Spotting suspicious transactions: Why automation is the future of compliance
The compliance side of Fintech is Regtech, and the same automation technology can drive the growth of safe, legal digital payments.
Southeast Asia’s Internet economy—the fastest and largest growth in the world—is primed for explosive growth. A report by Google, Temasek and Bain & Company found the region’s Internet economy to have crossed the US$100 billion mark for the first time in 2019, with this growth forecasted to reach US$300 billion by 2025.
The catalyst for this growth was identified as the drive towards digital payments. While the latter brings about convenience and serves as an enabler for digital services, it conversely creates challenges specifically around financial crime.
The double-edged sword of digital payments
While the introduction of digital payments has provided unprecedented levels of convenience, it has also elevated risks of financial fraud for digital organizations. These businesses may face challenges in verifying the identities of stakeholders or in tracking the source and destination of funds.
In APAC, regulations against money laundering (AML) and the financing of terrorism (CFT) are constantly updated to address security lapses and boost financial safety. As economies digitalize, regulatory compliance has come under increasing scrutiny and it is being meticulously tracked by the financial authorities, who have put in place massive penalties for breaches. Organizations are aware of the importance of having robust regulatory compliance systems in place, but often leave plans on the back burner due to cost concerns.
The challenge of tackling money laundering activities will be further exacerbated by the rise of digital transactions, which involve vast volumes of data and complexity. The amount of data to be analyzed is growing rapidly, while new business models introduce fresh risks to be monitored. These issues are then compounded by evolving customer preferences that place speed as a top priority.
Typically regarded as an expensive and time-consuming affair that can substantially increase operating costs and manpower requirements, regulatory compliance is usually classified as a cost centre instead of a business necessity. This has created opportunities for “regtech” (the regulatory equivalent of fintech) to play a growing role in modern organizations, with solutions capable of overcoming compliance challenges while simultaneously reducing compliance costs and raising overall productivity.
AI and Machine Learning as game changers
A key problem— and answer—often lies with the technology undergirding AML/CFT technology. Many solutions simply are not designed to manage the sheer scale or demand organizations are contending with today. This can lead to compliance systems and teams being overwhelmed, allowing anomalies to slip through the cracks.
With high-quality risk data being the lifeblood of any effective AML/CFT technology, frontier technologies such as AI are beginning to play a larger role in compliance. Research by Chartis and IBM has determined that a majority of risk professionals are adopting AI-driven compliance processes that can augment the human workforce with better visualization and more effective analytic capabilities.
The use of AI in the creation of risk data can enhance the ability of compliance teams to spot anomalies and previously unknown red flags; extract and identify remote relationships between entities, quickly update affected entities, and enhance existing profiles with more information to drive better decisions.
When screening customer profiles, AI can expedite the process and introduce a higher level of accuracy. In traditional compliance processes, potential mismatches in data are flagged to human teams, who manually check the offending profile against a risk database. In today’s globalized economy, names may be written in varying scripts or be represented differently depending on the cultural norms. This may lead to an extensive volume of false positives that creates bottlenecks in an already tedious and time-consuming task.
AI-driven compliance solutions are able to enhance an organization’s ability to identify risks and reduce errors, placing it in a better position to detect and deter financial crime, and simultaneously remain compliant with regulations. AI systems can ease this process by accounting for the vast number of attributes to assess the probability of a true identify match rather than raising the alert whenever a rule is broken. Such systems can also learn over time from users’ decisions, and proactively suggest changes in the rules to improve the relevance of alerts.
Beyond this, AI also enables much of the transaction monitoring process to be automated on a real-time basis, allowing organizations to redeploy manpower for higher-skilled tasks and reducing overall labour costs.
AI-driven regtech as the future of compliance
Modern organizations face an uphill battle in the fight against money laundering. While seeking to improve efficiencies and reduce operating costs, challenges remain in organizations’ capability to accurately analyze large quantities of data rapidly.
With advances in technology, it is vital for organizations to realize that regulatory compliance does not have to be tedious or expensive. By leveraging technologies such as AI, regtech can help organizations comply more effectively with regulations and detect money laundering activities quickly without compromising the overall customer experience.
Being compliant with regulations will be critical for the continued growth of Southeast Asia’s digital economy. Long term success for organizations will be contingent on the ability to enable stakeholders to engage in the digital economy with confidence and operate in accordance with a continuously evolving set of regulations.
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