EN  EN EN 
 
EN  EN  COMMISSION OF THE E UROPEAN COMMUNITIES 
Brussels, 16.12.2008 
SEC(2008) 3054 
  
COMMISSION STAFF WORKING DOCUMENT 
 
Accompanying document to the  
COMMUNICATION FROM THE CO MMISSION TO THE EUROPEAN 
PARLIAMENT, THE COUNCIL AND THE EUROPEAN COURT OF AUDITORS 
 
Towards a common understanding of the concept of tolerable risk of error 
   
{COM(2008) 866 final} 
  
 2COMMISSION STAFF WORKING DOCUMENT 
Towards a common understanding of the concept of tolerable risk of error 
1. SCOPE ....................................................................................................................... ........................................ 3 
2. APPROACH AND ASSUMPTIONS.................................................................................................... ........... 3 
2.1 THE LINK BETWEEN RESIDUAL RI SK AND COST OF  CONTROLS............................................... 3 
2.2 MODELLING THE RELATIONSHIP BETWEEN THE COST AND THE RATE OF 
UNDETECTED ERRORS .............................................................................................................. ..................... 4 
2.2.1 Linear model............................................................................................................. ............................ 4 
2.2.2 Extending the linear model............................................................................................... .................... 5 
2.2.3 Testing the model........................................................................................................ .......................... 7 
2.3 GENERAL ASSUMPTIONS AND CALCULATION METHODS............................................................ 8 
2.3.1 General assumptions:..................................................................................................... ...................... 8 
2.3.2 Calculations and methods................................................................................................. .................... 9 
2.4 ILLUSTRATI VE CASES......................................................................................................... .................... 11 
2.4.1 European Regional De velopment F und (ERDF)................................................................................ 11 
2.4.2 European Agricultural Fund  for Rural Devel opment (EAFRD)......................................................... 15 
3. THE COST OF CONTROLS EXERCISE ............................................................................................... .... 17 
3.1 METHODOLOGY................................................................................................................ ........................ 17 
3.2 RESULTS FOR THE CO MMISSION SERVICES................................................................................... 18 
3.2.1 European Agricultural Guidan ce and Guarantee F und (EAGGF) .................................................... 18 
3.2.2 European Regional De velopment F und (ERDF)................................................................................ 19 
3.2.3 DG Employment and Social Affairs......................................................................................... ........... 20 
3.2.4 DG EuropeAid............................................................................................................. ....................... 21 
3.2.5 DG Environment........................................................................................................... ...................... 21 
3.2.6 DG Research .............................................................................................................. ........................ 22 
3.2.7 DG Information Society................................................................................................... ................... 22 
3.2.8 Other Services ........................................................................................................... ......................... 23 
GLOSSARY: ...................................................................................................................... ................................. 24 
  
 31. SCOPE 
 
The aim of this document is to present the t echnical elements supporting the conclusions and 
the analysis set out in the accompanyi ng Communication COM(2008) 866. The document 
presents the approaches taken in respect of  selected policies of the Commission for the 
illustrative examples in the main communication, t ogether with a first estimation of the costs 
of controls for selected policies (results of Acti on 10 of the Action Plan towards an Integrated 
Internal Control Framework) in both direct cen tralised mode and shared management mode.  
  
2. APPROACH AND ASSUMPTIONS 
 
2.1. The link between residual risk and cost of controls
 
 
Controls cost money and a cost-effective bala nce has to be sought between the number of 
controls and the amounts of error detected and recovered. The mo re controls that are carried 
out, the lower the ra te of undetected e rror will be. This  intuitive  relationship between  the level 
of errors undetected by Commissi on and Member States' controls  and cost of controls  is 
shown in the following chart: 
 
Graph 1 
 
 
 The following components of the curve can be distinguished, each with its own elasticity:  
• Zone 1: In the absence of any control : a theoretical level of "errors" would remain 
undetected, the nature and value of which depend on the complexity of the 
regulatory framework, the propensity to  error, the inherent risk etc. Zone 1 
Zone 2 
Zone 3
Zone 4
Zone 5  
Rate of errors undetected by 
Commission and Member States  
Cost of controls      DAS rate  
Current 
(improved) 
error rate  
 
Increase of the rate of on-the-spot controls Current costs 
  
 4• Zone 2:  (Quasi) Fixed  costs : or the cost of setting up the control system before 
controls are carried out (in te rms of strategy chosen, risk analysis, definition of tools 
and procedures).  
• Zone 3: Reverse economies of scale : gradual reduction of the error rate while 
increasing the costs of control (due to great level of elasticity at this point of the 
curve); at a critical threshold (which we ca ll the "tolerable risk point"), the marginal 
benefit of an additional control equals the marginal cost of an additional control. 
Beyond this point the marginal cost of a c ontrol exceeds the marginal benefit to be 
expected (in terms of a reduction in the error rate or the amount of error likely to be 
detected and recovered).  
• Zone 4: “One-off” errors : once the most important and/or systemic errors have 
been eliminated, only “one-off” errors will exist. Because of their nature, such errors 
require significant resources in order to be detected. 
• Zone 5: Tangent to the 0% error rate:  the last remaining errors will require more 
resources to detect them due to the low level of elasticity at this point of the curve 
(ultimately all activities will n eed to be checked completely to identify these errors). 
 While this is a sound theoretical presentation of the issues, it would be very difficult to draw 
the “real” curve reflecting the reality of each po licy area. In order to identify the coordinates 
of the points of the curve extensive data would be needed to model the impact of different 
levels of control - something that is not feasible  in practice. It is for example not possible to 
model the impact of the removal of all controls to define a rate of undetected errors in zone 1. 
The process of estimating accurately  the cost of control and obtai ning reliable data to estimate 
potential error rates would also imply an extens ive data collection exercise, in particular at 
Member State and implementing body level since de tailed statistics are currently not available 
(for example the number and value of ongoing proj ects). However, on the basis of available 
2006 data complemented by data collected by th e Commission on the costs of control, this 
document sets out some illustrative examples of tolerable risk using a variety of assumptions which are set out in section 2.3 below.  
 
2.2. Modelling the relationship between the cost and the rate of undetected errors
 
 2.2.1.  Linear model
 
 
The basis for the illustrative examples of tolerabl e risk presented in this document is a simple 
linear model in which the rate of undetected erro r decreases as more controls are carried out. 
The model presents how one variable (error rate) is related to other variables (principally the cost of control and the numbers of proj ects/beneficiaries to be controlled).  
 
The model presents the situation where one Y vari able (the error rate) is related by a straight 
line to just one X variable (cost of controls ). A trend line is then drawn between two known 
points using a Cartesian equation of the type Y = cX + b where 'c' is the (negative) slope and 
'b' the intercept resulting in a distribution (or population) of Y values, appropriately called the 
probability distribution of Y1 give n X1, and similarly a distribution of Y2 at X2, and so forth. 
The population parameters b and c specify the straight line, known as  the true population 
regression line and are estimat ed from the available informa tion on control costs and error 
  
 5rates. Once the line is drawn between two give n points the whole set of  Y populations can be 
inferred and the level of Y (error) can be pred icted at a given level of X (control costs).  
Technically, only 2 coordinates are necessary to prepare the model:  
• Point A: the current error rate at  the current cost of control  
• Point B: the point where all th e open projects are audited on-t he-spot (if we assume that 
the Y-axis (error rate) is zero once all projects are audited) – that is that controls will 
detect and correct all errors. 
 
