No news isn’t always good news

Operating within the intricate web of EU regulations, Allianz Benelux must conform to strict rules when selling life policies to individuals, group insurance policies to companies, and granting mortgage loans. These include complying with the European anti-money laundering directives (AMLDs), which require insurance companies to report any suspicious activity related to money laundering or terrorist financing to the relevant authorities.

Effective adverse media screening is crucial in upholding these obligations. Before meeting with ComplyAdvantage, Allianz Benelux could only conduct minimal, manual media investigations. This made adverse media screening slow, potentially leaving the company vulnerable if a threat wasn’t detected quickly.

The company needed a robust solution that would enable it to quickly scour global media sources for adverse reports and designations involving clients or partners. Its objectives were to: 

• Fulfill enhanced due diligence (EDD) obligations.
• Proactively address compliance lapses.
• Minimize the impact and delay of its underwriting and management process.
• Pre-empt reputational damage that could impact client relationships and its brand.

After conducting a comprehensive process to find the right partner, Allianz Benelux met with ComplyAdvantage’s representatives in 2022. When Allianz Benelux tested ComplyAdvantage’s solution against its current approach, the team was impressed with the results.

We were looking for an efficient tool to perform adverse media checks. It had to be easy to use, with efficient support, and the price was also important.

Yves Declercq – AMLCO Compliance Officer, Allianz Benelux

Easier adverse media screening at Allianz Benelux’s fingertips

By implementing ComplyAdvantage’s natural language processing-powered adverse media screening solution, Allianz Benelux now benefits from an adverse media tool with instant, relevant alerts. The solution also provides the company with an accurate AML/CFT-focused taxonomy aligned to its regulatory requirements and structured profiles, including year of birth, known organizations, and other essential information. This has enabled Allianz Benelux to modernize its processes and optimize its workflows to improve efficiency and free up its compliance team’s time.

Clear, actionable insights on clients and partners, such as sanctions lists and regulatory non-compliance mentions, have streamlined file handler workflows, allowing more time for client onboarding and other essential tasks.

Once the contract with ComplyAdvantage was signed, it was only a matter of days before all users could use the tool. We found it to be easy, flexible, and fast.

Yves Declercq – AMLCO Compliance Officer, Allianz Benelux

Allianz Benelux and ComplyAdvantage: Partnership highlights

Fortifying Allianz Benelux and its customers for the future

Since successfully integrating the adverse media solution, Allianz Benelux’s customer success manager has arranged regular meetings to ensure the solution operates smoothly. They are also working on keeping the firm’s KYC procedures up-to-date as its needs evolve. 

ComplyAdvantage’s adaptability and prompt responsiveness have empowered Allianz Benelux analysts to quickly learn how to use the solution, enabling the company to maintain effective adverse media screening despite inevitable staffing changes.

All technical issues are solved in hours, not days. We have never seen such fast and professional support for an IT tool. In-house, we consider the support we receive from ComplyAdvantage to be the best we have ever received.

Yves Declercq – AMLCO Compliance Officer, Allianz Benelux

In a world where criminals are becoming increasingly sophisticated, the partnership will continue to grow, fortifying Allianz Benelux and its customer base with AI-supported solutions.

If you’re looking for an adverse media solution, it would be a mistake not to explore ComplyAdvantage’s proposed solution.

Yves Declercq – AMLCO Compliance Officer, Allianz Benelux

The post Allianz Benelux improves adverse media screening efficiency with AI  appeared first on ComplyAdvantage.

• Adverse media screening software to reduce your reliance on manual processes when onboarding and monitoring customers.
• A way to quickly compare the top available solutions.
• How respected third parties assess top adverse media and AML vendors’ capabilities.

This article summarizes seven adverse media screening software vendors, listing their key strengths and features.

Adverse media screening software: 4 features to look for

When evaluating adverse media screening vendors, there are several features compliance teams should look for:

1. An entity-level view of information. Implemented at scale without the right strategy, adverse media can create a lot of noise for compliance analysts. Firms should ensure the solution they choose has an entity-level view of key risks, grouping articles rather than simply displaying large volumes of news like a search engine. 
2. Predicate crime-aligned taxonomies. Similarly, does the solution tag adverse media information to be viewed in a way that will resonate with regulators? This should include categories aligned with the Financial Action Task Force (FATF), such as narcotics and cybercrime, alongside those related to key regulatory regimes. For example, the 22 predicate offenses listed in the European Union’s 6AMLD include fraud, environmental crime, smuggling, and corruption. 
3. Dyanmic risk ratings. Properly deployed, adverse media screening should operate as a core, integrated part of the wider anti-money laundering (AML) function. As a result, when customer risk profiles and ratings are adjusted, this should be reflected in the screening process. This may dictate, for example, how frequently an individual is screened, the level of fuzziness, and/or which topics are covered.
4. Operational efficiency. A ComplyAdvantage survey of 600 financial crime decision-makers showed employee morale related to adverse media screening is a key challenge. When asked about the primary benefit they’d seek in a new solution, 53 percent said, “increasing employee morale by removing repetitive, no-value alert remediation tasks.” From automating ongoing monitoring to curated insights, firms should ensure they comprehensively assess where adverse media screening is currently proving time-consuming and how a new solution can solve those problems.

