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Intelligent Screening ISO 20022 payments formats: Opportunities & Challenges


Intelligent Screening of ISO 20022 Payments: How to Benefit from the Opportunities & Meet the Challenges

The recent global survey reported that over 80% of participating central banks plan to implement the International Organisation for Standardization (ISO) 20022 messaging format within the next three years, with over 70 countries already adopting the ISO 20022 format. With the 2025 migration deadline rapidly approaching, it has already become a de facto global standard for financial messaging across the financial services industry[1].

Ross Jones, head of global payments at Barclays, informed an audience of global financial professionals that “over the next four years, ISO will revolutionise the banking sector by improving efficiency, data quality and the ability for organisations to establish enhanced controls.”[2]

The ISO20022 standard provides a common language for financial transactions and enables the exchange of information between different systems, organisations, and countries. It enables richer structured data to be carried in payments messages, adding greater levels of detail which can have a significant impact on payment screening and workflows – bringing  new benefit opportunities as well as adding complexity challenges.


Payment Screening

Payment screening is the process of checking transactions against embargoed and sanctioned entity lists to counter financial crime (terrorist financing or money laundering). With the use of ISO 20022, payment screening has the potential to become more efficient and effective, as financial institutions can now access a greater wealth of information about transactions.

In particular, ISO 20022 enables the transfer of important information such as the purpose of the payment, the structured information of the sender and recipient, including their addresses. This level of detail makes it much easier for financial institutions to identify potential risks associated with a transaction and take appropriate action to prevent sophisticated financial crime.

With the expansion of structured data fields, the XML-based ISO 20022 message standard provides financial institutions with greater opportunities to benefit from the efficiency and performance benefits of deploying AI disciplines such as Machine Learning (ML) algorithms to automate the payment screening process. With the standardization of data, these algorithms can analyse transactions in real-time, reducing the risk of illegal activity slipping through undetected. This not only improves the speed and accuracy of the screening process but also reduces the cost of manual review and reduces the risk of human error.


New Challenges

While richer payments data can provide significant upside benefits for payments participants, there are also a number of new challenges banks and financial institutions face in being able to intelligently screen and in understanding the increased volume of data accompanying each transaction, with the potential for ‘false positive’ flags rising as the number and complexity of data fields increases.

How should each data element be used in the screening process? Should optional supporting payment reference information have to potential to trigger a match or a positive flag?  Different data fields require different screening processes and source lists, whether BIC or LEI codes, named entities including Individuals, Corporates Vessels or Aircrafts against multiple sanctions lists, or other embargo data criteria (city, port, country).

The type to screening logic to deploy can vary for each data element – knowing how best to deeply fuzzy match for all free format information against exact matching for structured identifiers (ISO country codes, BICs, LEIs, etc) is vital to both ensure security and compliance, while avoiding the unnecessary overheads of increased false positives.


Intelligent Approach

An intelligent smart and targeted screening approach is best described as a matrix where transaction data elements and tags appear in rows, while the information it can be matched against is in columns. Each cell can then be used to provide the recommended and appropriate screening behaviour.

Only the appropriate list will then be used to scan each separate data element or tag – with any information not screened fully visible to support alert dispositions in case management tools. This targeted screening approach ensures the correct processing of all payment data, allowing financial institutions to ensure compliance and detect financial crime, while avoiding false positives linked to mismatches between information types (e.g. debtor name incorrectly matching against vessel or street name, etc).


Game Changing
At Pelican, we claim over three decades of payments domain and AI experience and expertise, processing over one billion transactions. As pioneers of the practical application of AI technology along the payments chain, we understand how important it is for financial institutions to achieve both high accuracy matching along with the highest levels of efficiency and reduced false positive rates.

The move to ISO 20022 is transformative for payment screening – with the right approach and technology, it has potential to significantly increase efficiency, accuracy, and cost savings to financial institutions. Its impact will continue to be felt as more and more financial institutions adopt the standard, creating a more secure and efficient financial system for everyone.


[1] https://www.centralbanking.com/benchmarking/payments/7949586/payments-benchmarks-2022-report-on-the-shores-of-a-digital-future

[2] https://www.treasurers.org/events/conferences/cash-management-conference-22