Download Money Laundering: the Economics of Regulation

European Journal of Law and Economics, 7:225–240 (1999)
© 1999 Kluwer Academic Publishers
Money Laundering: the Economics of Regulation
DONATO MASCIANDARO
Professor of Monetary Economics, Paolo Baffi Centre for Monetary and Financial Economics, Bocconi
University, Via Sarfatti 25, 20136 Milano, Italy, e-mail: [email protected]
Abstract
The paper undertakes an economic analysis of money laundering and of anti-money laundering regulation within
a theoretical and normative framework. The model is then applied to the development of the Italian anti-money
laundering regulation in recent years.
Keywords: Crime, money laundering, regulation
JEL Classification: K4, G2
Economic research has not yet systematically undertaken the analysis of the existing
interactions between criminal economy and financial markets. The present work belongs
to a research field increasingly interested in such issues and focuses on the economic
analysis of money laundering (Masciandaro, 1993, 1994, 1998; Hallet, 1994) following
the structure explained below.
Section 1 contains the economic analysis of money laundering in the context of criminal activities. We will first provide a theoretical definition of the phenomenon in order to
highlight the substantial economic function of money laundering, which is to transform
potential purchasing power into an effective one. We will then present a theoretical
analysis of the mechanisms ruling the growth of this illegal activity as well as of its ties
with the development of a criminal economy.
The model we propose, based on a previous approach introduced by Masciandaro
(1993, 1994), will allow us in section 2 to further analyze money laundering and antimoney laundering policies adopting a positive theoretical perspective.
First we identify the role of money laundering as a multiplier of criminal financial
activities. Such a “polluting” element of the economy becomes more considerable:
i) the lower the aggregate transaction costs of undertaking money laundering;
ii) the larger the share of reivestment in illegal activites;
iii) the more pressuring the need of financing such reinvestment with “clean” liquidity;
iv) the wider the differentials in expected real returns between illegal and legal activities;
v) the larger the initial volume of illegal revenues that has to be “cleaned”.
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In section 2 we will turn to the analysis of the optimal macro features of anti-money
laundering regulation using a formal model. We will see how the legislator on one hand
faces the need of limiting the damages caused by money laundering, which are far from
being of exclusively economic nature, and on the other hand he cannot but take into
account the results of anti-money laundering regulations in terms of burdens and costs
imposed on the banking and financial systems.
As the legislator’s sensitivity towards the damages of crime and the costs of regulation
changes, both the level of related legal action strictness and the degree of money laundering tolerance within a country are subject to change too.
The effects of anti-money laundering regulation will also be analyzed according to the
degree of correlation between the efficiency of the regulation itself and the outcomes that
the latter may produce on the efficient functioning of the financial and banking system due
to the burdens imposed on intermediaries. The main finding will consist in the fact that
legislation becomes more effective the less it is responsible of impairing the efficiency of
banks.
In section 3 previous analytical tools and results will be applied to the Italian case in
order to test the relationship between the spread of money laundering and the state of
anti-money laundering regulations.
The final section holds some conclusive remarks.
1. The economics of money laundering
The economic analysis of money laundering requires an appropriate definition of the
phenomenon. The one adopted in the present study, which was introduced in Masciandaro
1993, is structured upon two key-characteristics of money laundering: 1) illegality (general feature): money laundering implies the use of any revenue originated by a criminal or
illegal activity; 2) concealment (specific feature): the primary goal of money laundering
is to hide the illegal source of such revenues.
The first of these two characteristics aims at pointing out the autonomy that money
laundering holds in criminal terms as it does not consider the specific illegal or criminal
activity responsible of producing the revenues later to be laundered (drugs markets,
kidnapping, corruption, fraud, etc.).
The second characteristic identifies the essential economic function of money laundering in turning illegal capital into legal. The peculiar economic function of this activity is
therefore to transform potential purchasing power, since it cannot be directly used for
consumption, investment or saving, into an effective one.