The line is the following:  
Graph 2 
 
 
2.2.2.  Extending the linear model  
 
Of all the regression principles, the straight line is the most simple. It leads to a relatively 
simple formula for calculating the intercept and the slope of the line and is easy to understand. 
However, even if two points can be located, as proposed by the model, defining the shape of 
the connecting line/cu rve that depicts the rela tionship between the "unde tected error rate" and 
the "cost of controls" is the ke y issue (essentially defining the slope 'c') . In practice one can 
connect two points with an infin ite number of different curves . Therefore it is important to 
recognise that a mathematical model is a simp lification of a complex reality and can only be 
of useful approximation. In particular we ca nnot take seriously the assumption that the 
population means are strung out exactly  in a straight line (see as sumptions in 2.3 below). If 
we consider the intuitive rela tionship between the level of errors undetected by the internal 
control system and the costs of control, it is likely that the le vel of errors decreases rapidly 
initially (as the “easiest ” errors are detected) but then becomes more flat eventually as the 
"tolerable risk point" is approached and the marginal cost of control becomes exceptionally 
high compared to the marginal benefits (as il lustrated by graph 1 above ). In such cases a non-
linear model is likely to be more  representative of the population.  Rate of undetected errors 
(Y) 
Cost of controls 
(X) Current rate  
Current cost 
of controls  0% 
Cost of 
control for all 
open projects   (A) 
 (B) 
  
 6Since the fundamental problem of the model co mes down to defining slope 'c', the linear 
model was extended by adding a trend line to the straight line to reflect a line sloping 
downward, representing decrease d error rates over increasing co sts of control. Since the 
population used for this exercise does not me et the assumption of homogeneity (because 
different projects present differe nt types and levels of risk),  a "logarithmic trend line" is 
appropriate, as a logarithmic scale shows variab le growth changes perc entage-wise (whereas a 
linear trend line is used for constant rates). Therefore a logarithmic trend line is a best-fit curved line that is most appropriate when the rate  of change in the data increases or decreases 
quickly and then levels out. 
 
The logarithmic equation for calculating trend li nes calculates the "bes t line" through points 
by using an equation of the type y = c ln x + b where c and b are constants, and ln is the 
natural logarithm
1 function.  
 A graphic representation of this trend line is shown in graph 3: 
 
Graph 3 
 
 
Once the curve is drawn, the level of Y (error) ca n be predicted at a given level of X (control 
costs). This means the coordinates of an optimal level of control or the cost of control for a 
given error rate (for example the cost of achieving the 2%  materiality crit erion used by the 
European Court of Auditors) can be estimated.   
                                                
 
1 In mathematics, the logarithm of a number to a given base is the power or exponent to which the base must be 
raised in order to produce the number. For example, the logarithm of 1000 to the base 10 is 3, because 10 raised 
to the power of 3 is 1000. In the logarithmic tren d line, ln(x) stands for the natural logarithm of . To compute a 
logarithmic trend line one must plot x against “log y” (for example x1,log y1) and (x2, log y2), then draw a 
straight line between these points on a graph and calcu late the equation of the gradient using Y = cX + b Rate of undetected 
errors (Y) 
Cost of 
control (X) Current rate 
Current 
cost of 
control 0% 
Cost of 
control for 
all open 
projects Cost of 
control at 
Tolerable 
Risk Point Rate at 
Tolerable 
Risk Point   (A) 
  (B) Tolerable Risk 
Point 
  
 72.2.3.  Testing the model  
 
It is essential to acknowledge that the shape of the curve can have a material difference in 
setting the optimal level of cont rols. Therefore the model was te sted using more sophisticated 
mathematical approaches.  The following modifications of the model were introduced:  
• introduction of  "control sc ope" (% of projects) (A) 
• introduction of a more realistic parabolic equation for the cost of control function, 
taking account of fixed and variable costs (B) 
• introduction of the concept of "opportunity  cost" (C) and a "combined cost curve" 
(D), combining the cost of c ontrols and the opportunity cost 
• introduction of a "benefit curve" (consist ing of recovery order), current benefit 
being equal to zero (E) 
• introduction of "proceeds curve" (benefit– control costs) (F) 
• making use of "optimisation" problem solving (maximising proceeds/minimising 
costs) 
 
Graphically this would lead to five curves: 
 
Graph 4 
Co nt r ol sco pe (% of  p r oje cts )Op portu nity/co ntrol CostControl costs (m odified)
Opportunity cost
Combined cost
Benefit (recovered errors)
pr oceeds (benefit - contr ol
cost)(B)(C)
(D)
(E)(F)
(A)
 
 
 When tested within the limits  of the available data, the tests we re found to produce 
comparable results (see below). The simplified model is therefore belie ved to be reasonably 
reliable and to provide a sound basis for a first indication  of where the tolerable risk point 
may lie.  
  
 8 
2.3. General assumptions and calculation methods  
The use of regression relies heavily on the underl ying assumptions being satisfied. In this 
model, the following hypotheses were made: 
 
2.3.1.  General assumptions:  
 
The following assumptions could potentially cause the tolerable risk point to be overestimated:  
 
• Absence of  "lurking" variables : in observational studies, it is essential to eliminate 
bias. For this reason some existing models  make use of conf ounding variables called 
"lurking" variables to take into account more  than one independent variable and reduce 
bias. This is not the case in the model used  as many benefits ar e difficult to quantify 
(such as the additional re duction of errors through the deterrent effect of controls  over 
and above any specific error detected, th e benefits beyond spe nding, the reputational 
risk of the Commission due to fraud, etc). Anal ysis at this stage was therefore limited to 
cost and benefits of controls in purely quantifiable financial terms. 
• All projects need to be controlled to secure 0% error : even if theoretically the 
control chain should be designed to provide "a ssurance" to final beneficiary level, the 
only way to really ensure 100% regularity an d legality of underlying transactions is 
through on-the-spot controls of  all projects at a moment when all costs can be fully 
verified.  
• Extrapolation of errors:  the model excludes extrapolatio n of errors (application of 
corrections of systemic errors to non-a udited projects) and th erefore requires 100% 
audit coverage since all projects need to  be controlled to el iminate all errors.  
• The cost of controls axis is  project-based
2, meaning that each control is assumed to cost 
the same amount and there are no economies of scale  from simultaneous auditing of 
several projects for the same beneficiary.  
• Homogeneity of the population : when a straight line is used,  the population of projects 
is assumed to be homogeneous in  size and in terms of risk of error. Technically this 
means all the Y distributions have the same spread. This is not likely to be the case in reality since certain types of projects ma y for example have hi gher error rates than 
others. An optimal approach would allow stra tification of the projec ts according to risk, 
taking account of policy area, size and natu re of the activity, management mode or 
beneficiary where controls w ould be directed towards highe r risk areas thereby reducing 
risk of undetected e rror at a lower cost. 
 
