a) One of the key elements of Indonesia’s ML/TF strategy is to optimise asset recover efforts. LEAs are well aware of the value in tracing, recovering, and seizing assets that represent the proceeds of criminal conduct and this features regularly in investigations. However, the authorities do not maintain and monitor comprehensive statistics in a consolidated manner to enable Indonesia to develop a mature understanding at the operational policy level that would feed into concrete asset recovery goals that take into account the statistics.
b) Indonesia has a strong legal and organisational framework for the seizure and confiscation of criminal proceeds, instrumentalities, and to some extent, assets of corresponding value (See R.4). To this end, the Asset Recovery Centre (ARC) in the AGO effectively supports, coordinates, and enhances LEAs’ asset tracing and recovery efforts domestically and transnationally. There is also strong coordination among Indonesian authorities to share information to support LEAs’ pursuit of illicit proceeds.
c) The ARC has demonstrated its expertise and capability in the management of illicit assets, such as through timely auctioning of seized assets to preserve their value until the conclusion of the case.
d) The Indonesian authorities have seized and identified a wide range of assets confiscation. However, less than 10% of these confiscations have
been realised to the State. Approximately half of these relate to corruption offences and their assets, which is a significant risk area in Indonesia.
However, there is no evidence that asset recovery in relation to other risk areas, including forestry and environmental crime, narcotics and fraud, and their proceeds are in line with its risk. Although Indonesian authorities pursue illicit assets laundered abroad, the amounts recovered transnationally are low.
e) Indonesia has implemented a CBCC declaration system at all of its ports of entry to detect under/non-declared cash/BNIs as well as through other means such as the use of intelligence searches. DGCE submits these cases as well as all CBCC reports to PPATK. Both applicable sanctions for under/non-declared cash/BNIs and the number of administrative fines issued for this are low given Indonesia’s risk and context.
Recommended Actions
Immediate Outcome 6
a) PPATK, in collaboration with other DNFBP supervisors (e.g., MLHR), should enhance its outreach activities to DNFBPs, in particular to notaries, to improve their STR reporting.
b) PPATK should further develop its operational cooperation with KLHK and BNN to ensure that they are optimising the use of financial intelligence from PPATK in their investigations relating to forestry/environmental crimes and narcotics investigations respectively.
c) PPATK, in collaboration with other FI and DNFBP supervisors, should proactively reach out to reporting entities that have not yet registered with goAML so that they understand their reporting obligations and proceed with their registration on goAML.
Immediate Outcome 7
a) Indonesia should develop a high-level operational policy across competent authorities to ensure that parallel ML investigations are conducted for all appropriate cases.
b) Indonesia should identify and pursue more ML investigations and prosecutions relating to third-party, stand-alone ML cases, and cases involving legal persons.
c) In view of the substantial amounts of proceeds of crime generated, KLHK, supported with appropriate training and resourcing as well as through the adoption of robust internal policies, mechanisms and procedures, should enhance its capability to conduct more ML investigations and prosecutions for forestry and environmental crimes.
d) In view of ML risks relating to corruption, KPK should use its expertise and resources to pursue more ML investigations, particularly complex third party, stand-alone ML cases and ML involving legal persons.
e) Indonesia should enhance the capability of specialist ML investigators and experts in forensic accountancy and forensic examination of digital devices, as well as updating ML training in investigations techniques in relation to the use of emerging technology in ML offences.
Immediate Outcome 8
a) In coordination with all relevant competent authorities, Indonesia should maintain and monitor comprehensive seizure and confiscation statistics in a consolidated manner that allows its authorities to better understand the strategic effectiveness of its AML regime in relation to asset recovery. Based on this, Indonesia should also consider formally developing concrete national and operational policy goals, to be able to monitor and develop confiscation and asset recovery policies that are proactive, optimal and effective.
b) To ensure assets are permanently disengaged from criminals, Indonesia should address challenges faced by LEAs and put in place policies and resources to enhance their ability to seize, ultimately confiscate, and realise assets subject to a court ordered confiscation.
c) Indonesia should enhance its efforts to seize, confiscate and recover proceeds of crime moved offshore.
d) Indonesia should develop the technical and operational capability of KLHK and other civil service investigators to trace criminal assets, pursue asset seizure to effectively overcome operational difficulties in ultimately recovering criminal assets related to forestry and environmental crimes.
e) Indonesia should expand its ability to confiscate property of corresponding value to all types of offences and consider the development of a comprehensive non-conviction based legal framework to add to its asset recovery capability and encourage the use of this by all LEAs as an additional tool to pursue criminal assets.
f) Indonesia should ensure that effective, proportionate and dissuasive sanctions be applied for under/non-declared transportation of cash at all borders, and relevant authorities should regularly follow-up on all suspicion of ML activity arising out of this.
133. The relevant Immediate Outcomes considered and assessed in this chapter are IO.6- 8. The Recommendations relevant for the assessment of effectiveness under this section are R.1, R.3, R.4 and R.29-32 and elements of R.2, 8, 9, 15, 30, 31, 34, 37, 38, 39 and 40.