optimization of AML-FT tools as a lever for long-term growth rather than as a costly constraint.