Two further assumptions in the model could pote ntially cause the tolerable risk point to be 
underestimated:  
• improving existing controls to reduce the error rate, for example through better 
guidance and training, is assumed to have zero cost. 
                                                
 
2 While 'project' is a word which has many different meanin gs within the Commission, it is used in this exercise 
in the context of the Structur al Funds and CAP policy areas. 
  
 9• Audit risk: the model excludes the audit risk (the risk of a control not detecting an 
existing error) as it assumes that  an error rate of 0% would be obtained  if all projects 
were controlled. By excluding the "false nega tives" and assuming th at controls carried 
out identify and correct all errors in a project, we dist ance ourselves from the standard 
control frameworks that rely on the c oncept of "reasonable a ssurance" used to 
acknowledge that even the best control system  cannot avoid all erro rs and an increased 
number of controls could neve r produce a zero level error.  
 
Furthermore three general assumptions are made: 
• The control strategy is  annual:  eliminating all errors on an  annual basis would require 
each project to be audited at the end of each  year (to match with the annual opinion of 
the Court of Auditors required  by the Treaty), although this is not likely to be feasible in 
reality. 
• The economic trade-off between costs and benefits  is only valid as a hypothesis 
insofar as the amount of error detected and recovered resulting from an additional 
control is consequently re-all ocated for additional controls. 
• The examples provided are based on a single y ear and it is assumed that this year is 
representative. 
 
 
2.3.2.  Calculations and methods:  
 
2.3.2.1. Current rate (point A):  
 
To fully understand the methodology presented in this working document, it is essential to distinguish the e rrors detected by the ex ante internal control chain of the 
Commission and its implementation partners (t herefore proving the efficiency of its 
controls put in place) from those discove red by the European Court of Auditors, 
whose findings are outside this control chain. Since many of the proj ects audited in the 
Court's annual sample will not have been subj ect to the full set of controls required by 
legislation over the lifespan of programmes,  the multiannual correc tive mechanisms in 
place (e.g. for cohesion policy) impact th e longer-term error rate. The (annually-
based) tolerable risk point in this illustra tive example is therefore totally distinct from 
the error level at the closure of each  individual (multi-annual) programme. 
The methodology used only focuses on the errors  that the internal control chain had 
not prevented or detected at th e time of the Court's audit. The current rate of error in 
the calculations in this document is theref ore based on the findings of the Court of 
Auditors in their annual repor ts where possible. This estim ation constitutes the first 
point for the construction of the whole model.  
It is important to bear in mind the underlying EU c ontrol concept where ex-ante 
controls are of utmost importance as a prev entive tool and ex-pos t controls fulfil a 
monitoring function as well as  acting as corrective controls. In order not to focus 
disproportionately on th e corrective ex-post controls on ly, the estimated benefits of 
improving the existing ex ante controls at limited or no significant additional cost were 
also brought into the equation (using the DAS 2006 "substantive findings" i.e. findings 
with financial impact accord ing to the Court methodology). 
  
 10 
2.3.2.2.Cost of control for all op en projects (point B):  
While it could be worthwhile to invest ad ditional resources in desk-based and on-the-
spot ex-ante controls, these controls cannot de tect and correct all ty pes of errors. It is 
also necessary to go on-the-s pot to fully control an activ ity ex-post. Controls on the 
spot by the audit bodies are therefore necessa ry to check in detail the legality and 
regularity of underl ying transactions. 
Point B (situated on the X-axis) is calcu lated by multiplying the number of open 
projects not controlled (the to tal population to be controlled ) by the average cost of an 
on-the-spot control for each policy and adding the product to the curre nt control cost. 
The fact that the cost of controlling ever y project on-the-spot is estimated does not 
mean that every cost claim has been aud ited but rather that each open project is 
assumed to be controlled once annually. Other methods were considered for this modelling but the available data were  insufficient to support these.  
 
2.3.2.3.The tolerable risk point: 
 
 
The optimal trade-off between costs and benef its is based on the concept of marginal 
benefit, being the decrease in  error (defined as the amount of error likely to be 
detected and corrected by a control) resul ting from a unit increase in terms of control 
cost. In this logic, it is wo rth carrying out additional contro ls as long as an additional 
Euro spent on controls leads to a reducti on of the error of more then one Euro3. The 
tolerable risk point (represe nted by a star on graph 5) co rresponds to the point where 
the marginal benefit of an extra control becomes equal to its marginal cost. Beyond 
this point an extra euro spent on controls w ould exceed the benefits obtained from this 
additional euro. This means that from a pur ely economic viewpoint the tolerable risk 
of error would not be set lower th an this "tolerable risk point". 
 Graphically this point is re presented by the slope of the tangent of the curve that 
depicts the cost-benefit relati onship. The point where the tangent and the curve touch 
is the point at which the angle of the curv e is 45°/135°, which means that an additional 
euro spent on control at this exact point w ould result in an error of one euro being 
detected and corrected. Mathematically, at this shared point, the first derivative of the curve is equal to the slope of the line (45 ° tangent gradient)
4. 
 
                                                 
3 In technical terms a positive net benefit corresponds to the ratio "benefit derived from marginal increase of cost 
of controls/ marginal increase in terms of cost of control" being greater than one. 
4 Mathematically the slope, or derivativ e, of f(x) at point x is the limit, as  h approaches zero, of [f(x+h)-f(x)]/h. 
Note that the tangent for an 45° radian angle (arithmetically equal to ' 1') is the inverse tangent of an 135° radian 
angle (arithmetically equal to ' -1'). 
  
 11For a negative slope we get the fo llowing graphical representation: 
 
 
Graph 5 
 
 
In theory it could be that for certain ar eas there would be no tolerable risk point 
because it would be cost-effec tive to control all projects. Ma thematically this is linked 
with the notion of elasticity of a curve. In cases where a chart line is steeper than 45° on every point this means it is cost efficient to audit 100% of the projects. In cases of 
very flat chart lines never reaching 45°, this means that controls could be effected as a 
deterrent but could not be ju stified by pure cost-benefit considerations. Therefore the 
model presented uses a tacit assumption wher e we assume the degree of elasticity as 
being sufficiently high to obt ain a meaningful trade-off between costs and benefits.
5 
This approach implies that the size and rela tive risk of the diffe rent projects is not 
taken into account. However, this may be disconnected fro m the true distribution of 
the population. Ideally the "tolerable risk point " would be analysed at project level if 
such data were available. 
 
