The Anti-money laundering solutions market in the Asia-Pacific region is expected to exhibit maximum growth over the next few years due to the several innovations done by the regional players and initiatives taken by the regional government to heighten the security of the financial landscape of the countries in the region.
COVID-19 has positively impacted market growth due to a rapid rise in online sales and the increasing use of online payment solutions. A rise in non-cash payments through mobile payments, internet payments, and prepaid cards is increasing the chances of illegal money transactions in recent times. The high-speed execution of transactions coupled with minimal direct interaction between the person initiating the transaction and the service provider has amplified the vulnerability of these new payment methods to money laundering activities.
Companies are increasingly integrating technologies, such as AI, ML, and automation, in their AML solutions to boost the market growth. For instance, 3i Infotech Limited launched an advanced AML solution, AMLOCK Analytics, equipped with Artificial Intelligence (AI) and Machine Language (ML). AMLOCK Analytics uses various statistical methods and machine learning algorithms to derive analyses and predictions based on institution-specific historical data.
Several regional banks and financial institutions are collaborating with global AML solution providers to deploy their solutions, which will help them maintain compliance.
Asia-Pacific is the most developed real-time payments market globally. Thailand is the largest country in the volume recorded 9.7 billion real-time transactions in 2021, the fourth leading country in the world. The widespread adoption of real-time payments resulted in estimated cost savings of USD 1.3 billion for businesses and consumers.
In 2021, Malaysia recorded 1.2 billion transactions, accounting for an estimated USD 434 million in cost savings for businesses and consumers, whereas Singapore witnessed real-time payments transactions hit 256 million and realized approximately USD 105 million worth of cost savings for businesses and consumers.
Real-time transactions and growth are expected to rise continuously, with emerging countries like India leading the way and outpacing developed nations. Governments around the globe that enable real-time schemes are driving economic growth and prosperity by providing consumers and businesses with cheaper, faster, and more efficient payment methods.
Demand for automated transaction monitoring systems is growing substantially in Asia-Pacific, especially in countries like China and India. In the current pandemic scenario, financial institutions face an even larger challenge in AML and terrorist financing. Public firms are taking preventive measures to combat jobless people involved in money mule scams. Financial criminals started developing more advanced money laundering methods as technology advanced. Criminals detect gaps in financial systems and commit crimes such as money laundering and terrorist financing. It is hard for financial institutions to detect and prevent these financial crimes.
So, companies automatically monitor their customers' transactions, such as deposits, withdrawals, and money transfers, and can present any suspicious activity as evidence so that financial institutions can ensure they meet AML Compliance requirements using AML Transaction Monitoring.
The report covers major Asian-Pacific Anti-Money Laundering Solutions Market players. In terms of market share, few major players currently dominate the market. However, with technological advancement and service innovation, domestic to international companies are increasing their market presence by securing new contracts and tapping new markets. Its major players include Accenture, ACI worldwide, BAE system, NICE systems, and SAS Institute.
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COVID-19 has positively impacted market growth due to a rapid rise in online sales and the increasing use of online payment solutions. A rise in non-cash payments through mobile payments, internet payments, and prepaid cards is increasing the chances of illegal money transactions in recent times. The high-speed execution of transactions coupled with minimal direct interaction between the person initiating the transaction and the service provider has amplified the vulnerability of these new payment methods to money laundering activities.
Companies are increasingly integrating technologies, such as AI, ML, and automation, in their AML solutions to boost the market growth. For instance, 3i Infotech Limited launched an advanced AML solution, AMLOCK Analytics, equipped with Artificial Intelligence (AI) and Machine Language (ML). AMLOCK Analytics uses various statistical methods and machine learning algorithms to derive analyses and predictions based on institution-specific historical data.
Several regional banks and financial institutions are collaborating with global AML solution providers to deploy their solutions, which will help them maintain compliance.
Key Market Trends
Rise in the Volume of Wired Transactions Driving the Market
Asia-Pacific is the most developed real-time payments market globally. Thailand is the largest country in the volume recorded 9.7 billion real-time transactions in 2021, the fourth leading country in the world. The widespread adoption of real-time payments resulted in estimated cost savings of USD 1.3 billion for businesses and consumers.
In 2021, Malaysia recorded 1.2 billion transactions, accounting for an estimated USD 434 million in cost savings for businesses and consumers, whereas Singapore witnessed real-time payments transactions hit 256 million and realized approximately USD 105 million worth of cost savings for businesses and consumers.
Real-time transactions and growth are expected to rise continuously, with emerging countries like India leading the way and outpacing developed nations. Governments around the globe that enable real-time schemes are driving economic growth and prosperity by providing consumers and businesses with cheaper, faster, and more efficient payment methods.
Increased Need for Automated Transaction Monitoring Systems Boosting the Market
Demand for automated transaction monitoring systems is growing substantially in Asia-Pacific, especially in countries like China and India. In the current pandemic scenario, financial institutions face an even larger challenge in AML and terrorist financing. Public firms are taking preventive measures to combat jobless people involved in money mule scams. Financial criminals started developing more advanced money laundering methods as technology advanced. Criminals detect gaps in financial systems and commit crimes such as money laundering and terrorist financing. It is hard for financial institutions to detect and prevent these financial crimes.
So, companies automatically monitor their customers' transactions, such as deposits, withdrawals, and money transfers, and can present any suspicious activity as evidence so that financial institutions can ensure they meet AML Compliance requirements using AML Transaction Monitoring.
Competitive Landscape
The report covers major Asian-Pacific Anti-Money Laundering Solutions Market players. In terms of market share, few major players currently dominate the market. However, with technological advancement and service innovation, domestic to international companies are increasing their market presence by securing new contracts and tapping new markets. Its major players include Accenture, ACI worldwide, BAE system, NICE systems, and SAS Institute.
Additional Benefits:
- The market estimate (ME) sheet in Excel format
- 3 months of analyst support
This product will be delivered within 2 business days.
Table of Contents
1 INTRODUCTION
4 MARKET DYNAMICS AND INSIGHTS
5 MARKET SEGMENTATION
6 COMPETITIVE LANDSCAPE
Companies Mentioned (Partial List)
A selection of companies mentioned in this report includes, but is not limited to:
- Accenture
- ACI worldwide
- BAE system
- NICE systems
- Oracle corporation
- SAS Institute
- Fiserv
- Open text corporation
- IBM corporation
- Temenos AG
- eastnets
- Idbi intech*
Methodology
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