How do you help clients manage the balance between regulatory risk and business specific risk in terms of AML? Examples.
The Accounting Professional and Ethical Standards Board (APESB) is an independent, national body that sets the Code of Ethics and Professional Standards with which members of CA ANZ must comply. Members in public practice in Australia need to perform an assessment of a client at the point of acceptance, as well as on a continuous basis.
With regard to the integrity of a client, matters to consider include, the identity and business reputation of the client’s principal owners, key management, related parties and those charged with its governance. We should also take into account indications that the client might be involved in money laundering or other criminal activities and the identity and business reputation of related parties.
When the AML/CTF regulations are expanded to include accountants it is expected that the recommendations will apply to accountants when they prepare for or carry out transactions or activities for their clients, including buying and selling real estate, managing client money, securities or other assets and the management of bank, savings or securities accounts.
Australia and New Zealand are members of the Financial Action Task Force (FATF), which has money laundering (ML) obligations for accountants, centred on customer due diligence, internal controls and special measures for mitigating risks around foreign branches.
The risk-based approach to regulation of the AML/CTF Act would assist some accountants to minimise compliance costs, recognising that it is impractical and inefficient to apply an equal level of vigilance to every client transaction.
Instead, it encourages directing resources and effort towards clients and transactions with a higher potential for money laundering (ML). This means that affected businesses must implement controls that are in proportion to the level of assessed risk of ML that they face. In practice, the risk-based approach requires a professional to consider the ML risk of each client, taking into account relevant risk factors including the type of client, the jurisdictions they deal with, the services they provide and the method through which they provide them, as well as the nature, size and complexity of the client’s business.