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Anti Money Laundering – A More Effective, Efficient & Innovative Approach for Financial Institutions

The Business Problem of Anti-Money Laundering Financial Services Firms, subject to the USA Patriot Act including banks, insurance companies, money services firms and casinos face many challenges when it comes to complying with Bank Secrecy Act (BSA) requirements and implementing effective Know Your Customer (KYC) and Anti-Money Laundering (AML) processes and systems. These challenges include:

  • Solution options primarily include packaged software systems that are often a collection of point solutions which are not integrated and make effective management of the overall BSA process more difficult

  • Inadequate access to data and analytics, including internal and external data which is required to effectively investigate suspicious transactions

  • The need for greater innovation, including applying Artificial Intelligence to identify complex money laundering schemes and stay ahead of the miscreants

  • Costly and manual intensive processes with no relief in sight – labor is often 50% of the total process cost

  • Accurately identifying and maintaining counterparty risk profiles on an ongoing basis. This includes having a 360 degree view of counterparty risk across the enterprise.

The United Nations estimates that up to $1 trillion is laundered globally. Since 2011, regulatory fines for Know Your Customer / Anti-Money Laundering (KYC/AML) have risen a whopping 1,300% in the United States. A top regulatory priority, banking regulators have recently asked banks to be more innovative and consider adopting new technologies, such as artificial intelligence, in their approach to preventing money laundering crimes.

Financial Institutions are spending significantly on KYC/AML compliance, but due to fragmented systems solutions, a lack of data and analytics capabilities, the difficulty to innovate in traditional systems and increasing regulatory requirements, a high percentage of the spend (over 50%) is on manual labor. Mid-sized and smaller banks are at a significant cost disadvantage as the fixed cost of basic compliance infrastructure is high.

The consulting firm of McKinsey & Co wrote an excellent whitepaper on the deficiencies of today’s AML systems and processes. I encourage you to read it at:

Clearly, there is an opportunity to make these critical compliance functions not only more efficient, but effective and innovative as well. But how? Applying innovative technical capabilities and lessons learned in other industries can certainly help achieve the objectives of efficiency, effectiveness and innovation, potentially cutting the cost and time to achieve compliance by 20% or more.

Large banks such as JPMorganChase clearly have an interest in applying innovative technical capabilities to KYC/AML processes:

Almost all risk and control functions (think Anti-Money Laundering, Know Your Customer (KYC) and Compliance) could be better performed if we worked with the regulators to streamline what we do and use advanced techniques, like artificial intelligence and machine learning, to improve the outcomes.” (JPMorganChase & Co., 2017 Annual Report, p. 26). Software as a Service is a Better Solution to Money Laundering Today, the options for addressing these problems are limited and include primarily packaged software solutions. At CDAR, we believe the Financial Services industry would be better served by a Software as a Service (SaaS) AML solution based on a private cloud implementation platform.

SaaS solutions are widely available and largely deployed in other parts of these same financial institutions. Examples include and ServiceNow. Indeed, leading software companies such as Oracle are moving aggressively to SaaS based solutions for core financial systems. These solutions have allowed Financial Services firms to improve their processes, better and more effectively manage customer relationships and release innovations to the field more quickly. The AML world could benefit great from this approach. A high-level conceptual architecture of this AML solution would look like the following:

Key features of an effective SaaS based AML solution would include:

  • Integrated KYC/AML Process Management – An integrated AML process management solution, such as AMLP’s award winning Surety system, could form the basis of the solution offering. Redesigned from the ground up, all aspects of the KYC/AML Process are integrated and easily share data. Processes are end-user configurable by business users. In addition, external data sources are much easier to connect to via an API driven architecture. This is a significant improvement on some of the AML market leaders

  • Advanced Data Management, Artificial Intelligence, Advanced Analytics & Reporting – Easy access to internal bank data from multiple data sources, external data from published sources as well as the internet coupled with advanced analytics, artificial intelligence and reporting streamline KYC and investigation processes. Much of the manual effort to find and analyze data is made simpler, faster and better.

  • Highly Secure Private Cloud based Deployment – A private cloud infrastructure would provide the security a Financial Institution requires. The service based model provides not only excellent information security, but allows an institution to implement faster and take advantage of innovative new capabilities.

