AFC CHALLENGES
Several factors account for BNPL ’ s traction , including the following :
• A shift toward online shopping
• Accelerated digitalization of finance
• Increased consumer demand for alternative payment options
In addition to consumers , retailers and e-commerce platforms have been quick to adopt BNPL services . They recognize these services ’ potential to boost sales . Furthermore , lax regulatory oversight has allowed BNPL providers to scale their operations quickly . It has also enabled them to expand their services to a broader customer base .
However , the rapid expansion and innovative nature of BNPL also opens another door : One that leads to misconduct .
Vulnerabilities
The new technology and rapid growth of BNPL increases its susceptibility to money laundering and cybercrime . Incipient regulations further enhance its appeal to criminals . Contributing factors include the absence of formal credit checks , time delays in repayments and poor verification processes .
Various entities are behind the rising BNPL fraud , including consumers , professional criminals and merchants . In some cases , even BNPL companies themselves may be involved .
Fraudulent use of BNPL : Strategies and tactics
BNPL fraud can take many forms . The following examples depict four common BNPL tactics :
1 . Identity theft : Bad actors can use stolen credentials to create accounts with BNPL providers , enabling them to make purchases and launder money through the system .
2 . Account takeovers : Criminals can gain access to legitimate BNPL accounts and exploit them for fraudulent activities .
3 . Transaction laundering : BNPL providers may inadvertently facilitate transaction laundering , in which undisclosed businesses use approved merchants ’ credentials to process transactions for illicit goods and services .
4 . Synthetic identity fraud : Fraudsters combine real and fake personal information to create identities and establish BNPL accounts to launder money .
Advancements in technology continuously lead to more sophisticated fraud techniques . Examples include :
• Trojan horses : A BNPL account is created with fake or stolen credentials , and then the fraudster changes the payment method to another stolen account they control .
• Biometric hacking : A BNPL account is created using biometrics data ( e . g ., fingerprints and facial recognition ) acquired by illegal means , such as phishing scams , data breaches or leveraging artificial intelligence ( AI ) to recreate fingerprints from photos .
• Machine learning : Algorithms are employed to identify patterns and learn BNPL system behaviors to mimic “ normal ” user behavior to conduct fraudulent transactions without detection .
To counter these fraudulent tactics , it is necessary to understand the unique AML risks associated with BNPL .
Understanding BNPL risks
The BNPL space is continually adapting , but there are a few themes that AML compliance officers can examine to better understand AML risks .
These include :
a . Rapid growth and broader access to BNPL , which facilitate the movement of illegal funds quickly and in large amounts .
b . Increased one-off purchases , which enable international customers to evade sanctions .
c . Challenges in identifying high-risk customers due to low-quality or incomplete customer data .
d . Anonymity in online transactions , such as naming ambiguities ( e . g ., nicknames , unusual spelling conventions ), that make it harder to assess risk .
BNPL impacts each institution differently . It is important to consider the nature and extent of its relationships with BNPL providers and the types of BNPL services the institution facilitates .
Risk impact
Compliance officers need to establish a risk profile to determine the specific risk impact associated with BNPL services . As detailed in the Federal Financial Institutions Examination Council ( FFIEC ) manual , 6 this can be achieved by assessing risk in the context of inherent risk categories ( e . g ., customer , product , transaction and geography ). Table 1 illustrates what BNPL looks like in the context of key inherent risk factors .
34 acamstoday . org