Research upon different forms of money laundering (Savona and De Feo, 1994) shows
how an acknowledged priority of the phenomenon is to give rise to an independent activity
not necessarily related with the criminal one that produced illegal assets. Such an autonomous activity appears to be oriented towards different customers, such as criminal organizations, centres of political and administrative corruption, tax evaders and basically
anyone wishing to avoid the risk that the source of laundered money might be identified.
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Throughout this paper we will assume the economy to be closed, since no one of the
issues just considered would lose its significance if we were to consider an open economy;
such an assumption would only imply a further conditioning element, represented by the
existence, beyond heterogeneous national regulations, of increasingly integrated financial
markets for the activity of money laundering.
We will now show how money laundering can be seen, given an economy with both
legal and illegal sectors, as a multiplier of the volume of economic activities carried out
by criminal agents, allowing them to transform their illegally gained revenues into effective purchasing power. Such analysis will make use of the traditional multiplier approach
(Meade, 1934) in a completely new framework.
Let us start by considering an initial amount of liquidity, ACI, produced by one or more
criminal activities in a given economic system. Let us also assume that at least a fraction
yACI -being 0 ⬍ y ⬍ 1- of such funds needs to laundered1; as a matter of fact, without
having been separated from its illegal source, this “dirty” money holds virtually no value.
That is the reason why a money laundering action is urged to take place.
Each money laundering operation implies what we would call aggregate transaction
costs, represented by the resources a criminal agent needs in order to put money laundering into action. Such costs may carry a dual nature: on one hand, we have technical
costs related to the specific money laundering technology to be adopted; on the other
hand, we have those costs due to anti-money laundering regulation. Other conditions
being equal, the costs of money laundering will therefore depend on the effectiveness of
anti-money regulation: the more effective the latter is, the more expensive it will be for
criminal agents to undertake the activity of money laundering. The two types of costs may
obviously be correlated in a more or less significant fashion.
Let us make the assumption that the aggregate transaction costs of money laundering,
named CR, are a fixed proportion of the amount of illegal funds that need to be laundered
(yACI). We then can write:
CR ⫽ cyACI
where c refers to both technical and regulation-related costs.
After engaging in money laundering operations, criminal agents may decide to use what
has now become a “clean” liquidity, (1-c)yACI, for consumption, saving or investment,
either on legal or illegal markets. Let us indicate by q(1-c)yACI the portion of laundered
liquidity that is reinvested in illegal activities. We define q as a function q(r), where r is
equal to (ri-r1), i.e. the differential in expected real returns between illegal and legal
investment operations2. Such an illegal reinvestment will originate a new liquidity that
will need to undergo a laundering process again. Taking into account the revenues produced by the illegal reinvestment operation, we can write the new amount of money to be
laundered in the form q(1-c) (1 ⫹ ri) yACI3.
The crucial hypothesis we are making is that both the legal and the illegal investment (at least part of the latter) need to be financed by “clean” liquidity. Such
position would be supported by the presence of rational operators informed about the
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Figure 1. The money laundering process.
supply of financial services to criminal agents, as well as by criminal agents’ own rationality which urges them to minimise the risk of being discovered.
If we consider money laundering operations to be repeated several times—even infinite—with constant values of the parameters (see fig.1), the global amount of illegal
financial flows that underwent money laundering will be equal to the following geometric
series4:
AFI ⫽
yACI
1 ⫺ q(1 ⫺ c)(1 ⫹ ri)
(1)
where m is the multiplier of money laundering. We could then consider AFI as a broad
indicator of the degree of expansion of money laundering within a given economy. The
multiplying effect of money laundering will be stronger:
a) the lower the aggregate transaction costs of undertaking money laundering as represented by parameter c; i.e. the less effective anti-money laundering regulation happens
to be:
ACIqy2 (1 ⫹ ri)
⳵AFI
⬍0
⫽⫺
⳵c
(1 ⫺ qy(1 ⫺ c)(1 ⫺ ri))2
(2)
If we assume anti-money laundering regulation to have a significant impact on the cost of
carrying out a criminal activity, then an effective system of rules will in fact reduce the
ability of criminal agents to launder their illegal liquidity.
