Data-driven compliance

Compliance: the data challenge

From sanctions screening to detecting fraud, compliance activities depend on fast access to high quality data. But in practice, payments data often includes incomplete, missing and/or unstructured data. This can hinder the effectiveness and efficiency of transaction screening and AML monitoring: 

Effectiveness. Poor quality data is a significant hindrance when it comes to screening transactions. If the required information is not accurate or present – such as a missing country name – illicit transactions may fail to issue an alert, leaving the bank at risk of non-compliance.  

Efficiency. From an operational efficiency point of view, poorly formatted messages may require manual intervention, which reduces the efficiency of the screening process. 

Likewise, where fraud is concerned, the ability to access data in a timely fashion is essential when preventing, stopping or recalling potentially fraudulent payments.

Data and KYC

Know Your Customer (KYC) due diligence can also present challenges where data is concerned. Sourcing and verifying the large volumes of data needed for KYC can be time consuming and unwieldy, as data typically has to be obtained from disparate sources and in multiple formats. 

Leveraging data and analytics

To optimise both the efficiency and effectiveness of compliance processes, banks need to leverage their data more effectively and take full advantage of sophisticated analytics – all while delivering a better client experience. In other words, they need to embrace data-driven compliance. 

Banks can do this in a number of ways: 

Optimise data quality 

As well as improving the effectiveness of screening and AML monitoring, better quality data also increases straight-through processing and reduces the need for repairs. And with higher quality data, institutions will be better able to benefit from advanced analytics.

Harness richer data 

The adoption of ISO 20022 messaging provides the opportunity to harness richer and more structured data. As well as minimising false positives during the screening process, banks can take advantage of more structured data in order to detect fraud with greater precision.   

Take advantage of analytics 

Sophisticated data analytics enable banks to monitor their correspondents’ behaviour and reduce their exposure to high-risk transactions. By harnessing the power of machine learning, analytics tools can learn individual customers’ payment patterns and identify suspicious payment instructions – thereby augmenting more traditional fraud prevention controls. 

Streamline KYC 

Where KYC is concerned, banks are looking to move from periodic reviews to an event-driven approach, with due diligence carried out in response to changes to customer behaviour, market conditions or the bank’s own business. By taking advantage of shared KYC utilities, banks can access up-to-date KYC information whenever they need it. 

The bottom line: by embracing data-driven compliance, banks can harness data and analytics more effectively. This enables them to reduce the risk of fraud and increase the accuracy and efficiency of their transaction screening – thereby minimising false positives, reducing compliance costs and mitigating the risk of non-compliance. 

Learn more about The KYC Registry

How to leverage payment data and analytics to mitigate compliance risk

Knowing who is sending and receiving money is vital in the fight against financial crime 

The international banking community is rallying in the fight against money laundering, terrorist financing and cyber fraud. And as cross-border payments move to real time, financial crime compliance will become even more challenging. 

At the same time, payment data volumes are increasing exponentially. These datasets lack standardisation, are often spread across multiple IT systems and subsidiaries, and are delivered in several formats. 

Having access to accurate insights into payment data remains a key compliance imperative to help avoid financial loss and reputational damage. 

Financial Institutions are realigning policy, data and systems to support new payments standards 

The Wolfsberg Group’s guidance on payments message standards has been important in the enhancement of international paymenttransparency. 

However, the full adoption will require Financial Institutions (FIs) to realign policy, data and systems to these new requirements and/or foster the development of enhanced market infrastructures. Legacy payments infrastructures may limit the amount of information that can be included in a payment due to the absence of sufficient field space. 

Full implementation of ISO 20022 standards would support addressing these limitations. 

Addressing these requirements is no easy task

There are a myriad of challenging factors, including systems complexity, legacy infrastructure, the lack of standards, and the possibility of losing data throughout the payments chain. 

The payments chain can span multiple counterparties and branches across the globe, which means that risk altogether is unclear. 

The following steps can help you better address these challenges and proactively seek new ways to mitigate risk. 

1. Get the big picture on payment activities 

Attaining a complete view of all message data for payments and trade-related messages across branches and correspondents is key to identifying and quantifying global risk within your institution’s transaction activities. 

Overlaying data from your in-house network with message data from the Swift network provides unique insights into payment flows without compromising data privacy and security. 

Get the big picture on payment activities 

2. Monitor for unusual behaviours 

FIs typically understand who they are receiving payments from, but struggle to identify the other banks that are sitting behind the transaction. 

The ability to monitor payments traffic across your network can mean that you can proactively spot potential pockets of risk and ensure that your risk policies are being followed throughout the network. 

These insights can be used for manual review as part of ongoing AML/CFT Anti-Money Laundering operational processes. 

3. Enhance payment data quality by identifying flaws and blind spots 

With the heightened regulatory focus on originator and beneficiary information, payments data quality needs to be constantly assessed. 

This will help you identify problem areas and take the right action where needed to ensure that your payments meet relevant data quality standards. 

Evidence from an independent source can enable you to discuss the subject with counterparties, when appropriate. 

4.    Accelerate decision making with the latest analytics 

Building a robust analytics programme from the ground up to deliver the insights that you need can be a costly and time consuming exercise. 

Consider the return on investment of building the tools and capabilities in-house versus the adoption of purpose-built analytics tools that you can configure according to your risk appetite and reporting requirements. 

5.   Take a community approach to addressing these challenges 

Compliance teams are continuously challenged by unexpected costs that impact departmental efficiency. As the regulatory landscape evolves, it is even more critical to leverage the right data and technologies to make the best risk-based decisions. 

Swift is working hand-in-hand with the entire community to expand its analytics portfolio to help you respond to these challenges. Our solutions deliver extensive insights into payment data quality and transaction flows across your network, so that you can monitor and address financial crime risk with pinpoint precision. 

Read more: Embrace shared solutions to meet the new reality of instant payments