Transaction screening plays a key role in protecting financial systems from illicit activity. Thefore it is an essential part of a robust international sanctions implementation programme and overall anti-money laundering and counter-terrorist financing (AML/CFT) framework.
Transaction screening enables financial institutions to alert on possible international sanctions matches, politically exposed person matches, negative media matches or other risk indicators. It does this by analyzing incoming and outgoing transactions and payments.
With financial crime on the rise in the digital payments landscape, coupled with volatile international sanctions regimes and associated evasion schemes, transaction screening provides a crucial protective measure. It prevents criminals from exploiting financial institutions as conduits for their activities.
But what exactly does transaction screening involve? How does it differ from transaction monitoring? What is the best way to ensure an effective process? How does it fit into an organization’s overall compliance process? And what are the key trends and challenges for transaction screening? Discover the ins and outs of transaction screening.
What is transaction screening?
Transaction screening involves assessing financial transactions against various watchlists to identify and block potentially illicit activity.
Organizations widely use it to ensure compliance with international sanctions. And its capabilities depend extensively on the datasets used as the primary source for screening. These datasets can include politically exposed person (PEP) lists and internal watchlists or blacklists. And lists published by law enforcement or regulatory agencies.
Unlike customer screening, which checks customer data, transaction screening helps to ensure regulatory compliance by checking all key payment attributes. The name of the counterparty or ultimate counterparty, the counterparty’s financial institution (BIC code), transaction reference data (e.g. ISIN code for securities), the country of the counterparty and the purpose of the transaction (free text) can be checked to ensure that the transaction itself does not fall under the restrictions of international sanctions and that the screened data does not appear on any other lists that may trigger an increased risk of possible financial crime.
If the analysis of the transaction screening alert confirms hits on international sanctions lists or excessively risky activity, transactions may be frozen, suspended or rejected. Transaction screening has a direct impact on payments. There fore it is vital that the appropriate parameters are selected for the screening system. This will ensure that legitimate businesses are not adversely affected, while complying with regulatory requirements.
Transaction screening vs. transaction monitoring
Real-time transaction monitoring is essential for financial institutions. It is needed to detect and prevent suspicious activity for money laundering and terrorism financing. Or even underlying financial crimes such as fraud. Transaction screening, which includes sanctions screening, is a crucial component of this process. However, the implementation of transaction screening may differ from real-time transaction monitoring.
Some financial institutions make a clear distinction between transaction screening and real-time transaction monitoring, while others consider these processes interconnected. Despite the differences in approach, the ultimate goal remains the same. To freeze assets in real-time to prevent further illicit activities. These illicit activities may be related either to international sanctions violations, sanctions evasion, money laundering or terrorism financing or any other underlying financial crimes.
With this in mind, there are few essential differences within the processes. Automated transaction screening solutions are essentially a set of algorithms used to compare one string of text with another to identify similarities that indicate a potential match. Such matching applies to sanctioned individuals, politically exposed persons, individuals on law enforcement watch lists, regulatory watch lists (including bans on specific services such as financial or gambling services) and even internal watch lists (e.g. individuals who may be identified as posing a higher risk of money laundering or terrorist financing).
Comparison table
Meanwhile, transaction monitoring tools can be broader in scope, incorporating not only screening algorithms to compare data but also sophisticated rules, scenarios, or machine learning tools to analyze whether a transaction exhibits suspicious patterns indicative of underlying criminal activity. These tools can operate in two modes:
- Real-time analysis
This mode involves the immediate suspension of transactions up until the analysis of individual transactions. Or sets of transactions to identify and freeze those deemed suspicious on a real-time basis. The objective is to halt potentially illicit activities instantly.
- Retrospective analysis
This mode focuses on the broader examination of historical data to identify suspicious patterns in overall behavioral activity. While it does not stop transactions in real-time, it helps in detecting and understanding trends and patterns. Those that may indicate criminal behavior over time and prevent it in the future.