b) the larger the share of reinvestment in illegal activities (q), which obviously depends
on their expected revenues and riskiness. Therefore we can write:
(1 ⫺ c)(1 ⫹ ri) ACIy2
⳵AFI
⬎0
⫽
⳵q
(1 ⫺ qy(1 ⫹ ri)(1 ⫺ c))2
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c) the higher the expected real return ri on illegal activities (under the assumption of
constant returns from legal activities):
⳵AFI
(1 ⫺ c) ACIqy2
⫽
⬎0
⳵ri
(1 ⫺ qy(1 ⫺ c)(1 ⫹ ri))2
(4)
d) the larger the initial volume of liquidity produced by illegal activities (ACI):
⳵AFI
y
⫽
⬎0
⳵ACI 1 ⫺ qy(1 ⫺ c)(1 ⫹ ri)
(5)
e) the larger the share (y) of illegal funds that needs to be laundered:
(1 ⫺ c) ACI
⳵AFI
⬎0
⫽
⳵y
(1 ⫺ qy(1 ⫹ ri)(1 ⫺ c))2
(6)
We do not need to make any specific assumption on the nature of the criminal activities
here considered; such activities must meet the only requirement of producing “dirty”
money, i.e. flows of revenues that cannot be reinvested without concealing their source.
A more effective money laundering operation will obviously result in a larger liquidity
flow available to criminal agents for reinvestment. The amount of laundered liquidity
ready to be reinvested can be written as:
ARE ⫽
(1 ⫺ c)(1 ⫺ q) yACI
1 ⫺ yq(1 ⫺ c)(1 ⫹ ri)
(7)
Finally we can calculate the total revenues produced by money laundering, assuming that
this activity is carried out by specific productive units and that the costs named c represent
net5 gains to such units:
RAR ⫽
cyACI
1 ⫺ yq(1 ⫺ c)(1 ⫹ ri)
(8)
If the multiplier of money laundering turns out to be stable6, then any variation in the
initial quality of illegal assets (ACI) will cause a more than proportional variation in the
final amount of illegal financial flows that were globally laundered (AFI). The strongest
multiplying effect is obviously reached when anti-money laundering regulation is ineffective, technical costs are negligible (c ⫽ 0) and the whole illegal revenues need to be
laundered (y ⫽ 1). Under these conditions we obtain the largest amount of laundered
liquidity ready to be reivested (AFImax), which can be written as:
AFImax ⫽
ACI
⫽ mrbmaxACI
1 ⫺ q(1 ⫹ ri)
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The highest value of the multiplier, mrb max, points out the substantial role played by the
initial amount of illegal assets ACI, that we can see as a peculiar kind of “raw material”
in the money laundering process. It is thus possible to conclude that the expected volume
of money laundering activities increases with the growth of the criminal economy. Such
a conclusion is more plausible the more likely the hypothesis of a closed economy appears
to be, so that every real transaction has its financial couterpart within the same economic
system.
2. Anti-money laundering regulation
In the previous section we found an inverse relation between the degree of expansion of
money laundering within a given economy (as represented by AFI) and the effectiveness
of anti-money laundering regulation, which is responsible of raising the costs of money
laundering. This relation may be interpreted as an estimate of the potential demand for
anti-money laundering regulation within a given economy. Therefore, in order to reduce
the entity of crime, an increasingly effective anti-money laundering policy is needed.
Let us rewrite equation [1] in a more simple form, setting parameter y equal to 1. The
demand for anti-money laundering regulation, as expressed by the variable AFI, is then
equal to:
AFI ⫽
ACI
1 ⫺ q(1 ⫺ c)(1 ⫹ ri)
[1bis]
The activity of money laundering reaches a maximum degree of expansion when antimoney laundering regulation is completely ineffective (AFImax) and then decreases in
volume.
