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Rapid advances in financial services and technologies facilitate effortless and prompt transactions of money, worldwide. Although, this exposes the financial institutes to the risk of money laundering, thus, making the mission of combating money-laundering more crucial and urgent than ever. According to United Nations Office on Drugs and Crime (UNODC), money worth of approximately 2% - 5% of global GDP is laundered in a year, which ranges from $800 billion - $2 trillion in current US dollars. Governments of varied nations are forming their own regulatory bodies, in order to address money laundering. For instance, the U.K. established National Crime Agency (NCA) in 2013, which ensures to cut down crimes such as money laundering by monitoring high end customers which include lawyers, trust and company formation agents, investment bankers, and accountants.
The report titled “Global Anti-Money Laundering (AML) Software Market” provides an in-depth analysis of the key development strategies and market trend dynamics which includes drivers, challenges, and opportunities prevailing in the industry. The report provides an extensive insight into various forms of developments, trends and key participants.
The Global AML Software market estimation has been built on detailed assumptions and limitations. The market has been estimated by the type of software, their deployment type, and geographical analysis.
The report profiles 16 organizations across different geographies that allows the readers to gain an insight into the various industry trends.
Key questions answered in the report:
• What are the major market drivers, challenges and opportunities in the global AML software market?
• What is the supply chain for the global AML software market?
• What is the market value of AML software market for different software?
• What is the market value of AML software market for different deployment type on the basis of on-premise and cloud?
• What is the market value of AML software market on the basis of different geographical regions?
• Which geographical location will dominate the AML software market?
• What will be the growth rate of different segments of the AML software market during the forecast period?
• Who are the key players for the AML Software market?
• What are the key developmental strategies implemented by the key players to stand out in this market?
• What is the market share of the leading players in the global AML software market for 2016?
| TABLE OF CONTENT | ||
| Executive Summary | ||
| 1 | Research Scope and Methodology | |
| 1.1 | Scope of the Report | |
| 1.2 | Global Anti-Money Laundering Software Market Research Methodology | |
| 2 | Market Dynamics | |
| 2.1 | Drivers | |
| 2.1.1 | Increased Need for Automated Transaction Monitoring Systems | |
| 2.1.2 | Compliance Requirement with International Regulatory Bodies | |
| 2.1.3 | Integration of Big Data Analytics with Anti-Money Laundering Software | |
| 2.2 | Restraints | |
| 2.2.1 | Risk of Security Breaches | |
| 2.2.2 | High Implementation Cost of AML Software | |
| 2.2.3 | AML Software Integration into Existing Systems | |
| 2.3 | Opportunities | |
| 2.3.1 | Anti-Money Laundering Software in Crypto currency Market | |
| 2.3.2 | Adoption of AML in the Emerging Economies | |
| 2.3.3 | Robotic Process Automation (RPA) in AML and KYC | |
| 3 | Industry Analysis | |
| 3.1 | Patent Analysis | |
| 3.2 | Consortium, Associations and Regulatory Bodies | |
| 3.3 | Value Chain Analysis | |
| 4 | Competitive Landscape | |
| 4.1 | Key Market Developments & Strategies | |
| 4.1.1 | Mergers & Acquisitions | |
| 4.1.2 | Partnerships, Collaborations & Joint Ventures | |
| 4.1.3 | Product Launches | |
| 4.1.4 | Business Expansion | |
| 4.2 | Market Share Analysis | |
| 5 | Global Anti Money Laundering Software Market, by Delivery Model | |
| 5.1 | Assumptions and Limitations for Analysis and Forecast of the Global Anti Money Laundering Software Market | |