Comparison of transaction screening vs. transaction monitoring
| Transaction Screening | Transaction Monitoring | |
|---|---|---|
| Purpose | Identifies potential matches with sanctions lists and other watch lists. | Detects suspicious patterns indicative of financial crimes. |
| Scope | Focused on comparing transaction data to specified lists. | Broader analysis of transaction patterns using rules, scenarios, or ML. |
| Algorithms and tools | Uses algorithms to match text strings to lists of sanctioned entities. | Uses rules, scenarios, and machine learning to analyze transaction data. |
| Operational modes | PEP, international sanctions, adverse media screening | Real-time analysis and retrospective analysis. |
| Transaction freezing on real-time analysis | Applicable for international sanctions screening. | Applicable for real-time monitoring (in exceptional cases, based on the set of advanced rules). Not applicable for retrospective monitoring. |
| Data dependency | Relies on specified transaction data fields. | Utilizes customer data, declared activity, due diligence, and behavior. |
| Key metrics | Match rate of the screening algorithm. | Rule coverage and alert metrics. |
| Risk identification | Immediate identification of risks through matching. | Continuous analysis to detect suspicious behavior over time. |
Metrics for transaction screening and transaction monitoring
For transaction monitoring, customer data is essential in setting up monitoring rules. It includes declared customer activity, customer due diligence data, and behavioral activity while accessing the e-banking system. In contrast, transaction screening relies solely on checking specified transaction data fields.
When comparing the metrics for transaction screening and transaction monitoring, the match rate of the screening algorithm is an essential metric for assessing the efficiency and effectiveness of the service. In contrast, transaction monitoring focuses on rule coverage and various rule alert metrics to evaluate its performance. Transaction screening aims for immediate risk identification, while transaction monitoring continuously analyzes transaction patterns to detect suspicious behavior. Both processes are critical, but their metrics highlight different aspects of their respective functions.
For detailed transaction screening metrics, you can continue to browse our material here.
And if you are interested in what transaction monitoring is all about, you can read our blog article on the subject or check out the features of our product.
How transaction screening works
There is no single transaction screening solution suitable for every financial institution.
Institutions might alter transaction screening algorithms based on several parameters. Based on their risk appetite, exposure to certain jurisdictions (which is especially important for effective international sanctions implementation), and internal compliance procedures. What constitutes an adequate transaction screening solution? It depends largely on who your customers are, the nature of your business and the expectations of the local regulator (which might differ from a strict “rule-based” approach towards a more flexible “risk-based” approach).
Certain areas of bank operations, such as international wire transfers and trade finance, are at a higher risk than others. Numerous software packages are commercially available, including those from AMLYZE, which can ease compliance with regulatory obligations. However, it is up to each financial institution to decide how to calibrate the software capabilities. And determine which transactions to screen and which datasets to use as well as what sensitivity level should be used for the screening the transactions (e.g. if it should be lower or higher than for customer screening).
Sounds too complicated? Let us give you a very simplified scheme and examples on how transaction screening works and how you may calibrate it.
Example of low-risk payment service provider’s transaction screening
Presume that Company A is a money service business and works with a stable, well-known customer base in a localized environment within the European Union. Company A provides exclusively SEPA payments. Company A has limited funds transfers and works only with well known local financial service providers. The local regulatory authority additionally recommends to follow up USA jurisdiction’s international sanctions (even if there is no clear USA nexus).
Company A has made the following decisions regarding transaction screening:
a) It has determined the scope of the transactions screening
Company A, which provides only SEPA payments, decided not to whitelist any transactions from its screening processes. Initially, the company considered excluding local payments from OFAC sanctions list screening. However, strict regulatory expectations and high compliance risk deemed this option unacceptable.
b) It has selected the datasets against which the transaction screening should be performed
International sanctions list
Company A selects EU, UN, and local international sanctions lists (imposed by the local jurisdiction’s competent authority) for transaction screening. Additionally, considering local regulatory recommendations, Company A includes the USA’s international sanctions lists (OFAC consolidated SDN and non-SDN lists) to meet regulatory expectations. The company also establishes separate procedures to follow if a match with a USA-sanctioned person is confirmed, taking into account the legal obligations and legal drawbacks of the extraterritorial applicability of international sanctions (e.g. blocking statutes).