Therefore the sensitivity of the volume of money laundering activities to the stringency
of the regulation can be synthesised by the substitution rate of money laundering, SSR:
SSR ⫽
ACIq(1 ⫹ ri)
⳵AFI
⬍0
⫽⫺
⳵c
(q(1 ⫺ c)(1 ⫹ ri))2
(10)
Under the assumptions previously made on the parameters, the substitution rate SSR is
negative and decreasing:
⳵2 AFI
⳵2 c
⫽
2q2 (1 ⫹ ri)2 ACI
(1 ⫺ q(ri ⫹ 1)(1 ⫺ c))3
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Equations [10] and [11] imply that increasingly stringent rules result in decreasing gains
of effectiveness; that is to say that the curve of money laundering, obtaining by plotting
AFI against c, is convex (see fig.2 below).
If the supply of anti-money laundering regulation was costless, the policy maker’s7 best
decision would be to increase the costs of money laundering as much as possible (c ⫽ 1).
However, the problem is obviously far from being so trivial.
In fact the policy maker also faces the problem of fixing the optimal level of those costs
which are due to anti-money laundering regulation. Conceiving such a regulation implies
the imposition of some costs on the entire economy and on the banking system in
particular (the nature of these costs will be analysed in the following section). The optimal
policy will be the one that will succeed in minimising the social costs of regulation while
keeping crime at a tolerable level.
What we mean by social tolerance towards crime is the fact that the policy maker, in
order to achieve the hypothetical goal of zero crime, must take into account the welfare
costs imposed by anti-money laundering regulation on honest private agents, families,
companies and banks, since these costs are proved to carry a considerable impact.
The policy maker faces a function of social loss V(D,c1), which is continuous and has
existing first and second order partial derivatives. Variable D stands for the harmfulness
induced by money laundering while ci for the costs of regulation in terms of the efficiency
loss caused to the banking and financial system.
V ⫽ V(D,c1)
⳵V
⳵V
⬎0
⬎ 0,
⳵D
⳵c1
(12)
The assumption we are making is that a trade-off exists between the effectiveness of
anti-money laundering regulation, responsible of increasing the integrity of the banking
and financial system, and the efficiency of the system itself which is obviously impaired
Figure 2. ISO-integrity curves.
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by the costs of regulation. The costs imposed to the banking and financial system by
anti-money laundering regulations are related to monitoring and notifications duties and
are subject to increase as the rules become more strict.
We will now assume such a trade-off to be complete, which implies a totally effective
but inefficient regulation (c ⫽ c1).
All the possible combinations between the social losses due to money laundering and
those due to the costs of regulation, responsible of inducing a total level V0 of social loss,
represent what we define an iso-integrity curve.
For the sake of simplicity we will adopt a linear form of V:
V ⫽ dAFI ⫹ ec
d,e ⬎ 0
hence
AFI ⫽ V ⫺
e
c
d
(13)
Diagram in fig.2, illustrating the relationship between the spread of money laundering
(AFI) and the costs of regulation (c), shows how higher iso-integrity curves correspond to
increasing levels of social loss as plotted along the axes:
The policy maker’s sensitivity towards the costs of anti-money laundering regulation
can be synthesised by the anti-money laundering substitution rate SSA:
SSA ⫽
⳵AFI
e
⫽⫺
⳵c
d
(14)
SSA, which was calculated from the total differential of the linear loss function adopted
above, expresses the substitution rate between the policy maker’s tolerance of the damages
caused by money laundering and his sensitivity towards the costs induced by regulation.
The policy maker will conceive the best anti-money laundering regulation given the
constraint represented by the potential demand for regulation. As we can see in fig.2,
equilibrium is attained through the lowest tangency between the potential demand curve
and an iso-integrity function, thus equalising SSA ⫽ SSR.
Reflecting changes in the behaviour of criminal organisations and policy makers, he
optimal anti-money laundering regulation is subject to change too.
Criminal agents may decide to increase the revenues produced by criminal activities or
to shift a larger share of their funds towards reinvestment in illegal markets: both decisions, though in a different degree, imply an increase in money laundering and negative
welfare effects for society. Such changes are represented by an upward shift in the curve
of potential anti-money laundering demand, thus locating the new equilibrium on a higher
iso-integrity curve. Negative welfare effects, although different in size, are also induced
by an increase in the returns on illegal activities. Higher returns obviously imply a larger
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Figure 3. The equillibrium level of anti-money laundering regulation.
share of reinvestment in illegal activities and therefore stimulate the growth of money
laundering.