| 5.2 | Market Overview | |
| 5.3 | Cloud Based Delivery Model | |
| 6 | Global Anti-Money Laundering Software Market by Software Type | |
| 6.1 | Market Overview | |
| 6.2 | Transaction Monitoring Software | |
| 6.3 | Currency Transaction Reporting Software (CTR) | |
| 6.4 | Customer Identity Management Software (CIM) | |
| 6.5 | Compliance Management Software | |
| 6.6 | Others (Sanction Screening Software and Case Management Software) | |
| 7 | Global Anti Money Laundering Management Software Market, by Region | |
| 7.1 | Market Overview | |
| 7.2 | North America | |
| 7.2.1.1 | The U.S. | |
| 7.2.1.2 | Canada | |
| 7.2.1.3 | Mexico | |
| 7.3 | Europe | |
| 7.3.1 | Europe, by Country | |
| 7.3.1.1 | Germany | |
| 7.3.1.2 | U.K. | |
| 7.3.1.3 | Italy | |
| 7.3.1.4 | Spain | |
| 7.3.1.5 | Rest of Europe | |
| 7.4 | Asia-Pacific | |
| 7.4.1 | APAC, by Country | |
| 7.4.1.1 | Australia | |
| 7.4.1.2 | China | |
| 7.4.1.3 | India | |
| 7.4.1.4 | Japan | |
| 7.4.1.5 | Singapore | |
| 7.4.1.6 | Rest of APAC | |
| 7.5 | Rest of the world (RoW) | |
| 8 | Company Profiles | |
| 8.1 | ACI Worldwide | |
| 8.1.1 | Company Overview | |
| 8.1.2 | Product Portfolio | |
| 8.1.3 | Financials | |
| 8.1.3.1 | Financial Summary | |
| 8.1.4 | SWOT Analysis | |
| 8.2 | AML Partners | |
| 8.2.1 | Company Overview | |
| 8.2.2 | Product Portfolio | |
| 8.2.2.1 | Corporate Summary | |
| 8.2.3 | SWOT Analysis | |
| 8.3 | Targens | |
| 8.3.1 | Company Overview | |
| 8.3.2 | Product Portfolio | |
| 8.3.2.1 | Corporate Summary | |
| 8.3.3 | SWOT Analysis | |
| 8.4 | BAE Systems | |
| 8.4.1 | Company Overview | |
| 8.4.2 | Product Offerings | |
| 8.4.3 | Financials | |
| 8.4.3.1 | Overall Financials | |
| 8.4.3.2 | Segment Revenue Mix | |
| 8.4.3.3 | Geographic Revenue Mix | |
| 8.4.3.4 | Financial Summary | |
| 8.4.4 | SWOT Analysis | |
| 8.5 | Global Radar | |
| 8.5.1 | Company Overview | |
| 8.5.2 | Product Portfolio | |
| 8.5.2.1 | Corporate Summary | |
| 8.5.3 | SWOT Analysis | |
| 8.6 | Route Trading | |
| 8.6.1 | Company Overview | |
| 8.6.2 | Product Portfolio | |
| 8.6.2.1 | Corporate Summary | |
| 8.6.3 | SWOT Analysis | |
| 8.7 | Safe Banking Systems | |
| 8.7.1 | Company Overview | |
| 8.7.2 | Product Portfolio | |
| 8.7.2.1 | Corporate Summary | |
| 8.7.3 | SWOT Analysis | |
| 8.8 | Infrasoft Technologies Ltd. | |
| 8.8.1 | Company Overview | |
| 8.8.2 | Product Portfolio | |
| 8.8.2.1 | Corporate Summary | |
| 8.8.3 | SWOT Analysis | |
| 8.9 | Experian PLC | |
| 8.9.1 | Company Overview | |
| 8.9.2 | Product Portfolio | |
| 8.9.3 | Financials | |
| 8.9.3.1 | Financial Summary | |
| 8.9.4 | SWOT Analysis | |
| 8.10 | Fiserv Inc. | |
| 8.10.1 | Company Overview | |
| 8.10.2 | Product Portfolio | |
| 8.10.3 | Financials | |
| 8.10.3.1 | Financial Summary | |
| 8.10.4 | SWOT Analysis | |
| 8.11 | NICE Actimize | |
| 8.11.1 | Company Overview | |
| 8.11.2 | Product Portfolio | |
| 8.11.3 | Financials | |
| 8.11.3.1 | Financial Summary | |
| 8.11.4 | SWOT Analysis | |
| 8.12 | Oracle Corporation | |
| 8.12.1 | Company Overview | |
| 8.12.2 | Product Portfolio | |
| 8.12.3 | Financials | |
| 8.12.3.1 | Financial Summary | |
| 8.12.4 | SWOT Analysis | |
| 8.13 | Accuity | |
| 8.13.1 | Company Overview | |
| 8.13.2 | Product Portfolio | |
| 8.13.2.1 | Corporate Summary | |
| 8.13.3 | SWOT Analysis | |
| 8.14 | LexisNexis | |
| 8.14.1 | Company Overview | |
| 8.14.2 | Product Portfolio | |
| 8.14.2.1 | Corporate Summary | |
| 8.14.3 | SWOT Analysis | |
| 8.15 | Inetco Systems Limited | |
| 8.15.1 | Company Overview | |
| 8.15.2 | Product Portfolio | |
| 8.15.2.1 | Corporate Summary | |
| 8.15.3 | SWOT Analysis | |
| 8.16 | FICO | |
| 8.16.1 | Company Overview | |
| 8.16.2 | Product Portfolio | |
| 8.16.3 | Financials | |
| 8.16.3.1 | Financial Summary | |
| 8.16.4 | SWOT Analysis | |
| List of Tables | ||
| Table 1 | Examples of Some Regulatory Bodies, Associations, and Consortia | |
| Table 2.1 | Comparison between Manual and Automated Anti-Money Laundering Software | |