 
2.4. Illustrative cases  
 
2.4.1.  European Regional Development Fund (ERDF)  
 
The specific nature of the shared manageme nt mode required the approach to take 
account of the following characteristics: 
                                                 
5 'Elasticity' must not be confused with 'slope' as elasticity is the slope of a curve on a log/log graph only and not on a regul ar graph. 
 Rate of undetected 
errors (Y) 
Cost of 
controls (X) Current 
rate 
Current 
cost of 
controls 0% Cost of 
controls for 
all open 
projects Cost of 
controls at Tolerable 
Risk Point Rate at 
Tolerable 
Risk Point   (A) 
  (B) Tolerable Risk 
Point 
      45° 135°       45° 
  
 12 
2.4.1.1.Specificities of the work done  
 
• The estimation of the  error rate  after improvement of ex ante controls  involved the 
analysis of all DAS 2006 errors for the Stru ctural Funds family, classifying each error 
according to whether improved ex ante controls (resulting, for example, from the provision of additional guidance and trai ning by the Commission and the Member 
States) could have prevented it at limited additional cost. The impact of the improved 
ex ante controls on the level of error quoted by the Court of Auditors for the Structural 
Funds in its Annual Report 2006 (at least 12 %) was then estimated, resulting in a 
revised error rate of 9%. 
• The Y-axis indicates the total error rate in relative terms . The corresponding 
monetary amounts of errors are calculated on the basis of the total public expenditure 
for ERDF in 2006 (including national co-financing).  
• For the cost of control exercise , the approach developed t ook account of the fact that 
controls occur at two different levels, name ly at Member State level and Commission 
level. Due to the fact that assurance is gained mainly at Member State level, the model focuses on that part of the control chain.  
• The cost of control for all open projects was calculated on the basis of the product of 
the "number of open projects" and the "avera ge cost of an ex- post control" (both 
estimated for 2006 exercise). This result was added to the current estimated cost of controls to determine a theoretical cost of  controlling all projects on-the-spot annually. 
• To determine the tolerable risk point  the first derivative of the curve was calculated 
and a tangent was drawn at 135° from the X-ax is to touch the curve in order to find the 
shared point where the first derivative of the curve is equal to the slope of the tangent. 
 
2.4.1.2.Assumptions used
: 
 
• The estimation of the  impact of improved ex ante control  was done at Commission 
level and was based on Commission assumptions estimating the impact of better 
Member State controls, essentially following the issue of further guidance and training 
by the Commission and Member States to all the actors concerned and at all levels. No 
consultation of the Member States took place at this stage.  
• It should be noted that the European  Court of Auditors' error rate , on which the 
extrapolation to take account of the improved ex  ante controls was ba sed, relate s to the 
entire Structural Funds fam ily whereas the Commission's de tailed analysis of costs 
and benefits covered only the ERDF. 
• The co-financing rate  used to calculate the total public expenditure was estimated at 
50% (meaning that for every euro paid by th e Commission an additional euro is paid 
by the Member State). In the absence of detailed data, this rate is based on the Court's sample (using a weighted average of the co-financing rates stated in its DAS 2006 
errors). While indicative, the Commission considers this a reasonable approximation 
of the actual figures.  
• The cost of control figures provided by the Member States  were used without any 
revision or adaptation at Commission leve l. The figure obtained is therefore an 
arithmetic sum. However a few Member Stat es did not provide complete information. 
  
 13Despite this the information obtained was deemed to provide a reasonable basis for 
this exercise. Better data would require an extensive data collection exercise at Member State and implementing body level with a commitment from all to provide accurate and complete information. To cater for the possible underestimation of control costs by the Member States, the effect of a 50% increase in costs of control was estimated by the Commission services and is presented below. 
• Number of open projects:  the number used in the calcula tions is an estimate as the 
Member States are not requi red to communicate this info rmation to the Commission. 
However, the estimate was deemed to be sufficiently robust to be used for the purpose of this exercise. In addition, it was assume d that the number of projects is the cost 
driver of an Article 10 audit in the Struct ural Funds. The model therefore disregarded 
the fact that the Article 10 audit is driv en primarily by operational programmes, which 
in turn include system audits and audit plan ning at this level, which are procedures not 
driven primarily by the number of projects. 
• Average cost of an on-the-spot  control : the average cost of controlling a project on-
the-spot was used and not the average cost of performing a contro l assignment (which 
normally means checking a payment claim a ttributed to an operational programme). 
All on-the-spot controls were  assumed to cost the same. 
• The following sensitivity analysis was carried out to cater for possible under- or 
overestimation of two of the most essent ial parameters used in the illustrative 
example, namely  the control costs by the Member States and the number of open 
projects for ERDF: 
Cost of Controls  Error Rate 
simulations €215 Million 
(current cost*) +50%  
( MS level) +100%  
(MS level) 
250,000 2% 4% 5% 
350,000 4% 5% 6% Number 
of open 
projects 450,000 5% 6% 7% 
*including cost of Commission controls 
If the cost of controls by Member States  were 50% higher than estimated by the 
Member States6 or the number of open pr ojects 100,000 higher than the 350,000 
currently estimated by Commission’ services , the tolerable risk point would increase 
by 1 percentage point (to 5%). 
 
2.4.1.3.Enhanced model : 
 
Given the broad assumptions made, the product of  the simplified model could be subject to 
some uncertainty, one aspect being the value of  the results possibly being tainted due to the 
fact that important variables are assumed to be  stable (simplification, preventive effect of 
controls). To identify the possible impact of  this, the model was enhanced, making use of 
parabolic and logarithmic functions.  
 
                                                 
6 Number of art 10 controls being constant and at current cost of Commission controls. 
  
 14The following elements were  introduced: 
• a more realistic parabolic cost of control  function, making use of a "fixed costs" 
constant (being equal to €215 million) and a "variable cost" variable, the second term 
of the equation varying with a calculated exponent7. The basic idea behind the 
parabolic slope is that following a risk analys is, riskier projects would be subject to an 
on-the-spot control first. This means that in order to cover the initial part of the control 
scope, less cost for control is incurred in relative terms, i.e. increasing the control 
scope becomes relatively more expensive the further one goes  along the curve. 
• a logarithmic opportunity cost function (therefore showing a decreasing marginal 
opportunity cost), being the cost incurred, in terms of  unrecovered amounts, at the 
given cost of control level .8  The mirror image of this opportunity cost function 
corresponds to the benefit function (also  logarithmic), being the benefit obtained in 
terms of recovered amounts, at th e given cost of control level .9 
From these equations two further equations are derived. 
• The sum of the cost of control  equation and the opportunity cost  equation make 
the  combined cost function (of parabolic type).  
• The  difference between the benefit  equation and the control cost  equation make 
the proceeds function (of logarithmic type). 
From these functions the slopes were defi ned and the derivative cost function and 
derivative profit function calcula ted. This produced some possibl e "optimal risk points" as 
illustrated in Graph 6: 
                                                 
7 f(x) = A + s*x2, with A = current (fixed) cost of €214. 19 million and s = factor which corresponds to A and the 
coordinate corresponding to ("100 % control scope"; "€2,250 million euro"). Note that the graph of a degree 2 
polynomial of the form f(x) = a0 + a1x + a2x², where a2 ≠ 0 is always a parabola. 
8 For example, at current cost of contro l of €215 million there is an implied level  €2,550 million recoveries (this 
being the error rate of 8.6% multiplied with the total public expenditure of €29.65 billion). The opportunity cost 
if everything is controlled would amounts to €350 million. 
9 For example when the control scope (% of projects controlled) amounts to 100%, the recovered amount would 
be €2,550 million. 
  
