Facebook’s Libra project has renewed focus on how cryptocurrencies are regulated, with current rules on the sector patchy and varying from country to country.
This week, it was reported that the Financial Action Task Force (FATF), the global anti-money laundering organization, is monitoring the planned Libra cryptocurrency, a signal of the growing scrutiny on cryptocurrency’s potential for money laundering and terrorism financing.
The latest AMC/KYC Tracker examines current efforts to stop money laundering, fight fraud and improve customer identity authentication in the financial services space.
The Cost of Compliance
The projected 2020 cost of AML compliance across all U.S. financial services firms is $26.4 billion, a figure that is set to increase.
Between 2008 and 2018, approximately $26 billion worth of fines were levied against banks for AML, KYC and sanctions noncompliance. A report found that the U.S. imposed a full $23.52 billion – 91 percent – of those penalties.
A recent survey of decision-makers from financial institutions (FI), investment firms and asset management and insurance companies found that many are choosing to proactively ramp up their defenses rather than potentially running afoul of regulations or paying heavily for failing to stop crime.
The drivers of AML initiatives in the U.S. were equally split between regulatory compliance (69 percent) and reputational risk (69 percent), though reputation was a larger motivation among larger companies.
Cloud-based KYC activities were among the new technologies most used by U.S. financial institutions (77 percent) for AML compliance. Nearly all (96 percent) had plans to use cloud-based KYC in the next five years.
Smaller companies were less likely to report investing in and using AML technologies. A 2019 study underscored this point, discovering that even though the AML software market is slated to grow 15.25 percent from 2019 to 2026, the technologies’ high costs and lack of skilled IT professionals prevent the market from doing so more quickly.
Cryptocurrency and Blockchain
Facebook’s Libra project is bringing cryptocurrency into the spotlight, and others are reexamining their onboarding procedures. In July, cryptocurrency exchange IDEX officially ended a policy under which users could remain anonymous while trading up to $5,000. Now the company has enacted security and AML procedures, to the consternation of cryptocurrency advocates.
Digital currency is creating a unique set of challenges due to its high degree of anonymity and ease of cross-border transactions. Regulators are increasingly taking note, with some seeking to improve AML and anti-tax evasion efforts by prohibiting anonymous crypto transactions. Australia began regulating digital currency exchanges and requiring compliance with AML and counterterrorism financing (CTF) rules last year, and in March France’s Finance Committee started banning the trade or distribution of digital assets that enable anonymous dealings.
Blockchain could also potentially help, because the public distribution ledger that records transactions can be independently verified. It’s possible that regulators could require verified wallets to be KYC- and AML-compliant. Customers could enter their personal information to be encrypted and stored on the blockchain, allowing financial institutions to access the transaction history of their digital currency and to verify their identity.
Automation tools are expected to take on the more repetitive tasks involved in AML and KYC compliance, as well as those that entail high levels of data-crunching.
In the aforementioned survey, machine learning and AI showed the most potential for future investments. Those tools had one of the largest gaps between current usage (27 percent) and planned usage (68 percent).
Nicolas Dinh, chief operating officer at payment app startup STACK, spoke with PYMNTS about how synthetic IDs are a major threat and how FIs can mitigate risk. Hackers can use falsified videos to challenge today’s liveness tests, so companies need to keep improving their detection methods to stop deepfakes and other new types of fraud.
Dinh expects to see increased investments in neural networks, sets of algorithms that mimic the human brain to detect patterns in data that deviate from the norm and might indicate illicit takeovers.