| Table 2.2 | Government Regulatory Bodies of Various Regions | |
| Table 2.3 | Legal Petitions | |
| Table 2.4 | Company Size and Required Percentage Investment for Anti-Money Laundering Software Implementation | |
| Table 2.5 | Emerging Nations with New Regulations to Fight Money Laundering | |
| Table 3.1 | Examples of Some Recent Patents (Feb 2015-2017) | |
| Table 3.2 | Examples of Some Regulatory Bodies, Associations, and Consortia | |
| Table 4.1 | Key Mergers & Acquisitions (2014-17) | |
| Table 4.2 | Key Partnerships & Collaborations (2014-17) | |
| Table 4.3 | Key Product Launches (2014-17) | |
| Table 4.4 | Key Business Expansion Activities (2015-17) | |
| Table 4.5 | Key Global AML Software Vendors | |
| Table 5.1 | Global AML Software Market Value by Deployment Type ($Million) | |
| Table 6.1 | Global Anti-Money Laundering Software Market by Software Type, 2016-2021 | |
| Table 6.2 | Global AML Transaction Monitoring Software Market by Deployment Type, 2016-2023 | |
| Table 6.3 | Global AML Transaction Monitoring Software Market Penetration by Region, 2016-2023 | |
| Table 6.4 | Global AML Currency Transaction Reporting Software Market by Deployment Type, 2016-2023 | |
| Table 6.5 | Global AML Currency Transaction Reporting Software Market Penetration by Region, 2016-2023 | |
| Table 6.6 | Global AML Customer Identity Management Software Market by Deployment Type, 2016 to 2023 | |
| Table 6.7 | Global AML Customer Identity Management Software Market Penetration by Region, 2016 to 2023 | |
| Table 6.8 | Global AML Compliance Management Software Market by Deployment Type, 2016-2023 | |
| Table 6.9 | AML Compliance Management Software Market Penetration by Region, 2016-2023 | |
| Table 6.10 | Global AML Other Software Market by Deployment Type, 2016-2023 | |
| Table 6.11 | AML Other Software Market Penetration by Region, 2016-2023 | |
| Table 7.1 | AML Software Market Value by Region, 2016-2023 | |
| Table 7.2 | BASEL AML Index Scores in 2017 | |
| Table 7.3 | Penalties charged by FinCEN to various organisations, 2016-2017 | |
| Table 7.4 | Compliance Examinations, by Sector, 2013-2015 | |
| Table 7.5 | Entities AML/CFT Supervision, 2017 | |
| Table 7.6 | BASEL AML Index Scores, in 2017 | |
| Table 7.7 | Number of STRs reported in 2010 and 2013 | |
| Table 7.8 | BASEL AML Index Scores in 2017 | |
| Table 7.9 | Money Laundering Cases in India | |
| Table 7.10 | Number of STRs, 2013 and 2014 | |
| List of Figures | ||
| Figure 1 | BASEL Anti-Money Laundering (AML) Index Scores, 2017 | |
| Figure 2 | AML Monitoring and KYC Technology Spending: Percentage of Respondents, 2015 | |
| Figure 3 | Global AML Software Market Value Snapshot ($Million) | |
| Figure 4 | Global AML Software Market Value Snapshot by Deployment Type ($Million) | |
| Figure 5 | Global AML Software Market Value Snapshot by Software Type ($Million) | |
| Figure 6 | Global AML Software Market Value Snapshot by Region ($Million) | |
| Figure 1.1 | Global Anti-Money Laundering Software Market Segmentation | |
| Figure 1.2 | Secondary Data Sources | |
| Figure 1.3 | Top-Down Approach | |
| Figure 1.4 | Global Anti-Money Laundering Software Market Influencing Factors | |
| Figure 1.5 | Assumptions and Limitations | |
| Figure 2.1 | Market Dynamics | |
| Figure 2.2 | Cost Breakdown of AML Software | |
| Figure 3.1 | Industry Analysis Segments | |
| Figure 3.2 | Anti-Money Laundering Software: Value Chain Analysis | |
| Figure 3.3 | Anti-Money Laundering Software: Core Necessities | |
| Figure 3.4 | Key Features of an Anti-Money Laundering Compliance System | |
| Figure 4.1 | Strategies Adopted by Key Players | |
| Figure 4.2 | Recent Market Development Strategies Snapshot: Analysis (January 2014-October2017) | |
| Figure 4.3 | Key Vendors’ AML Software Deployment Breakdown, (2016) | |
| Figure 4.4 | Key Vendors Market Share Analysis, (2016) | |
| Figure 5.1 | Global AML Software Market Value Snapshot by Deployment Type ($Million) | |
| Figure 5.2 | Advantages of On-Premise Delivery Model | |