 15Graph 6 
 0, 00250, 00500, 00750, 001. 000, 001. 250, 001. 500, 001. 750, 002. 000, 002. 250, 002. 500, 00
01 12 23 34 45 66 77 88 9 1 0 0
Cont rol scope ( % of projects)Opport unit y/c ontrol C ostControl costs
Opportunity cost
Combined cost
Benefit (recovered errors)
proceeds (benefit - control
cost)cost min
proceeds maxcurrent opportunity cost: 2,550 mio euro
c ur rent error: er ror rate 8,6%
current control cost: 215 mio euro(B)
(A)(C)
(D)
(E)(A)
(B)
(C)
(E)(D)
 
Introduced on current data basi s, these equations yielded a comparable result, being a 
tolerable risk point which ranges between  3.4% and 5%.  However, this does not 
guarantee the outcome of the results being bias -free, since the underlying data used are the 
same and present the same uncertainties expl ained above. It is rather the incomplete 
nature of the data (e.g. Member States figur es) instead of the methodology used, that limit 
the scope of the conclusions drawn. 
Since the Court took only one sample for th e Structural Funds in the DAS exercise, no 
distinction can be made between the ERDF and the other structural funds measures. 
However, it is assumed that the results ob tained for ERDF can be, mutatis mutandis, 
extrapolated to the other measures and that the conclusions are therefore valid for the whole structural funds family. 
 
2.4.2.  European Agricultural Fund for Rural Development (EAFRD)
  
 
2.4.2.1.Specificities of the work done : 
 
• The estimation of the error rate  for EAFRD expenditure is based on statistics 
received from Member States on cont rol results regarding agro-environmental 
measures (AEM) concerning expenditure in fi nancial year 2007 since the sample taken 
by the Court on rural development for the DAS 2006 was considered too small to be 
analysed in the same way as for the illustrative example on regional development10. 
The error rate in terms of reductions to cost claims amounts to around 4%.   
• The estimation of the costs of controlling AEM  is based on an estimation and 
analysis of the costs of controls for the European Agricultural Guarantee Fund 
(EAGF) which was carried out by all Member States in the first half of 2007 using a 
                                                 
10 The Court draws a sample which covers the whole of the Agriculture policy area. 
  
 16methodology developed by the Commission. Data collected related to the Guarantee 
section of the EAGGF fund (f inancial year 2005) and take s into account expenditure 
effected by Member State entities con cerned (e. g. accredited paying agencies). 
• The costs of controls  were calculated based on a pro-rata basis taking into 
consideration the number of agents worki ng in full time equivalent (FTE) in the 
relevant entity in relation to the number  of agents dedicated to the corresponding 
control functions or activities.  
• The optimal level of control  was calculated using the firs t derivative of the curve that 
was created using three points, starting from the current cost of controls and the 4% 
residual error rate.  
• Annex 2  contains an overview of the coverage  and the benefits of agro-environmental 
measures, an explanation for the high incide nce of errors in this area, the related 
control framework and further information on the preliminary results at Member State 
level of the first rough estimati on of the cost of controls. 
2.4.2.2. Assumptions used : 
 
• It should be noted that the information pr ovided by Member States is not always 
complete and properly verified and, ther efore, only gives an indication of the 
magnitude of the control costs. This estimation is expressed as an average of the control costs, not including any indication of the marginal costs of any additional 
controls.  
• A sensitivity analysis reveals however that, even if a margin of error of 50% was 
applied for the calculation of the control costs, the conclusions set out in the 
communication would still be valid. 
 
 
  
 173. THE COST OF CONTROLS EXERCISE 
 
In addition to explanations of the methodol ogy used for providing a first indication of 
tolerable risk in two policy areas , this annex also provides inform ation on the results of a first 
estimation of costs of control launched as Acti on 10 of the Action plan towards an Integrated 
Internal Control Framework11, a pilot exercise was launched to assess the costs of control. 
The methodology chosen for this exercise was simple, not time consuming and valid both in 
shared management (Action 10a) and in di rect centralised management (Action 10b). 
 
3.1. Methodology  
 
The whole methodology for estimating the cost of controls is based on th e following three key 
notions:  
• Definition of control: "every function whose objective is to verify the rights of a 
beneficiary". 
• All controlling entities were  to be covered, including th e controlling entities in the 
Member States. 
• The cost of control was calculated on the basis of the number of staff undertaking 
control activities. 
 For the shared management this implied the formula: CC = NF / TF * BE  
Where  CC = Cost of Controls 
NF = Number of FTE involved in control activities 
  TF = Total FTE working in the organisation 
  BE = Budget of the  Entity 
Specificities in direct centralised  management : 
− The cost related to Commission staff was a ssessed by multiplying the full-time equivalent 
staff undertaking control activities by a standa rd staff cost established each year for 
budgetary needs. This cost integrates overhead costs such as infrastructure. 
− The cost of controls related to external contractors was ca lculated as the amount invoiced 
plus the estimated Commission overhead cost s for managing these external contracts. 
 Specificities in shared  management: 
− The same methodology as direct centralised ma nagement was used for the calculation of 
the costs of direct (Commission) c ontrols under shared management.  
− The cost at Member State level was included to provide a comprehensive picture and 
involved data gathering at  local level. This i nvolved all relevant Me mber State authorities 
being asked to estimate the proportion of thei r workforce involved in control activities 
related to EAGGF and ERDF activities and applying this proportion to their total 
administrative budget to provide a first estimation of the cost of controls. 
                                                
 
11 'Commission Action Plan towards an integrated internal control framework', COM(2006)9 
  
 183.2. Results for the Commission services  
 
This section presents some results mainly in line  with the cost of contro ls and therefore in line 
with the methodology described above. All of the services used the year 2006 as the reference 
year except as noted. 
These figures are first estimates and must be seen  in the light of the tolerable risk of error 
exercise. Therefore they do not constitute officially-validated figures of the Commission and must be handled with care, in particular the figures that are based on information relating to 
the Member States.  It is also important to understand that the data cannot be compared between DGs without 
additional information, even if some services may use a similar control strategy and/or budget 
implementation procedures. 
 
 
3.2.1.  European Agricultural Guid ance and Guarantee Fund (EAGGF
 
  
  Agricultural expenditure 2005 
(€ Million) Costs of controls 2005 
(€ Million EUR) Percentage 
breakdown 
EU-25 48,670 100% 2,018 100% 4.1% 
EU-15 44,701 92% 1,799 89% 4.0% 
EU-10 3,969 8% 218 11% 5.5% 
 
3.2.1.1.Specificities of the work done:  
 
• The estimation of control costs in agricultu re was established as a pilot exercise 
for the costs in shared management a nd helped to fine-tune the methodology.  
• For this reason, the data were collected for the exercise in 2005 instead of 2006.  
• The exercise was limited to the EAGGF-Guarantee fund. 
 
