AI Uptake for AML Compliance on the Rise despite COVID-19
Research suggests that financial institutions are increasingly adopting technologies such as AI and machine learning (ML) for anti-money laundering (AML) compliance in response to the COVID-19 pandemic. A new study by KPMG, SAS and the Association of Certified Anti-Money Laundering Specialists (ACAMS) found that a third of financial institutions are accelerating their AI and ML adoption for AML purposes.
The report based on a survey of more than 850 ACAMS members revealed that AI and ML have emerged as key technologies for compliance professionals, streamlining the AML compliance processes.
Why now more than ever?
In the anti-money laundering (AML) compliance space, the potential for artificial intelligence (AI) is immense. Increasing complexity of AML threats during the COVID-19 times, ever-increasing volumes of data to analyse, false alerts rising to unmanageable levels, ongoing reliance on manual processes and the ballooning cost of compliance are prompting many financial institutions to adopt modern technology and improve their risk profile.
Key takeaways from the survey
The survey primarily asked each respondent how their employer is using or has used technology to detect money laundering. Here are some of the key findings of the survey.
1. Increasing AI/ML adoption
More than half (57%) of respondents said they have either deployed AI/ML into their AML compliance processes, are piloting AI solutions, or plan to implement them in the next 12-18 months. A quarter of respondents describe themselves as ‘industry leaders’ and ‘innovators’ and 24% as fast followers actively watching the progress of the industry pioneers. Meanwhile, 29% recognise themselves as ‘mainstream adopters’ who generally adopt technology once it has hit critical mass in their industry, and 22% as conservative ‘late adopters’ who resist change as long as they can.
2. The COVID-19 impact on adoption
39% of the compliance professionals surveyed said their AI/ML adoption plans will continue unchanged, despite the pandemic’s disruption. Meanwhile, 33% say their AI/ML plans have been accelerated and 28% say their timelines have been delayed due to the pandemic. “For institutions on the AI adoption path, they stayed the course with their AI implementation despite COVID impacts and did not derail or slow implementations,” said Tom Keegan, principal US solution leader for financial crimes at KPMG.
3. The AI/ML impact on AML compliance
There are three ways in which data-driven AI and ML help improve AML compliance: 1) It increases the quality of investigations and regulatory filings, 2) The reduction of false positives and resulting operational costs and 3) It detects complex risks by finding the patterns that traditional transaction monitoring rules cannot.
4. The AI/ML value proposition
When asked about the areas where AI/ML implementation offers the most value, 39% opted for reduction in false positives and negatives at source for the transaction monitoring process. 38% opted for assistance to investigators to get a better answer more quickly and 22% opted for classification of high and low-risk alerts before they are touched.
5. AI/ML implementation
When it comes to the implementation of AI/ML solutions, over half (54%) considered advisory firms and/or technology vendors to be the best source for industry best practices on the adoption. Meanwhile, 22% said industry trade organisations are the most trusted source.
6. Regulatory stance on AI/ML
When asked about their AML regulator’s position on the implementation of AI/ML, 66% said their regulator promotes and encourages these technology innovations. Meanwhile, 28% said their regulator is apprehensive about AI/ML and 6% said their regulator is resistant to change and likely to stick with existing practices.
Small financial institutions are serious about AI/ML
It is not just the large financial institutions that are seeing value through the deployment of AI/ML. According to the report, 16% of smaller financial institutions (valued below US$1 billion) view themselves as industry leaders in AI adoption along with 28% of large financial institutions (with assets greater than $1 billion).
“Seeing a strong percentage of smaller financial organisations label themselves industry leaders debunks the myth that advanced technological solutions are beyond the reach of smaller financial organisations,” says Keegan. “With both smaller and larger organisations subject to the same level of regulatory scrutiny, it’s important these numbers continue to rise.”
Tookitaki’s AI platform for AML compliance
While AI and ML are gaining serious momentum in AML compliance, specifically to reduce false positives, ease caseloads, streamline reporting and save on operational costs, Tookitaki helps both large and small financial institutions with its AI-powered Compliance Platform as a Service (CPaaS).
Globally recognised for its innovation, Tookitaki offers the Anti-Money Laundering Suite (AMLS), an end-to-end AI-powered AML/CFT solution that ensures operational efficiency, low risk and better returns for the banking and financial services (BFS) industry. The solution is validated by leading global advisory firms and banks across Asia Pacific, Europe and North America.
We offer AMLS as a modular or end-to-end platform across the three pillars of AML activity:
- Transaction monitoring
- Name and Transaction screening
- Customer risk monitoring
In order to power AMLS with comprehensive financial crime detection capabilities, Tookitaki has also developed the Typology Repository Management (TRM). TRM brings together information on the latest techniques criminals and terrorists employ to launder money and then provides the insights to address them. It draws on intelligence we gather from AML experts, regulators, financial institutions and industry partners from across the globe. As soon as a new money laundering typology is identified, our technology shares it across the user base to promote crime prevention. As money laundering patterns continue to evolve, our TRM framework will help financial institutions build futuristic AML compliance programs.
Of course, the pandemic has provided criminals with more opportunities to gain and clean their ill-gotten money. However, financial institutions also have options to reform and turbocharge their AML compliance measures through the application of a risk-based approach and the use of modern technology. Powered by advanced machine learning, Tookitaki’s AML compliance solutions can help financial institutions revamp their compliance programs for lower cost of compliance, improved decision accuracy and better automation of repetitive tasks.
For a demo of our award-winning AMLS solution, please contact us.