Other lists provided by external dataset providers
Company A takes into account its customer portfolio and risk exposure and decides to use politically exposed persons, as well as adverse media and enforcement list screening, solely for client screening purposes and not for transaction screening purposes.
Internal watchlists (“black” or “grey” lists)
The Company A maintains an internal watchlist of high-risk names, which it monitors not only through its customer screening process but also includes in the transaction screening process.
c) It has determined relevant attributes in transactional data to be screened
Taking into account its risk exposure, Company A has chosen to monitor only the counterparty data and payment details of SEPA payments. The company has deliberately decided not to screen BIC data, considering the risk exposure of its existing client portfolio and the fact that transactions are conducted solely within a limited network of financial institutions (the latter approach is possible only if the regulatory/supervisory authority is allowing the risk based approach for sanctions implementation).
d) It has fine-tuned the “fuzzy logic” parameters*
Company A, considering its risk exposure and the fact that the counterparty has already been screened by the financial institution as their own client, decides to apply more liberal “fuzzy logic” parameters (closer to exact match) for transaction screening compared to those used for client screening. This decision is closely monitored and evaluated during regular enterprise-wide risk assessment exercises.
* The degree of fuzziness in fuzzy matching algorithms is a tunable parameter that allows the balance to be struck between the rigor of the match and the ability to find approximate matches in the data. By adjusting the various components of the algorithm, it can be fine-tuned to best suit a particular business model, product or risk appetite. For further details on the metrics please refer to our paper here.
Example of large financial institution’s transaction screening
Presume Company B is a credit institution that works with a large, fluctuating client base in an international environment. Company B is established within the EU and offers a wide array of banking products and services (SEPA, SEPA instant, SWIFT payments, card payments, correspondent banking accounts, securities accounts, trade based financing etc.). A high number of customer transfers are carried out, including international funds transfers as well as other types of international transactions are being performed. The regulatory authority allows the use of a risk-based approach regarding sanctions screening.
Company B has made the following decisions regarding transaction screening:
a) It has determined the scope of the transactions screening
Company B analyzes each business line to determine the appropriate screening option. For trade finance documents, Company B decides to use manual screening initially. Later, more advanced techniques, such as Optical Character Recognition (OCR), which scan documents and automatically transpose them into the system before screening, will be introduced.
Considering the different risk exposures of various business lines, Company B evaluates each one to decide on screening parameters. The company decides to whitelist certain low-risk clients, such as local governmental authorities collecting utility bills and tax payments, from transaction screening.
Company B opts not to screen SEPA instant payments for international sanctions (with exception for local international sanctions), taking into account the evolving regulatory requirements within the EU, which provide certain exemptions for these types of payments concerning sanctions screening.
Analysts take similar decisions into account when analyzing the risk exposures of each business line.
b) It has chosen datasets against which the transaction screening should be performed
International sanctions list
Company B decides to apply a risk-based approach in determining which sanctions lists to screen.
For SEPA instant payments and all other local payments, Company B chooses to screen solely the local international sanctions lists imposed by the local jurisdiction’s competent authority.
For cross-border SWIFT payments and other transactions that have a cross-border exposure (e.g. trade based financing), Company B assesses its nexus with different jurisdictions and the risk of exposure to extraterritorial sanctions. Such as secondary OFAC sanctions. As a result, Company B decides to use the USA’s international sanctions lists (OFAC consolidated SDN and non-SDN lists) and the UK international sanctions lists, considering its substantial funds transfers to and from the UK. The Company also establishes separate procedures for situations if a match with a USA or UK-sanctioned person is confirmed. It takes into account the legal obligations and challenges related to the extraterritorial applicability of international sanctions. Such as blocking statutes.
Other lists provided by external dataset providers
Company B takes into account its customer portfolio and risk exposure and decides to use politically exposed persons, as well as adverse media and enforcement list screening, solely for client screening purposes and not for transaction screening purposes.
Company B for different types of payments uses a list of certain key-words provided by the vendor to screen payment details. Key-word list consists of high-risk words indicating possible terrorism financing, fraud or possible exposure to sectoral sanctions risk (e.g. certain dual use goods key-words).