3.2.1.2.Key figures (in light of the above table) :  
 
• The total cost of controls amounted €2,018 million (for EU 25). 
• The cost of controls represents globally  4.1% of the funds paid (for EU 25). 
 
  
 19 
3.2.2.  European Regional Development Fund (ERDF)  
 
 
Cost of 
controls 
Article 4 
(2006)  Cost of 
controls 
Article 9 
(2006)  Cost of 
controls 
Article 10 
(2006)  Cost of 
controls 
Article 15 
(2006)  Total Cost of 
MS level 
controls   Cost of 
Commission 
controls 
(2006)   Total 
Cost of 
Control  
   
158       
  10   
31   
3   
202   
13    
     215 
(€ Million) 
 
3.2.2.1.Specificities of the work done : 
 
• The direct control costs were calcula ted for DG REGIO taking into account the 
statutory and external staff for the follo wing type of services : audit, outsourced 
controls, and operational and financial sta ff. The figures reflect the situation for 
2006. 
• Specific cost data gathering by Member States took place at  local level. The 
costs of control figures provided by th e Member States relate to the 2006 
exercise. They were used without any treatment at Commission level, although 
limited checking indicates that for some Member States the data provided was incomplete. The figure obtained is therefore the arithmetic sum (cfr supra). 
• The cost of controls of the Member States takes acc ount of the Article 4 checks 
(management and control systems complian ce by Managing Authorities), Article 
9 checks (certification of expenditure by Paying Author ities), Article 10 checks 
(sample checks on operations of at l east 5% by Implementing Bodies) and 
Article 15 checks (signing-off of the assi stance by "winding- up" Bodies) for the 
EU-25.
12 
 
3.2.2.2.Key figures (in the light  of the table above):  
 
• The total cost of direct contro ls for DG REGIO amount to €13 million. 
• The ERDF cost of controls of the Member  States' (art 4, art 9, art 10 and art 15) 
are estimated at €202 million. 
• The total cost of controls is therefore €215 million. 
• This total cost represents 0.7% of the total public contribution made for that 
year13. 
                                                 
12  See Commission Regulation (EC) No 438/2001 of 2 March 2001 laying down detailed rules for the 
implementation of Council Regulation (EC) No 1260/1999 as regards the management and control systems for 
assistance granted under the Structural Funds. 
13 ERDF payments by the Commission for 2006 were €14,825.09 million and the co-financing rate is estimated 
at 50%. 
  
 20 
3.2.3.  DG Employment and Social Affairs 
  
Cost of 
controls 
Article 4 
(2006) Cost of 
controls 
Article 9 
(2006) Cost of 
controls 
Article 10 
(2006) Cost of 
controls 
Article 15 
(2006) Total Cost 
of MS level 
controls 
(2006) Cost of direct 
controls for 
ESF Outsourced 
audit costs 
(2008) Total Cost of 
Control 
99 
 6 
 20 
 2 
 127 
 13 
 2 
  142 
 
(€ Million) 
 
 
3.2.3.1.Specificities of the work done : 
 
• The staff costs were calculated for th e European Social Fund, using the staff 
situation as at 01/08/2006. At this stag e (in contrast to 2008) there was no 
contract to outsource some ex-post contro ls. A fixed percentage of the costs of 
geographical desk officers was taken into  account (30% of their working time). 
• The outsourced control costs (also consid ered a central cost) were based on an 
estimate for the 2008 exercise. 
• No specific data gathering t ook place at local level. Inst ead, the cost of controls 
at Member State level was estimated in order to provide a comprehensive picture 
of the situation. The figures for DG REGIO we re used to calculat e a pro rata rate 
using the total payments for DG EMPL as numerator and the sum of the payments for DG EMPL and ERDF paymen ts as denominator of the fraction. 
 
3.2.3.2.Key figures
 (in the light of the table above):  
 
• The total central cost of  control for ESF is €13 million for staff and €2 million 
for the audits that are outsourced. 
• The Member State costs (art 4, art 9, art 10 and art 15) are estimated at €127 
million. 
• The total cost of control is therefore estimated at €142 million. 
• This cost represents 0.8% of th e total public contribution for 200614. 
 
                                                 
14 DG EMPL payments by the Commission for 2006 were  estimated at €9,335.59 million with a co-financing 
rate of 50%. 
  
 21 
3.2.4.  DG EuropeAid  
 
 
Ex-ante staff 
costs (2006)  Cost of  
control audits 
(2007)  Cost of audit 
certificates 
(2006)   Total cost of control  
           49                15                  9                    73   
(€Million) 
 
 
3.2.4.1.Specificities of the work done : 
 
• The current cost of control includes staff at headquarters and delegations, the on-
the-spot controls contracted by the Commission and the expenditure verifications via audits contra cted by the beneficiaries. 
• The figures correspond to the cost of  controls for DG EuropeAid only, for 
actions financed by the General Budget. This means the cost of controls related 
to the European Development Fund or DG ECHO, DG RELEX, DG ENLARG, 
and DG DEV activities were excluded. 
 
3.2.4.2.Key figures (in the light of the table above
):  
 
• The total central cost of  control is €73 million. 
• This cost represents 2% of the payments made. 
 
3.2.5.  DG Environment  
 
 
Current ex-post 
control cost   Total ex-ante 
cost (2006)   Cost of audit 
certificates 
(2006)   Total cost of control  
           0.4                2.6                0.6                     3.6    
(€ Million) 
 
3.2.5.1.Specificities of the work done : 
 
• The current ex-post control cost takes account of the staff and mission costs.  
• The ex-ante costs for 2006 were calculated based on 25.45 FTE.  
• The external audits co-financed by the Commission as contracted by the 
beneficiaries (audit certificates) were calculated and included. 
 
3.2.5.2.Key figures (in the light  of the table above):  
 
• The total central cost of  control is €3.6 million. 
  
 22• This cost represents 1.6% of the payments made for the year 2006.   
 
 
3.2.6.  DG Research  
 
Current ex-post 
control cost 
(2007)  Total ex-ante 
cost (2007)   Cost of audit 
certificates 
(2006)   Total cost of control  
            6                17               7                  30 
(€ Million) 
 
 
3.2.6.1.Specificities of the work done :  
 
• The current ex-post control cost were cal culated, resulting from the total number 
of audits closed (either performed by an external company or by the DG's own 
resources) and the personnel costs. 
• The ex-ante costs were calculated fo r 2007, resulting from the number of 
statutory agents and external staff working as FTE controllers. 
• The external audits co-financed by the Commission as contracted by the 
beneficiaries (audit certificat es) were calculated for 2006. 
 
 
3.2.6.2.Key figures (at the li ght of the table above ):  
 
• The total cost of control is €30 million. 
• This cost represents 0.9% of the payments made.  
 