| Figure 5.3 | Disadvantages of On-Premise Delivery Model | |
| Figure 5.4 | Anti-Money Laundering Software Market Value, by On-premise Deployment Model | |
| Figure 5.5 | Factors Limiting Enterprises from Using Cloud Computing Services, by Type of Enterprise, in 2014 | |
| Figure 5.6 | Advantages of Cloud Based Delivery Model | |
| Figure 5.7 | Disadvantages of Cloud Based Delivery Model | |
| Figure 5.8 | AML Software Market Value, by Cloud based Deployment Model (2016-2023), $Million | |
| Figure 5.9 | Use of Cloud Computing Services in Enterprises, in 2016 | |
| Figure 6.1 | Global Anti-Money Laundering Software Market by Software Type, ($Million) | |
| Figure 6.2 | Working of an AML Transaction Monitoring Software | |
| Figure 6.3 | Format of an AML Currency Transaction Reporting Software | |
| Figure 6.4 | Status of Financial Firms in the Current CTR System | |
| Figure 6.5 | ALM Customer Identity Management Applications and Systems | |
| Figure 6.6 | ALM Compliance Management Process | |
| Figure 6.7 | ALM Compliance Management Features | |
| Figure 6.8 | Sanction Screening System Process | |
| Figure 6.9 | Case Management System Architecture | |
| Figure 6.10 | Features of Sanction Screening and Case Management Software | |
| Figure 7.1 | Global AML Software Market Value Snapshot by Region ($Million) | |
| Figure 7.2 | Number of complaints reported to FTC, 2006-2015 | |
| Figure 7.3 | Comparison of Large Cash Transaction, Suspicious Transaction Report, and Casino Disbursement, in Canada (2013 and 2015) | |
| Figure 7.4 | Monetary Penalties Issued Across Canada, from 2013-2016 | |
| Figure 7.5 | Comparison of Suspicious Transaction Report, 2008 and 2013 | |
| Figure 7.6 | Comparison of Suspicious Transaction Report, 2010 and 2013 | |
| Figure 7.7 | Comparison of Suspicious Transaction Reports in Italy, 2010 and 2014 | |
| Figure 7.8 | Number of People Convicted and Prosecuted in Italy, 2010-2013 | |
| Figure 7.9 | Comparison of Suspicious Transaction Report, 2010 and 2013 | |
| Figure 7.10 | Number of People Convicted and Prosecuted in Spain, 2010 and 2013 | |
| Figure 7.11 | Comparison of Suspicious Transaction Reports in China, 2010 and 2013 | |
| Figure 7.12 | Comparison of Suspicious Transaction Reports, 2010 and 2013-14 | |
| Figure 7.13 | Number of STR’s for Reporting Institution Types, 2010 | |
| Figure 7.14 | Number of Suspicious Transaction Reports in Japan, 2013-2014 | |
| Figure 7.15 | Number of Suspicious Transaction Reports, 2013-2015 | |
| Figure 7.16 | Number of Prosecutions and Convictions, 2013 and 2014 | |
| Figure 8.1 | Overall Financials, 2014-16 ($Million) | |
| Figure 8.2 | Geographical Revenue Mix, 2014-16 ($Million) | |
| Figure 8.3 | Segment Revenue Mix, 2014-16 ($Million) | |
| Figure 8.4 | ACI Worldwide – SWOT Analysis | |
| Figure 8.5 | AML Partners – SWOT Analysis | |
| Figure 8.6 | Targens – SWOT Analysis | |
| Figure 8.7 | BAE Systems – Overall Financials, 2014-2016 | |
| Figure 8.8 | BAE Systems – Business Segment Revenue Mix, 2014-2016 | |
| Figure 8.9 | BAE Systems– Geographic Revenue Mix, 2014-2016 | |
| Figure 8.10 | BAE Systems – SWOT Analysis | |
| Figure 8.11 | Global Radar – SWOT Analysis | |
| Figure 8.12 | Route Trading – SWOT Analysis | |
| Figure 8.13 | Safe Banking Systems – SWOT Analysis | |
| Figure 8.14 | Infrasoft Technologies Ltd. – SWOT Analysis | |
| Figure 8.15 | Overall Financials, 2014-16 ($Million) | |
| Figure 8.16 | Geographical Revenue Mix, 2014-16 ($Million) | |
| Figure 8.17 | Segment Revenue Mix, 2014-16 ($Million) | |
| Figure 8.18 | Experian PLC – SWOT Analysis | |
| Figure 8.19 | Overall Financials, 2014-16 ($Million) | |
| Figure 8.20 | Segment Revenue Mix, 2014-16 ($Million) | |
| Figure 8.21 | Geographic Revenue Mix, 2014-16 ($Million) | |
| Figure 8.22 | Fiserv Inc. – SWOT Analysis | |
| Figure 8.23 | Overall Financials, 2014-16 ($Million) | |
| Figure 8.24 | Segment Revenue Mix, 2014-16 ($Million) | |
| Figure 8.25 | Geographic Revenue Mix, 2014-16 ($Million) | |
| Figure 8.26 | NICE Actimize – SWOT Analysis | |