Internal watch lists (“black” or “grey” lists)
The Company B maintains an internal watch list of high-risk names, which it monitors not only through its customer screening process but also includes in the transaction screening process.
c) It has determined relevant attributes in transactional data to be screened
Company B evaluates the data attributes of each product and service it provides that must be screened. As an example, for trade based financing transactions, Company B decides to screen the following data of transaction:
– Vessels, including International Maritime Organisation (IMO) numbers (the Company closely follows OFAC information and collects additional information on vessels trading with Russia);
– Importer and exporter, manufacturer, drawee, drawer, notify party, signatories;
– Shipping companies, freight forwarders;
– Facilitators, such as insurance companies, agents and brokers or FIs, including Issuing / Advising / Confirming / Negotiating / Claiming / Collecting / Reimbursing / Guarantor Banks
d) It has determined the “fuzzy logic” parameters
Company B carefully considers parameterization of screening for each product it provides. For example, the Company decides to apply more conservative “fuzzy logic” parameters for cross-border transaction screening compared to those used for local transactions screening. For payment purpose (payment details) screening Company B decides to use more liberal (closer to exact match) “fuzzy logic” parameters to avoid the redundant false positive matches.
Once the decision has been taken to set up the transaction screening process and, after careful testing and additional consideration of changes to existing parameters, the transaction screening process has been enabled, regular quality control testing should be carried out. Purpose is to ensure that the system still meets the expectations and risk exposure of the firm. This is, of course, taking into account changing regulatory expectations.
Role of AML investigation in the parameterization of transaction screening
Effective AML investigation (case management) of alerts and subsequent actions is as crucial as the transaction screening parameterization. It is essential to establish clear procedures for responding to each type of alert. Because of the sensitive nature of transactions and the dual need for financial institutions to be both “user-friendly” and compliant with regulatory requirements. Here are a few key tips for setting up these procedures:
- Categorize alerts
Determine the status of the alert to assign it to the appropriate procedure (e.g., international sanctions, PEP, adverse media). - Validate alerts
Verify that the alert is not a false positive. You can do it by cross-checking the transaction data against the list that triggered the alert. - Gather additional information
If needed, request additional information from the counterparty financial institution or from the customer. - Take appropriate actions
Follow internal procedures to handle the transaction and client. Suspend the transaction, freeze the funds, reject the transaction, include the client into enhanced monitoring list, freeze or refuse further business relationship with the client, off-board the client etc. - Report to authorities
Inform the relevant authorities as necessary. Such as by filing suspicious transaction reports (STR) or reporting frozen funds related to sanctioned individuals.
Importantly, even if approved (e.g. by indicating that the hit is a “false positive” one), transactions are subject to ongoing monitoring alongside other transactions to ensure that approved payments aren’t part of a wider pattern of suspicious activity. This is where the transaction monitoring system comes in.
The synergy of screening and monitoring
Together, transaction screening and transaction monitoring form a comprehensive defense strategy against financial crime.
Transaction screening acts as the line of defense, preventing high-risk transactions from being processed. On the other hand, transaction monitoring provides ongoing review of transactions. It ensures that any suspicious activity that may have slipped through the initial screening is detected and addressed.
This dual approach supports a layered, risk-based AML/CFT due diligence strategy. It enhances institution’s ability to comply with regulatory requirements and protect against financial crime.
We strongly encourage our clients to implement both screening and monitoring solutions. Because these are mandatory requirements set by regulators in every country, not optional components of a risk-based approach. In this way, financial institutions can maintain a robust and adaptable compliance framework. The one that responds to evolving threats and regulatory landscapes.
To facilitate system integration and streamline internal procedures into a unified risk management component, we recommend using a single software solution for both screening and monitoring. The AMLYZE platform enables users to configure transaction monitoring rules alongside the screening service. This ensures that monitoring incorporates the results of screening, enabling a continuous review of customer behavior and risk exposure to financial crime.