  • Data Governance & 360 View of a Party – Provide out of the box data governance and 360 degree view of a party to see all of the relationships the bank has with a party (client). DFS 504 compliance is made much easier with integrated data governance for New York based financial institutions.

  • Consumption Based Pricing & Flexible Implementation Approach– Flexible pricing model allows you to “pay by the drink” for what you consume, and upgrade to additional components when ready. This would allow a Financial Institution to keep it’s existing alert management system and add KYC or data & analytics capabilities, with maximum flexibility.

  • Artificial Intelligence & Advanced Analytics Competency Center – It is difficult for a mid-sized or smaller financial institution to cost effectively have the AI capabilities in house to focus on AML issues, just as it would be difficult for each institution to develop it’s own anti-virus solutions. A SaaS provider could develop effective AI and Advanced Analytics countermeasures as part of a Competency Center and quickly implement the advances to all the institutions that are part of the SaaS AML network. This would be a major advantage to the baking system.

Benefits of this Approach There are multiple benefits to this approach. These include:

  • Business Driven vs. IT Driven Update Capabilities – most of today’s packaged software solutions require too much intervention by IT professionals to quickly respond to changes required by new AML schemes or regulatory updates. Having the ability for business based administrators configure and manage AML processes would be much more effective and efficient

  • Faster Implementation – A key constraint of the packaged software solutions is that they are not a solution at all – they are a piece of software. An actual solution requires hardware, data integration, and other capabilities. In the private cloud SaaS model, Financial Institutions would be able to begin implementation much faster because it already includes all the components and capabilities needed for a full solution. Thus, timelines to completion would be shortened

  • Reduced Manual Intervention & Cost – Given the more complete nature of the SaaS solution, including access to data management and analytics capabilities, the time required to investigate a suspicious transaction alert could be greatly reduced. In fact, there is the possibility that an AI solution could complete 80% of the investigation process and present its findings to an investigator for faster closure

  • Much Faster and Better Innovation – The very nature of SaaS based systems allows for innovation to be quickly distributed to the SaaS providers user network. This reduces the burden on smaller and mid-sized institutions while providing faster security to the overall banking system.


The requirements for a modern Anti-Money Laundering solution go beyond the capabilities of today’s packaged software solutions. A more complete end to end solution will require advanced data management, analytics, and artificial intelligence capabilities. In addition, the ability to push new innovations to the field quickly will also be key. It is challenging for an individual bank to find and invest in the combined set of talents required to develop this full solution on its own. A software as a service capability based on a private cloud implementation would provide a more complete end to end integrated solution, while also providing shared services capabilities to push innovation to the field faster.

In addition to providing new capabilities, the solution should also provide relief to the bank in terms of the cost of compliance. Today’s BSA/AML processes are inefficient and labor intensive. It is highly plausible that this type of solution could increase efficiency by a factor of 20% or more, based on our experience.

Given the advances in security, data management and analytics capabilities at the major cloud providers such as Amazon, Microsoft and IBM, this solution is not so far off. These providers have made significant advances in security and data management. The private cloud implementation pattern provides an even greater level of security that would minimize risk, accelerate implementation, and reduce cost for most banks.

It is important to realize that the Money Launderer’s are a sophisticated big business – often including nation-state level actors. They are investing in advanced capabilities and skillsets because they have so much to gain from effective money laundering. Stopping this crime will require banks, regulators and the IT world to put its best foot forward to create an effective, efficient and more innovative set of capabilities.

This article was inspired by a December 2018 joint letter from the combined banking regulators to its member regulated institutions. Hopefully, the ideas and vision expressed here will help encourage new thinking regarding the nature of AML solutions.

For More Information

For more information, please contact Michael Andrud, President, FinResults, Inc. (

About the Author: Michael Andrud has significant experience as a senior level banking executive, having been an Executive Vice President at leading financial institutions, including roles as a transformative Enterprise Chief Information Officer and Chief Data Officer. More recently, he was the lead Banking Data & Analytics Partner for IBM’s Global Business Services organization. Michael founded FinResults, Inc., which provides financial institutions with advice and solutions to some of their most complex business problems by leveraging the capabilities of the Cloud, big data, Artificial Intelligence, advanced analytics, and process robotics.


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