A number of banks have breached regulatory compliance in the past and are now on the radar of financial regulators. Fines, threats to reputation and career brakes are often among the consequences.
Why Regulatory Compliance Software is Becoming More and More Important in Banks
Financial Crime on the Rise – COVID-19 Being One of the Reasons
Banks and regulators are facing an uphill battle to combat financial crime – and the gradient has increased throughout COVID-19. The pandemic has led to a significant increase in fraud, money laundering and terrorist financing as cybercriminals seek to exploit heightened security risks – all while banks face operational challenges resulting from limited services, staff shortages, and suspension of conventional servicing channels such as branches.
Suspicious Activity Reports Related to Money Laundering Flood the Financial Authorities
In a number of countries, such as Germany and Switzerland, suspicious activity records related to money laundering are at record levels. In the UK, the UK Financial Intelligence Unit (UKFIU) saw another record number of suspicious activity reports (SARs) during 2019/20, receiving and processing 573,085 (a 20 percent increase on the previous period). The most significant growth in SARs was seen from financial technology (fintech) companies. They submitted 83,609 SARs in 2019-20 – up 263.94 percent from 2018-19 (22,973). Fintech thus accounted for 64 percent of the total increase in overall SARs.
Regulatory Compliance in Banks needs Automation
As regulators demand more and more transparency, financial institutions need to produce and manage an increasing amount of data. To do so – that is, to gather, analyse, and compute all the necessary data – firms make use of various technology systems and applications. In truth, however, much of this data gathering and analysis still includes manual processes – a huge cost-driver for firms.
Concentrate all Resources on Regulatory Compliance
In the face of increasing regulatory demands and cost pressure, banks are struggling to manage their regulatory compliance obligations. The result is significant compliance risk and the looming threat of regulatory fines – as well as an increased internal focus on administrative tasks as opposed to risk management.
Banks Must Embrace Regulatory Compliance Software
After more than a decade of global regulatory reforms defined by the 2008 financial crisis, deep-cutting changes have reshaped regulatory compliance in banks. They have seen a flood of new laws and regulations come pouring in. Though understandable, the sheer volume of these new rules and standards have created reams of red tape to cut through – making the work of risk and compliance officers more complex and time-consuming, and leaving financial service providers focussing on regulatory compliance rather than innovation.
The answer lies in digitalization. Financial firms need a sustainable, scalable and cost-effective solution to analyse enormous amounts of data more efficiently, identify suspicious activity more easily, and improve and accelerate risk detection and remediation.
The Rise of Regulatory Compliance Software as Beacon of Hope
Regulatory Compliance software uses cutting edge technology like machine learning to help financial firms solve regulatory and compliance issues quickly and at scale. Combining data with the knowledge and expertise of compliance officers, regulatory compliance software quickly and accurately detects complex cases of money laundering and terrorist financing.
Demand for regulatory compliance software has skyrocketed in recent years as organisations struggle to cope with increasing regulatory pressures. Indeed, the global RegTech market is expected to grow from USD 6.3 billion in 2020 to USD 22.2 billion by 2027, at an impressive Compound Annual Growth Rate (CAGR) of 20.1 percent over the forecast period, according to a recent analysis from Research and Markets.
Machine Learning Represents the Brains of Regulatory Compliance Software
Given the increasing complexity of threats and the growing volume of data to analyse, current compliance processes that rely largely on high levels of manual, repetitive and data-intensive tasks are simply inefficient and yield a relatively low impact in terms of detecting risk and fraudulent activity.
The time is now for financial firms to explore the capabilities of AI-powered and purpose-built automated compliance and risk management systems. New regulatory compliance software allows banks to analyse huge volumes of data from numerous sources at exceptionally high speed – automatically flagging up security risks or breaches of the law. Combining data with the knowledge and expertise of compliance officers, machine learning RegTech software quickly and accurately detects complex cases of money laundering and terrorist financing.
Regulatory compliance software slashes the time required to carry out complex analyses and checks, resulting in huge productivity and efficiency gains, while improving accuracy, data quality, and cutting costs – the much-needed solution to scale and adapt to the modern threat and regulatory landscapes.
A surge in criminal activities, shortage of skilled workers, cost pressures and new laws and regulations are exerting increasing pressure on the compliance departments of banks and insurance companies. Come what may, companies are desperate to avoid reputational risk or coming onto the radar of financial regulators. One solution is to use regulatory compliance software that relies on machine learning as a component of artificial intelligence.
Advantages of this approach include scope to analyse large and complex amounts of data efficiently, detect risks from an early stage and boost agility. Intelligent digitalisation enables complex regulatory requirements to be implemented as well as helping mitigate risks and keep costs under control. This means key personnel can focus on the essentials. When selecting the right regulatory compliance software and systems supplier, banks should ensure they have in-depth knowledge of regulatory compliance in banks. They can then be confident they are well equipped to tackle the challenges the future brings.
Whitepaper: Why successful banks and insurance companies now rely on machine learning in compliance
To learn more about how digitalization and machine learning work in the compliance function, download the whitepaper.
Providing an overview of the latest SAR figures, new regulations, and key steps towards automation in compliance, the paper also includes 9 lessons learned that should be considered when implementing machine learning.
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