3.2.7.  DG Information Society  
 
Current ex-post 
control cost   Total ex-ante 
cost (2007)   Cost of audit 
certificates 
(2006)   Total cost of control  
2 32 6 40 
(€ Million) 
 
 
3.2.7.1.Specificities of the work done : 
 
• The numbers for the staff in 2006 were used. 
• The costs for on-the-spot controls refer to those launched in 2006 under the 
Audit Framework Contract. 
• The number of on-the-spot controls ca rried out in 2006 (about 200) was used. 
  
 23• Institutional assessments (joint management ) and audits carried out as a result of 
OLAF investigations have been excluded. 
• The average cost of expenditure verificat ion as foreseen by the beneficiaries in 
the planned budgets was calculated on the basis of a sample of 24 grant budgets 
using the estimated costs for an audit.  
 
3.2.7.2.Key figures (in the light  of the table above):  
 
• The total cost of control is €40 million. 
• This cost represents 3.2% of the payments.  
 
 
3.2.8.  Other Services  
 
Against the background of Action 10 of the Action plan of  the Commission, an 
extension of the cost of cont rol exercise was launched late  in 2007 to assess the cost of 
controls of DG ECHO, DG J RC, DG SANCO and DG TREN.  
 
The costs of control can be summarised in the following table: 
 
   DG ECHO   DG JRC  DG SANCO   DG TREN  
 Total cost of 
control (2007) 25 4 1.1  11.2 
 % of the total 
budget  (2007) 3.4% 1% 0.3% 1.4% 
(€Million) 
 
 
3.2.8.1.Specificities of the work done : 
 
• The data collection was done using 2007 as reference year for all services. 
• DG ECHO takes into account two manage ment modes (joint management and 
central direct management). 
• DG TREN focuses on centralised direct management only. 
 
 
  
 24Glossary:  
 
Audit risk: represents  the risk of the auditor providing an inappropriate opinion on the 
financial statements. In other word s, it is the risk of the auditor stating the financial statements 
present fairly the financial position of the entity, when in fact they do not.  
 
Article 4 checks : the first level checks carried out by the Managing Authorities of the 
Member States, as laid down in the rules fo r implementation of Council Regulation (EC) No 
1260/1999 as regards the management and control systems for assistance granted under the 
Structural Funds.   
Article 9 checks : the certification of the expenditure car ried out by the Payi ng Authorities as 
laid down in the rules for implementati on of Council Regulation (EC) No 1260/1999 as 
regards the management and control systems for assistance granted under the Structural 
Funds.  
Article 10 checks : the sample checks on operations of at least 5% of the total of eligible 
expenditure that need to be carried out by the audit bodies of the Member States, as laid down 
in the rules for implementation of Council Regulation (EC) No 1260/1999 as regards the 
management and control systems for assist ance granted under the Structural Funds.  
 
Article 15 checks : the declaration of winding-up of the assistance by the winding-up body, as 
laid down in the rules for implementati on of Council Regulation (EC) No 1260/1999 as 
regards the management and control systems for assistance granted under the Structural 
Funds.  
 
Break-even point (BEP) : the point where the cost of controls equals the benefits (defined as 
the value of error likely to be detected by a control). Beyond this point an extra euro spent on 
controls would exceed the benefits (reducti on in error rate in %) obtained from it. 
 
Control risk:  represents the risk that errors or irre gularities in the underl ying transactions will 
not be prevented, detected and co rrected by internal control systems (either at the desk or on 
the spot). 
 
Elasticity : In economics, elasticity is the ratio of the percent change in one variable to the 
percent change in another variab le. It is a tool for measuring the responsiveness of a function 
to changes in parameters in a relative way. Elasticity is a popular tool among empiricists 
because it is independent of uni ts and thus simplifies data an alysis. In mathematical terms 
elasticity can be defined as the ratio of the in cremental change of the logarithm of a function 
with respect to an incremental change  of the logarithm of the argument. 
 
Ex-ante control: Ex ante verification of an operation repr esents all the ex an te checks put in 
place by the authorising officer responsible in order to verify its operational and financial 
aspects. According to the Financial Regulation, each operation shall be s ubject at least to an 
ex ante verification. The initiati on and the ex ante a nd ex post verification of an operation are 
separate functions. 
  
 25Ex-post control: the ex post verifications on documents and, where appropriate, on the spot 
check that operations financed by the Gene ral Budget are correctly implemented and in 
particular the expenditure and revenue are in or der and comply with the provisions applicable 
(in particular those of the budget and the relevant  Regulations) and with the principle of sound 
financial management. These verifications may be organised on a sample basis using risk 
analysis.   Inherent risk:  represents the risk linked to the activity itself and therefore related to the 
nature of the activities. 
 
Regression analysis : a curve fitting technique, used in st atistics and econometrics, which can 
be broken into two categories: linear regression and nonlinear regr ession. Of all the regression 
principles the straight line is the simple.  
Linear trend line : an optimized straight line that is suit able for linear datasets. A dataset is 
linear if the pattern of data points resembles a line. A linear trend line normally displays a 
constant increase or decrease in values. 
 
Logarithm : in mathematics, the logarithm of a number to a given base is the power or 
exponent to which the base must be raised in  order to produce the number. For example, the 
logarithm of 1000 to the base 10 is 3, b ecause 10 raised to the power of 3 is 1000. 
 
Logarithmic trend line : an optimized curve that is ideal if the rate of changes to the data first 
increases or decreases sharply and then stays nearly the same.   Residual risk:  could be defined as the risk linked to th e activity less the amount of error 
detected by controls . Put another way, residual risk is the amount of error likely to remain 
undetected.  
 
Trend line : A graphic representation of trends in da ta series. Trend lines are used for the 
study of problems of prediction, al so called regression analysis. 
  
 26Annex 2 
    
Agro-environmental measures (AEM) in rural development and their control 
 
 
1. Basic principles and descriptio n of agro-environmental measures 
Agro-environment measures aim to encourage farming practices and maintenance activities 
by farmers in view of preserving and enhancin g the rural environment and the environmental 
functions of cultivated landscapes.  
The most common AEM address in particular the following environmental objectives: 
Preservation or enhancement of biodiversity, pr eservation of endangered species, maintenance 
of high nature value ha bitats, preservation of water quality and water resources, soil quality 
and prevention of soil erosion, preservation and enhancement of landscapes and other 
environmental objectives (e.g. mitigation of climate change, prevention of fires). 
In the current programming period 2007-2013 agro -environmental measures are obligatory. 
Around €20.3 billion have been programmed for these measures, making them the biggest 
group of measures within rural development..  
2. Added value of agro-environmental measures 
In 2005, an evaluation of agro-environmental m easures was carried out  by an external 
contractor on behalf of DG AGRI
15.  
As regards the added value and benefits of AEM,  the evaluators concl uded that the measures 
generally achieved their objectives  of preserving and enhanci ng the environment. This was 
confirmed with respect to a wh ole range of issues addressed by AEM: biodivers ity, habitats, 
rare animal breeds and endangered species, wate r quality, water quantit y, soil and landscape. 
Some of the results were of a preliminary nature, as the impacts of AEM on biodiversity, 
habitats, landscapes, water and soil can take a long time to emerge and often depend on site-
specific circumstances. However, for a number of measures, robust fi ndings confirming their 
positive environmental effects were presented. These include: 
• Measures with positive effects concerning th e preservation of biodiversity and habitats:  
Reduction of inputs, diversifi cation of rotations, maintena nce of grasslands, arable 
reversion to grassland and ex tensification, grass strips , maintenance of extensive 
grasslands and grazing, ecological infrastr uctures (hedges and small plots), fallow, 
appropriate mowing dates and methods, reduced tillage, and organic farming. 
                                                 