Regulatory requirements
As mentioned above, the regulatory approach of each jurisdiction must be considered when selecting transaction screening parameters and evaluating the results (determining whether they are truly “positive” hits). Here are some tips, based on common standards set by organizations such as the Financial Action Task Force (FATF), that should be applicable wherever you are. By taking these factors into account, you can effectively parameterise your sanctions screening solution and set up procedures for handling alerts generated by the screening process. This will ensure compliance with international and national regulations while managing your company’s risk exposure.
International sanctions
International sanctions imposed by local governmental authorities typically follow the “territorial applicability” approach. This means they apply within the specific jurisdiction’s territory or to the jurisdiction’s citizens, regardless of their location.
When choosing the parameters for screening (specifically the choice of datasets and alert management functions), it is obvious that local sanctions should be applied. However, several factors should be considered:
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UN sanctions
UN sanctions are mandatory for all 193 UN Member States. Each member state must integrate these sanctions into their national legal systems by enacting domestic legislation and regulations to enable enforcement within their territory. The Financial Action Task Force (FATF) and its regional bodies closely monitor the implementation of UN sanctions at the jurisdictional level.
For EU countries, UN sanctions are transposed into EU regulations and are directly applicable to EU countries. In the case of emergency sanctions, the EU often acts quickly to implement the sanctions. This can happen within a few days to a few weeks after the adoption of the UN Security Council resolution. You could apply a similar approach outside the EU’s jurisdiction.
To mitigate the risk of missing certain UN sanctioned persons due to the time lag between the implementation of UN sanctions lists into national regulations, we recommend using the UN sanctions data set in addition to local (or EU) sanctions lists. If you are concerned about overlapping sanctions lists, contact your sanctions screening provider to understand how their suppression mechanisms work. This will help minimize the number of alerts and increase the efficiency of your screening process.
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Extraterritorial sanctions
Some countries impose international sanctions extraterritorially, extending their reach beyond national borders to affect entities and individuals worldwide. These sanctions force foreign individuals, companies and governments to comply with the laws of the sanctioning country, even if they have no direct ties to that country.
The United States is particularly well known for its use of extraterritorial sanctions, particularly through secondary sanctions. These target non-US entities that do business with US-sanctioned entities and threaten restrictions or penalties for non-compliance.
Therefore, evaluating jurisdictional nexus prior to setting up your international sanctions screening solution can be very important, especially when selecting international sanctions datasets for screening. This assessment should not be made blindly; the legal implications must be carefully considered, as extraterritoriality is not favored by the jurisdiction in which it is applied.
In determining the nature of the nexus with a country, factors such as cross-border transactions involving that country, the use of its currency in transactions, and the presence of branches or subsidiaries in its jurisdiction should be evaluated. Each of these nexus factors, along with the local regulatory requirements of the country where the nexus exists, may influence the approach to sanctions screening.
In determining what action to take, consider legal obligations and potential conflicts arising from the imposition of extraterritorial measures and local blocking statutes that prevent the application of such measures.
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Peculiarities of local regulation for transaction screening
Institutions should ensure that there are no legal obstacles to the application of transaction screening imposed by local regulators. In April 2024, the European Commission (EC) adopted amendments to the regulation on instant credit transfers in euro (also known as SEPA instant). Among other things, the regulation stipulates that transaction screening for EU international sanctions does not apply to SEPA instant payments.
There are several reasons for this requirement. On the one hand, there should be a consistent approach to sanctions implementation within the EU: the EU Regulation on International Sanctions requires consistent application of international sanctions within the EU and local supervisory mechanisms to ensure effective sanctions enforcement in all Member States. On the other hand, since customer screening is already carried out by each EU financial institution against EU sanctions lists, additional transaction screening for SEPA instant payments is considered redundant. Above all, the EC wants to accelerate the adoption of SEPA instant payments in the EU payments market by removing all unnecessary barriers. Although it may be debatable whether transaction screening is an “unnecessary obstacle,” the regulation is mandatory and must be applied within the EU.
However, it is important to note the scope of the Regulation. For example, the Regulation does not cover real-time AML/CFT transaction monitoring or transaction screening against local sanctions imposed by individual Member States. It also does not cover screening against internal lists, negative media lists, enforcement lists, PEP lists or sanctions lists of other countries.
