Page 13 - Unlicensed Digital Investment Schemes (UDIS)

5 CASE STUDIES BY COUNTRY (INDIA, KENYA ates via Facebook, Twitter, WhatsApp and Snapchat
& NIGERIA) and has numerous functioning web sites with a multi-
tude of domain names (several using a chatbot to in-
The countries selected for further study were coun- teract with consumers), including those URL that con-
tries where the working group has members with deep tain the country names India, Kenya and Nigeria. None
knowledge of the DFS market, who were also able to of the three countries studied shut down the MMM
provide input on the legal and regulatory frameworks, UDIS. In fact, the URL and Facebook pages affiliated
and provide background on past and ongoing UDIS in- with MMM remain operational in all three countries as
volvement in the country. The legal/regulatory reviews of March 2018. See case note 1 for more details on the
were also conducted by legal professionals from the MMM scheme in Nigeria.
country at issue. Because market monitoring, and apparently inves-
A fourth country, Bangladesh, was also used as a tigation and prosecution phases are challenging, this
point of comparison as the working group, which bene- research sought to better understand the roles of the
fitted greatly from insights of a Financial Intelligence various regulators in India, Kenya, and Nigeria and to
Unit Director at the Bank of Bangladesh who is also an better understand why they are failing to act, as per
AML expert. statutory mandates.
All three countries have common law roots, but very During the research, country contacts responded
distinct digital financial services (DFS) markets. Kenya, to ten questions in order to better understand the le-
for example boasts approximately 82% financial inclusion gal and regulatory frameworks related to UDIS, what
thanks in a large measure to the success of Safaricom’s should happen to prevent/deter these schemes, and
M-Pesa. Nigeria lags behind Kenya at 40% financial in- what improvements can be made in the future. (The
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clusion, respectively, but arguably Nigeria has greater full list of questions is attached as Annex A).
geographic, and language challenges to overcome.
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The other shared characteristic of the focus countries Our key findings are as follows:
is the victimization by at least one large scale, unli- a) Everyone is the boss, but no one is really in charge
censed digital investment scheme. In fact, all three (of UDIS).
countries have been victimized by Mavrodi Mondial
Moneybox or MMM, a scheme which originated in Russia b) There are low rates of prosecution for UDIS and
in the 1990’s and which has expanded globally due to rare reimbursements for the consumer when funds
the Internet and social networks. The MMM UDIS oper- are lost.

CASE 1
NIGERIA: THE IMPACT OF ONE UNLICENSED INVESTMENT SCHEMES ON THE ECONOMY
CAN BE SIGNIFICANT

In an attempt to better understand how fraudulent NIBSS conducted its analysis just following the
unlicensed digital investment schemes impact the MMM’s second crash. At the time, consumers who
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Nigerian economy, the Nigeria Inter Bank Settle- had invested funds, yet who had not received any
ment System, PLC (NIBSS), the central switch for payout lost over 11.9 billion Naira or USD 32.8 million.
the country’s financial sector undertook an analysis At the time of drafting of its report, NIBSS also
of interbank transactions from commercial banks. noted that it found evidence of at least 89 other on-
Transactions were analyzed from June 2016 to going unlicensed digital investment schemes in the
December 13, 2016 for linkages with the Mavrodi country.
Mundial Moneybox (MMM) Ponzi scheme in Ni- NIBSS has subsequently noted that the Central
geria. Because the scheme directed customers Bank Nigeria has been running awareness raising
to put identifying information on the transfer or- campaigns on TV to inform consumers of the dan-
der, NIBSS was able to discern that during the six gers of these schemes, however it would seem that
month period that 28.7 billion in Nigerian Naira was campaigns alone are insufficient. And, given that
transferred between banks related to the MMM NIBSS own data analysis was possible because con-
fraud, or USD 77.8 million. This amount transacted sumers used keywords on their transfer orders, it
in this one fraud in six months exceeded the Nige- would seem that artificial intelligence could be sim-
rian Ministry of Education’s annual budget by 61%. ilarly used to monitor the Internet and social media
Further, the data analyzed was only from inter- for indicators of similar fraudulent activity and to set
bank transfers. Thus, intra bank transfers related to indicators for financial institutions to flag suspicious
the MMM Ponzi are estimated to be at least twice transactions which would bely an underlying Ponzi
the interbank transfer volume. scheme is afoot.

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