Concerning the changes that may occur in the policy maker’s position towards moneylaundering, a lower sensibility towards the costs of regulation implies the adoption of
more stringent rules, while a lower sensibility towards the damages produced by money
laundering will cause regulation to be less restrictive. In the first case iso-integrity curves
become flatter, with a decrease in money laundering and an increase in the costs of
regulation, while in the second case iso-integrity curves become steeper, thus representing
a higher level of money laundering and lower regulation costs.
Let us now extend the previous assumption concerning the relationship between the
effectiveness of anti-money laundering regulation and the efficiency of the banking system. Anti-money laundering regulation may impair the efficiency of banks in different
degrees of intensity: i) fully (c1 ⫽ c), which means that regulation is completely effectiveinefficient (as assumed so far); ii) less than proportionally (c1 ⫽ zc, where 0 ⬍ z ⬍ 1),
which implies a relatively effective-inefficient regulation; iii) more than proportionally (c
⫽ wc1, where 0 ⬍ w ⬍ 1), which implies a relatively ineffective-inefficient regulation.
Therefore, starting from an effective-inefficient regulation (c1 ⫽ c), we can figure out
two opposite cases. On one hand let us consider an anti-money laundering regulation that,
given a certain level of effectiveness, is capable of reducing the costs imposed on the
banking and financial system. Such a regulation surely entails positive effects on the
overall efficiency of the system, reducing its global “pollution rate”. On the other hand we
can think of a regulation responsible of increasing the costs for financial intermediaries,
having negative consequences even in terms of efficiency. Graphically, it is possible to
represent case 1 (case 2) by a flatter (steeper) iso-integrity curve, thus implying a lower
(higher) equilibrium level of SSA ⫽ SSR.
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Figure 4. Increase in the legislator’s sensitivity towards the damages caused by money laundering (more
effective-less efficient regulation).
3. Money laundering and anti-money laundering regulation in Italy: a case study
In the previous sections we analysed the relationships between legal and illegal markets
within a theoretical framework. The adopted model will be now used as a tool to investigate the evolution of the Italian case.
Law n.197 July 5 1991 can be regarded as the starting point of the Italian anti-money
laundering regulation, although the legislative system actually began dealing with such
issues in the late ‘70s.
The conception of specific anti-money laundering rules can be related to the awareness,
increasingly shown by public authorities, of a strong expansion of illegal markets and
particularly of money-laundering activities within the country. Throughout the ‘80s the
country witnessed a strengthening of criminal organisations in terms of memberships,
range of activities and territorial diffusion (Savona, 1992).
The model proposed in sections 1 and 2 allows us to make predictions about medium
term relations between the growth of illegal markets an the volume of money-laundering
activities. The key idea of the model is that the financial side of a given economy does not
only reflect legal transactions but also illegal ones; due to the presence of money laundering, financial aggregates are therefore likely to be larger, ceteris paribus, in those
countries where organised crime has a stronger influence.
To test this hypothesis we undertook a cross-section analysis of the existing ties between bank deposits, legal economy and illegal markets within 95 Italian districts during
the ‘80s. Bank deposits represent an outstanding feature of the Italian financial system,
especially with respect to Southern regions (Faini, Galli and Giannini, 1993). Both the
legal and the illegal side of economy, however, being conceptionally rather vague, are very
difficult to quantify. A possible measure of the legal economy may be represented by per
capital gross national product, while per capita number of crimes could be adopted as a
proxy for the illegal economy, given the unavailability of data concerning illegal markets.
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Table 1 shows how in Italy the distribution of the suggested legal economy index (per
capita GNP) is not strongly correlated with the one concerning illegal economy (per
capital number of crimes).