15  The full evaluation report can be found at:  
http://ec.europa.eu/agriculture/eval/reports/measures/fulltext.pdf . 
  
 27• Measures with positive effects on water quality:  Fallow, diversification of rotations, 
maintenance of grasslands, buffer strips, conve rsion of arable land to grassland, winter 
soil cover, organic farming, and re duction of agri cultural inputs. 
• Measures with positive effects on soil protection:  Conversion of arable land to 
grassland, set-aside (with green  cover), grass strips, green  cover of the soil during 
critical periods, terraces in the areas conc erned by steep slopes, reduced tillage, sown 
fallow and ecological infrastructu res (hedges and small plots). 
3.  Control framework for rural development measures in general and agri-
environmental measures in particular 
On a proposal of the Commission, the Council d ecided for the-post 2007 period to align the 
management and control system for the e xpenditure under the newly created European 
Agricultural Fund for Rural Development (EAFRD) with the EAGGF guarantee system 
(Council Regulation 1290/2005). Thus , in the future, the "atout s" of the EAGF Guarantee 
system, that are largely recognized, will also cover the rural development expenditure. Key 
element is that the annual accounts of the accredited paying agencies will have to be accompanied by an audit opinion and report of an  independent audit service (Certification 
Body), and a statement of assurance signed by the heads of the paying agencies.  
As regards more particularly the control of agro-environmental measures, during the 
programming period 2000-2006, contro llability of agro-environmental measures proved to be 
problematic. The European Court of Auditors, in their special report 3/2005, concluded that 
the verification of the agro-envir onmental measures poses particular problems and is far more 
resource-intensive than verifica tion of the first pillar measur es and other rural development 
measures. 
In order to meet the recommendations of the Court several improvements have been 
introduced to the control framework for agro-environmental measures regarding the 
programming period 2007-2013. 
Regarding the regulatory framework the applic able legislation now re quires that all agri-
environmental commitments and eligibility conditi ons can be controlled according to a set of 
verifiable indicators to be established by Member  States. In order to gui de Member States in 
the application of this provi sion, the Commission provided detailed guidance to Member 
States regarding the controll ability of agro-environmenta l measures (WD RD 10/07/2006 
final). 
As regards the specific control rules for agro -environmental measures the following should be 
noted: All applications for agro-environmental aid measures must be  subject to detailed 
administrative controls (100% administrative controls). These check s include cross-checks 
within the IACS for all parcels and livestock covered by a support measure, in order to detect 
over declaration, double payments, etc. The admi nistrative checks further aim at verifying 
whether the eligibility conditions fo r the specific measure are met.  
Moreover, the applicable legisla tion provides that each year at least 5% of all beneficiaries 
subject to agro-environmental commitments must be subject to on-the-spot controls. 
According to the control statistics submitted by the Member States concerning financial year 
2007, 9% (77 490) beneficiaries of agro-enviro nmental measures have been controlled.  
  
 284. Error rate for expenditure related  to agro-environmental measures 
4.1.  Level of error rate  
In its Annual Report 2006, the European Court of  Auditors noted in point 5.72 that in rural 
development, the agro-environmental measures ar e prone to a high incide nce of errors. In the 
Annual Report 2007, the Cour t again reported that ru ral development is pa rticularly prone to 
errors because of the often complex rules and eligibility conditions. 
The controls carried out by Member States regarding the respect of agro-environmental 
commitments by farmers also confirm that these measures are prone to a higher incidence of 
errors than other. According to statistics re ceived from Member States on control results 
regarding agro-environmental measures conc erning expenditure in financial year 2007, the 
error rate in terms of financial reductions amounts to around 4%.  These data were not 
verified and validated by the certification bodies – and in some  cases were also incomplete. 
They nevertheless confirmed that error rates for agro-environmental measures were higher 
than for other measures in rural development and also significantly higher  than the error rate 
for area aids covered by IACS, wher e the error rate is around 1%. 
4.2. Reasons for higher inherent risk of error  
The reasons why agro-environmental measures are prone to a higher incidence of errors than 
for example purely decoupled area aid measures are multiple.  
It is crucial in this respect to keep in mind that measures pursuing environmental objectives, 
including agro-environment measures, are based on a number of technical requirements, that 
must be implemented in a spatially differen tiated manner, and complied with on a continuous 
basis or at different points in tim e. It is not possible to reap these considerable environmental 
benefits associated with these measures in a simpler way.  
One source of error common to all these measures is the over declaration of either areas or 
animals concerned. In practical terms this m eans, that for AEM the count starts at 1%. 
However, for the following reasons, these measures may be subject to additional errors: 
• Measures consist often of multiple obligations for farmers, such as:  
– Limitations on use of fertilisers and pesticides 
– Specific timing of certain  maintenance activities 
– Requirements as regards the methods used 
– Rotation plans 
– Constraints regarding irrigation 
This inevitably increases the likelihood of multiple errors, which by nature will tend to 
be higher.  
• Compliance must be continuous or at different points in ti me in relation to different 
commitments  
• It may be difficult to establish in all cases unambiguous causality between the 
commitment and the result obtained. As an  example may serve the input reduction of 
nitrate, the result of which not only depends on the actual behavior of the beneficiary, 
but also on weather conditions , soil structure, etc. 
  
 295. Costs of control of agro-environmental measures (AEM): preliminary results at 
Member State level 
In order to calculate the costs of control ling of agro-environmental measures the overall 
control costs were allocated according to the Full Time Equivalent assigned to "other than 
AEM" controls and "AEM" controls at Member  State's level. Comparing the agricultural 
expenditure spent for "other than AEM" with th e costs of controls related to "other than 
AEM", the average costs of controls amount to  3.3 %. As regards agricultural expenditure 
spent for AEM in relation to the costs of controls assigned to AEM, the average costs of controls add up to 21.5 %. E xpressed as a percentage of total public funding for AEM, 
including a 58.8% co-financing part by Member States for the period 2000-2006, the control 
costs for AEM amount up to 13%. 
The average costs
16 of an administrative control17 for a non-AEM is calculated to add up to 
about €90, while for an AEM the average costs are about €235 , i.e. almost 2.5 times higher. The costs for an on-the-spot check of a non- AEM amount to about €520 , while the costs for 
an on-the-spot check of an AEM add up to ar ound €1,100 , i.e. almost twice the amount as for 
a non-AEM. 
                                                
 
16  These average figures are based on in formation provided by the Member States. 
17  For the purpose of this document, the term includes administrative checks as well as other controls such 
as ex-post checks and controls carried out by other bodies such as the paying agencies' internal control 
department.