Politically exposed persons
There are several factors to consider when setting up transaction screening for politically exposed persons (PEPs) or when dealing with PEP screening alerts. For a comprehensive analysis of PEP screening, please refer to our broader analysis here. In the context of transaction screening, here are some answers for the questions we receive.
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Is transaction screening against PEP lists mandatory for enhanced due diligence (EDD) purposes?
The short answer is no. It is typically not a regulatory requirement for EDD purposes to have transaction (not NOT client) screening against PEP lists.
AML/CFT experts could quote the requirement to perform EDD measures for PEPs even if they woke up in the middle of the night. Typically, automatic client screening is used to verify if a customer or an associate with a customer party is a PEP. Transaction screening for PEPs (screening payment counterparty data and payment details) is generally not a regulatory requirement. It is rather a conservative approach to managing risks associated with PEPs.
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Would you recommend transaction screening against PEP lists?
Our answer is typically neutral—it depends on how conservative your risk tolerance is.
However, at AMLYZE we find that even the most cautious financial institutions typically avoid bluntly screening transactions against PEP lists. The primary reason is the difficulty in eliminating false positives in counterparty transaction screening. When the counterparty is a client of another financial institution, an additional layer of communication with that financial service provider might be required. It may be need to verify certain data of the transaction counterparty (e.g., date of birth, customer identification data might be necessary to verify information). However, it is not guaranteed that the financial institution will provide the necessary information.
Unlike sanction screening, where a counterparty suspected of being a sanctioned individual necessitates freezing the transaction until the suspicion is cleared, suspicion that a counterparty is a PEP is not a legal ground to freeze a transaction. Additionally, the mere fact that a counterparty of a transaction is a PEP does not automatically require EDD or indicate possible criminal activity. Therefore counterparty financial institutions might not be willing to provide all the information on its client merely on the ground that he/she is suspected of being a PEP (note, there is no suspicion that he/she is involved in ML/TF activity). In these cases, data protection and banking secrecy laws might come into play.
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What could be an alternative?
As an alternative, a request for similar information can be sent to the customer. However, imagine asking customers to verify if the person they are sending funds to or receiving funds from is a true PEP match. This would hardly contribute to providing “user-friendly” services. And what justification would you provide for requesting such information? Therefore, verifying if a counterparty is a PEP is more appropriate during the internal investigation phase when transaction monitoring flags a suspicious transaction, rather than during each transaction screening. The combination of risk factors, such as a PEP and a monitoring alert, may provide a reasonable basis for conducting a deeper investigation. And for requesting additional information from both the client and the counterparty financial institution.
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What else should we pay attention to while setting up PEP transactions screening?
If you decided to have transactions screening against PEP lists, there are a few tips from us to you to consider:
- Consider the varying time limits for determining whether a person remains a PEP after leaving office. Regulations differ across countries in this regard. Some jurisdictions, such as Canada, take a conservative approach. It requires that a person designated as a foreign PEP remains a PEP indefinitely. In some cases, individuals may retain their PEP designation even after death. In the EU, regulations require treating individuals as PEPs for 12 months after they leave their position.
This might help you to eliminate a number of PEP alerts (well, if you are not located in Canada at least).
- Consider which transactional data you are willing to screen. Within AMLYZE, you have the option to choose to screen specific elements. Such as solely the payment purpose or solely the counterparty, rather than all transactional data.
- Consider the parameters of “fuzzy logic”. We suggest making them more liberal (closer to exact match) than those used for client screening.
Other screening objectives from regulatory perspective
Adverse media screening. Although no strict regulatory requirement mandates adverse media screening, market practice typically includes it as part of the EDD process. However, the EDD component is usually client screening for adverse media rather than transaction screening.
Enforcement lists. At AMLYZE, we refer to enforcement lists as those announced by various law enforcement authorities. Similar to adverse media screening, monitoring enforcement lists is not a strict regulatory requirement when providing financial services. However, monitoring enforcement lists can be a valuable transaction screening tool for identifying potential criminal activities. Such as providing certain services illegally. Let us explain with an example.