Table 1 also allows us to consider such an outcome in terms of the main features of the
Italian banking system by looking at the correlations between bank deposits and both legal
and illegal variables in Italy as a whole, as well as in different areas within the country,
namely North, Centre, South and South with organised crime (Campania, Puglia, Calabria
and Sicilia). Bank deposits result to be considerably correlated to GNP (legal economy) in
Italy, Northern Italy and Centre Italy, while exhibiting a stronger correlation to crime than
to GNP in both Southern areas.
Similar results are achieved by running regressions of bank deposits on both per capita
GNP and crime, plus on a price variable given by the interest rate differential between
bank deposits and Government bonds (see Table 2). In the first place, the overall fit of the
regression improves when introducing the illegal variable. Secondly, only the illegal variable always shows a positive and significant coefficient. Finally, the impact of the illegal
economy appears to be relatively more significant in the South.
These findings are consistent with the criminological, institutional and legal studies that
highlight the increasing relationship between the growth of illegal activities and the more
or less conscious involvement of banks or other financial intermediaries in the money
Table 1. Bank deposits, legal economy and crime: correlation matrix (average per capita data 1980–90).
Italy
Deposits
GNP
Crimes
Deposits
GNP
Crimes
Deposits
GNP
Crimes
Deposits
GNP
Crimes
Deposits
GNP
Crimes
Deposits
GNP
1
0.88
1
0.27
0.16
North
Deposits
GNP
1
0.71
1
0.34
0.16
Centre
Deposits
GNP
1
0.80
1
0.37
0.31
South
Deposits
GNP
1
0.17
1
0.51
0.12
South with organised crime
Deposits
GNP
1
0.36
1
0.62
0.71
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Crimes
1
Crimes
1
Crimes
1
Crimes
1
Crimes
1
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Table 2. Bank deposits, legal economy and crime: regressions output (average per capita data 1980–90).
Dependent Variable: Bank Deposits
Independent Variables
Intercept
GROSS NATIONAL
PRODUCT
CRIMES
INTEREST RATES
DIFFERENTIAL
R2
S.E. of regression
Prob. ⬎ F
N°. observations
Italy
North
Centre
South
South with organised crime
-.41
(1.41)
.68
(.03)**
.03
(.01)**
-.69
(.27)**
.80
1.22
0.00
95
-3.37
(1.96)
.75
(.13)**
.04
(.01)**
-.31
(.38)
.58
.87
0.00
33
6.41
(4.08)
.59
(.14)**
.04
(.02)**
-2.41
(4.08)
.72
1.19
0.00
32
-.13
(2.32)
.01
(.05)
.03
(.01)**
.68
(.52)
.24
.58
0.01
30
2.2
(2.9)
-.13
(.18)
.04
(.01)**
.37
(.65)
.31
.57
0.02
22
Standard errors in parenthesis. A* (**) denotes significance at the 5% (1%) level. Each equation is estimated by
OLS.
Sources: Bollettino Statistico Banca d’Italia, Annuario ISTAT, Istituto Guglielmo Tagliacarne; various years.
laundering business (Bosworth-Davies and Saltmarsh, 1994, Norton 1994, Savona and De
Feo, 1994).
In the framework of our model, the diffusion of money laundering in Italy can be
represented by an upward shift of the money laundering curve towards a higher isointegrity curve, thus implying a welfare loss.
Facing the necessity of struggling against money laundering and discouraging the
constitution and development of polluted intermediaries, law n.197 (July 5 1991) states
the central role of the banking and financial system in such a fight by making financial
intermediaries agents of the public authority.
The elements of the 1991 regulation expressly related to this newly attributed role of
agents in monitoring and notifying money laundering activities are represented, for financial intermediaries, by the mechanisms ruling the use of cash, the introduction of
notification duties about suspicious financial operations and the extensions of previous
identification duties. In particular, the newly introduced duty of notifying any suspicious
operation to the judicial authority appears to be undoubtedly relevant in order to
strengthen such a role.
Getting back to our model, we can say that law 197 shows a stronger sensitivity of the
legislator towards the damages inflicted by money laundering to society than to the costs
of regulations. The position expressed by law 197 can then be represented by flatter
iso-integrity curves, revealing a lower sensitivity towards the costs of regulations and an
increased effectiveness of regulation itself.