| Figure 8.27 | Overall Financials, 2014-16 ($Million) | |
| Figure 8.28 | Segment Revenue Mix, 2014-16 ($Million) | |
| Figure 8.29 | Geographic Revenue Mix, 2014-16 ($Million) | |
| Figure 8.30 | Oracle Corporation – SWOT Analysis | |
| Figure 8.31 | Accuity – SWOT Analysis | |
| Figure 8.32 | LexisNexis Risk Solutions – SWOT Analysis | |
| Figure 8.33 | Inetco Systems Limited – SWOT Analysis | |
| Figure 8.34 | Overall Financials, 2014-16 ($Million) | |
| Figure 8.35 | Segment Revenue Mix, 2014-16 ($Million) | |
| Figure 8.36 | Geographic Revenue Mix, 2014-16 ($Million) | |
| Figure 8.37 | FICO – SWOT Analysis | |
Over the past few years, the financial service industry has witnessed a far-reaching technology-led modifications, with companies looking for improving the efficiency of their financing departments by incorporating innovative IT solutions. In addition, customers have set their expectations and are demanding added worth for their money, along with seamless experience and better services. The banking software industry, in particular, is filled with a range of activities, which are utilizing resources to create value and benefit society, globally, in terms of understanding, exploring, researching, managing, and utilizing financial services. It is expected that in the next decade, the banking industry will witness both revolution and evolution, in terms of facilitating global, multi-service, low-cost, and digital banking. However, with the growth in the banking software industry, there is an increasing demand of regulators to counter the upsurge in financing of terrorism and money laundering incidences.
The global Anti-Money Laundering (AML) software market is expected to reach $1420.8 million by 2023. The growth in the AML software market can be significantly attributed to the following factors: monitoring suspicious transactions, regulatory compliance requirements of financial institutions with international regulatory bodies along with analysis of historical consumer data analysis for risk management.
On-premise deployment type contributed the largest share to the AML software market in 2016, owing to high level of consumer data security provided as compared to cloud deployment. However, cloud deployment is expected to witness the highest growth rate during the forecast period. This delivery model requires monthly or yearly subscriptions which are cheaper as compared to on-premise deployment software. The widespread adoption of cloud based delivery model will be witnessed in future due to the low entry cost as compared to on-premise deployment model. The cloud based deployment model involves the combination of cloud computing with wireless sensor networking, and mobile computing to automatically provide the users with the required data.
Transaction monitoring software had the highest penetration rate in the overall AML software market in 2016, followed by currency transaction reporting, customer identity management, compliance management software, and others. Transaction monitoring software accounted for highest market share in the AML software market for the year 2016, owing to generate full-fledged analysis of a customer, thereby facilitating prediction of risk levels and future money laundering activities, along with providing reports and creating alerts for suspicious activities.
The North American region dominated the AML software market in the year 2016 and will continue to dominate the market, owing to stricter customer identification regulations and compliance for the financial institutions in order to reduce money laundering activities. The Asia Pacific region is expected to foster the highest growth rate in the market during the period, 2017-2023. The factors such as increasing regulatory compliance, adoption of stringent AML regulations, and adoption of the software in various institutions are the major reasons for the constant growth of the AML software market in the region.
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