In the EU, gambling regulation is not unified; each country has its own set of rules and licensing regimes. Some governments, like Norway, have monopolized certain gambling activities, while others, such as Germany, use a “territorial district” approach. This complex regulatory landscape can make it challenging for financial institutions working in the EU and providing cross-border financial services to determine one important thing. Are they are dealing with customers involved in illegal gambling activities? There is a way to simplify the identification of companies providing gambling services illegally (without a license) within a jurisdiction. Competent authorities in some countries publish lists of companies involved in such activities. Screening transactions against these lists can help identify specific cases. Those where a financial institution’s customer might engage in illegal activities.
Transaction screening challenges
Organizations often face significant challenges in screening transactions. These are due to legacy systems, unreliable or poorly processed data sources, and overwhelmed teams.
A common problem are backlogs caused by false positives. When the system generates too many false positives, it clogs queues. And diverts valuable analyst time away from identifying true positives. This not only results in less accurate screening, but also leads to analyst burnout.
At AMLYZE, our data scientists have enriched the transaction screening algorithm to drastically minimize the false positive rate. According to standardized tests, the AMLYZE system has a false positive rate of 0.2% with an effectiveness rate of 97-99%, depending on name manipulation (more details about here).
Another common problem in the industry is unclear alert data. Analysts often encounter alerts that do not clearly explain what data triggered them. This lack of context makes it difficult for analysts to conduct proper investigations. It causes them to either spend too much time on low-risk activities or miss transactions that they should flag.
Slow screening times are another common problem. Delays of up to a day or more in processing individual alerts can have a negative impact on customer satisfaction. Especially with the advent of faster payments where customers expect faster processing.
To keep pace, organizations need solutions that avoid hindrances from inaccurate data or the inability to target risks. Even the most skilled analysts cannot effectively mitigate an organization’s AML risks without adequate screening tools.
Reasons to choose AMLYZE
At AMLYZE, we brought together regulatory insiders, AML/CFT experts and IT. And asked them to create an easy-to-connect, customizable and accurate transaction screening tool.
And the effort paid off. Here are 5 reasons why you should put them on your shortlist when choosing your payment screening provider.
1) Exceptional accuracy
Our false positive rate is less than 1% (just 0.2%!). It has been rigorously tested and proven by customer feedback.
2) Advanced algorithms
Our data scientists have developed three different algorithms using over 40 parameters to ensure accurate comparisons against different watchlists.
3) Extensive data sources
We use over 100 data sources from our partners to provide the most accurate and cross-referenced results.
4) Lightning-fast performance
99% of transactions AMLYZE processes faster than in 282 milliseconds per transaction, 72.5 milliseconds on average
5) Seamless integration
You can seamlessly integrate transaction screening results with real-time transaction monitoring. Automatically stop payments if counterparty details match potential sanctions, ensuring robust compliance and security.
In addition, the algorithm supports Latin-based, Russian, and Greek languages. And it can effectively translate and compare when needed. You can also select different lists with different levels of fuzziness for customers and payments.
Conclusions on the topic of transaction screening
Transaction screening presents challenges. But it is also a great tool for any financial institution to stay compliant with regulatory requirements .
A key best practice for transaction screening is to adopt a risk-based approach. This involves financial institutions assessing the risk level of each customer and transaction. And then tailoring their screening procedures to match the assessed risk.
Given the increasing volume and complexity of financial transactions, manual transaction screening has become impractical. Financial institutions should invest in advanced tools such as one offered by AMLYZE.
Only advanced technology can analyze huge amounts of data in real time and identify suspicious transactions for further investigation. This approach increases the efficiency of the screening process and minimizes the risk of human error.
Sanctions lists and other screening databases are constantly evolving. So financial institutions need to ensure they are using the latest versions. This requires regular monitoring and updating of screening lists to reflect any new additions or changes.
Effective transaction screening requires a well-trained and knowledgeable AML/CFT team. Institutions should therefore invest in ongoing training and education for their staff.
But even if you’ve done all of the above within your organization, don’t forget to conduct regular AML audits. They are essential to ensure the effectiveness of transaction screening processes. Best practice dictates that an independent third party should carry out these audits. And they should provide an unbiased assessment of the screening process.