Nevertheless, this would be just a partial interpretation of law 197, not sufficiently
attentive to the negative effects produced on the efficiency of intermediaries. As a matter
of fact the anti-money regulation introduced by law 197 imposed some costs on every
single financial intermediary. In particular, there is a clear trade-off between the autonomy
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that an intermediary holds in running its own private information assets and its function
of agent of the public authority in charge of fighting against money laundering activities.
Such a trade-off is more than evident when thinking of the duties of identification,
registration and notification.
Identification and notification duties carry two different types of costs: privacy costs,
due to an impaired warranty of privacy provided to the client, as well as administrative
costs, due to the resources an intermediary must use in order to achieve the required
human and technical skills to put the regulation into practice. We cannot but remind
another category of costs, particularly relevant in the Southern area with organised crime,
represented by the risk of reprisal. However, reprisal costs themselves can be seen as a
specific case of privacy costs, as they arise when an intermediary is responsible of breaking its commitment to privacy by co-operating with public authorities.
The key-element of law 197 is therefore represented by the establishment of an active
cooperative role of financial intermediaries in the fight against money laundering, thanks
to the newly introduced duties of monitoring and notification of suspicious cases. Such
duties, however, are far from being costless and law 197 does not provide an adequate set
of incentives for intermediaries to fulfill them. This serious lack in 1991 regulation soon
came to light.
A hint of the ineffectiveness of such regulation was to be seen in the scarce number of
submitted notifications that followed the enforcement of the law. Any expectations, based
upon the symptoms of pollution shown by the economic and financial system, were
strongly disappointed: up to June 1992 only 86 notifications had been made by banks,
other financial intermediaries and postal offices. Among them, 52% turned out to be
meaningless and almost none came from those regions where organised crime is particularly relevant: only 7 from Sicily, 2 from Calabria and 3 from Campania.
The main reason for such a serious failure can be found in the missed chance to really
involve banks in the fight against money laundering, that is to say in the impossibility of
putting the concept of active cooperation into real practice. Therefore, following our
model, we can conclude that law 197 turned out to be a relatively ineffective-inefficient
form of regulation.
The global effects of law 197 can be graphically described by a double variation in the
map of iso-integrity curves: the stronger sensitivity of the legislator towards the damages
induced by money laundering makes them flatter, while the inefficiency of the regulation
implies steeper curves, thus achieving an uncertain global result.
Ever since the failure of law 197, Banca d’Italia has regarded the need of a more
balanced regulation in terms of effectiveness and efficiency as particularly pressuring.
Such an awareness, induced Banca d’Italia to produce the so-called “Decalogue” which
contains some indications to bank operators on how to fulfil their notification duties.
Besides adopting an approach which aims at achieving and maintaining the integrity and
stability of the economic and banking system, the structure and content of the Decalogue
also show the intention of influencing each single intermediary by dealing with the issues
of microeconomic incentives. The document points out how beneficial it would be to
adopt homogeneous plans of actions in order to maximise the effectiveness of regulation
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while minimising its costs, as well as to avoid that banks might behave as free-riders
concerning the real application of anti-money laundering rules.
Main legislation made its further steps in the same direction by facing, with law 328
August 9 1993, the issue of those criminal actions that take place before moneylaundering itself. Law 328 ratified the Strasbourg Convention on money laundering (November 8 1990), stating that the crime of money-laundering is committed relatively to
money, goods or other utilities produced by whatever non negligent crime. In such a way
the legislator improved the substantial cohesion and efficiency of the role played by banks
as agents of the public authority.
Such a wide definition of the crimes that originate money laundering brings the Italian
regulation closer to the economic definition of money-laundering adopted in this work,
which highlighted the activity of concealment of illegal revenues without considering the
nature of the crimes responsible of producing them.
Banca d’Italia further strengthened its normative action by approving, in November
1994, an updated version of the Decalogue, where the analysis of anti-money laundering
costs is particularly relevant. The adopted approach also takes into account the categories
we previously analysed, i.e. administrative and privacy costs.
We believe that the effort of rationalisation represented by the Decalogue, given the
pre-existing normative framework, is to be considered noteworthy. Our hope is that also
primary legislation will soon be aware of the need of fighting money laundering effectively AND efficiently.
In such a perspective, the December 1994 bill which gives execution to the money
laundering EEC Directive n.308 1991 carries some interesting points. First of all, the bill
states the need of rethinking the notification system in order to meet both effectiveness
(for instance by introducing specific computer technologies) and efficiency criteria, thus
trying not to impair the operational functioning of banks. Secondly, the bill calls for the
adoption of preventive measures to protect the notifying agents from reprisal risks. Such
plans for action, if correctly implemented, may produce an important—although not
conclusive—improvement in the effort of minimising both administrative and privacy
costs.
To conclude, we wish to highlight how anti-money laundering regulation, due to a
well-designed system of incentives and costs for financial intermediaries, may evolve
towards the achievement of higher effectiveness goals while improving its efficiency
standards as well. The optimal solution is therefore to orient policy efforts in the direction
of an effective-efficient regulation.
Conclusion
Within the theoretical approach adopted in the first part of the paper, we showed how
money laundering can be seen as a multiplier of criminal financial activities. Transforming
potential into effective purchasing power, money laundering allows the reinvestment of
laundered illegal funds, thus playing a crucial role in strengthening the ties between the
real and the financial side of a criminal economy.
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Secondly, we highlighted the inverse relationship between the degree of diffusion of
money laundering activities and the effectiveness of anti-money laundering regulation in
a given economy.
Consequently, we analysed the mechanisms ruling the conception of anti-money laundering policies, given a certain level of public demand for such a regulation. The legislator
was shown to face a trade-off between protecting the integrity of the economic system by
an effective regulation and impairing the efficiency of financial intermediaries due to
regulation-related costs. Therefore, the legislator’s tolerance towards both the damages
caused by money laundering and the costs of regulation determines the strictness of an
anti-money laundering policy.
The possibility of increasing the effectiveness of the regulation while efficiently rationalising its costs was pointed out as well. Such an outcome would allow both a gain in
efficiency and a more effective regulation.
Throughout the paper we assumed the economy to be closed, so we call for further
relaxation of this hypothesis.
The model presented in Sections 1 and 2 was then applied to analyse the development
of the Italian anti-money laundering regulation. We showed how the Italian case reveals an
increasing sensitivity of policy makers towards the damages of money laundering,
matched with an unsatisfactory solution to the efficiency-effectiveness trade-off.
Improvements in such a direction were therefore indicated as feasible and hoped for.
Acknowledgments
The first draft of this paper was presented at the Eleventh World Congress IEA, Tunis, 21st
December, Session 19: Economics of Corruption and Crime. Without implicating them,
the author would like to thank all the participants of the Session and in particular Stefano
Zamagni, Gianluca Fiorentini, Frederic Rychen and the discussant Arindam Dasgupta for
helpful comments. I also thankfully acknowledge financial support from Paolo Baffi
Centre.
Notes
1. For the sake of simplicity parameter y can be considered equal to 1.
2. We assume this differential to be positive and dependent on the relative riskiness of both forms of investment.
3. We are implicitely assuming that the expected real return from illegal activities equals the actual one.
4. The geometric series will converge if y(1 ⫺ c)(1 ⫹ rii) ⬍ 1. In economic terms, convergence is better
respected the smaller is the amount of liquidity to be laundered and the higher are the costs and returns on
money laundering.
5. Risk-net.
6. The stability of the multiplier obviously depends on the stability of the parameters; it is thus possible to
figure out a variable multiplier build upon non-constant parameters.
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7. In this model we assume to have homogeneous policy makers. As a matter of fact, more than a single public
authority is involved in establishing anti-money laundering regulations. Masciandaro (1995) developed a
“main-agent” model in order to capture the relationships between the policy maker, the central bank and the
banking system in anti-money laundering regulations.
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