Top adverse media screening software companies

1. ComplyAdvantage

The G2 GridⓇ for Anti-Money Laundering is a helpful way of measuring financial crime risk management vendors based on customer reviews. The G2 GridⓇ lists ComplyAdvantage as a leader in anti-money laundering.

Adverse Media Screening from ComplyAdvantage is a natural language processing (NLP)-based solution to help firms analyze AML/CFT risk through negative news at scale. It fulfills all recommendations from The Wolfsberg Group for negative news screening solutions and enables continuous monitoring, dramatically reducing backlog.

It’s based on four central capabilities:

• Structured screening: Instead of screening against an infinite stream of articles, it screens against structured, continuously updated entity and individual profiles. 
• Curated source lists: Financial crime experts collate specific source lists based on the reality of how criminals operate. 
• Contextual machine learning: The solution filters out non-adverse media hits with machine learning that’s trained on the specific context of adverse media. 
• FATF Taxonomy: It leverages an AML/CFT taxonomy that’s aligned with the regulations and guidance laid out by the FATF. 

Top ComplyAdvantage features:

Adverse Media Screening from ComplyAdvantage is ideally suited to a range of organizations, including banks, insurance companies, and payment providers, who need to shorten customer wait times, improve analyst productivity, and proactively manage compliance. 

The solution’s most important features include:

• Live profiles – Use live, structured profiles of rich, dynamic information from millions of data points to reduce onboarding times by as much as 80 percent. 
• Streamlined workflows – Focus on the alerts that matter most with automation for labor-intensive processes and custom risk profiles that are quick and easy to create.
• Automated KYC updates – Meet even advanced due diligence requirements with automated updates to continuously know your customer (KYC) without manual rescreening. 
• Tailored alerts – Customize your program based on the most relevant risks to your business and select source lists based on recommendations from the FATF and EU money laundering directives (MLDs).
• Hassle-free API integration – Integrate the feeds, systems of record, and applications you rely on into a single search function.
• Natural language processing (NLP) – Use a contextual approach to filter out non-adverse media hits. 

ComplyAdvantage’s Adverse Media Screening customers include Allianz, Currencycloud, Holvi, raisin, and Luno.

Transform your adverse media screening program with ComplyAdvantage

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2. Quantifind

As per Crunchbase, Quantifind provides “AI solutions for anti-money laundering and fraud detection.” Its investors include DNS Capital, Citi Ventures, US Venture Partners, and S&P Global. The firm is based in Palo Alto, with teams in various US cities, alongside Madrid and London.

3. Quantexa

Launched in 2016, Crunchbase describes Quantexa as a “decision intelligence platform for the banking, insurance, and government sectors.” Its investors include ABN AMRO Ventures, Dawn Capital, and Evolution Equity Partners.

4. Dow Jones Risk and Compliance

According to G2, Dow Jones Risk and Compliance is “a global provider of third-party risk management and regulatory compliance solutions.” The firm has operated since 1882, evolving from a news agency to offer a wider range of services.

5. Moody’s Analytics

Crunchbase describes Moody’s Analytics as providing “financial intelligence and analytical tools.” The firm was founded in 2008 and has expanded its field of operations since then, including through a number of acquisitions.

6. LexisNexis Risk Solutions

According to Crunchbase, LexisNexis Risk Solutions “provides information to assist customers in industry and government in assessing, predicting, and managing risk.” Headquartered in Atlanta, Georgia, the firm has offices in 24 countries worldwide.

7. LSEG Data & Analytics (Previously Refinitiv)

According to Crunchbase, the London Stock Exchange Group (LSEG) is a “provider of financial markets data and infrastructure.” LSEG acquired Refinitiv in 2021, expanding its service offering.

How to measure success

While every firm will have different objectives and challenges with their adverse media screening software, success metrics should include:

• Protect the firm and its customers’ reputation. Adverse media can be an effective risk prevention tool, particularly for typologies like environmental crime, which are a growing focus for regulators.
• Faster decisions based on adverse media profiles, thanks to information being collated effectively.
• Greater depth of risk knowledge based on access to specialized blogs and newspapers alongside national, high-profile outlets.
• Adverse media screening that is fully aligned and integrated with wider AML processes, not operating as a standalone ‘nice to have.’

Next steps: Explore Adverse Media Screening from ComplyAdvantage

Discover why leading firms choose ComplyAdvantage for Adverse Media Screening, and book a demo to see the solution for yourself. 

All information is sourced from publicly available websites and is correct as of March 2024. If you’d like to request a correction, please e-mail content@complyadvantage.com and we’d be happy to review this with you.

The post The best adverse media screening software and companies in 2024 appeared first on ComplyAdvantage.

Before working with ComplyAdvantage, BigPay had a manual, ad hoc screening process. It needed to implement a more efficient one – fast – to meet its regulatory obligations. The reliance on manual processes also meant the firm faced the challenge of cumbersome batch processing during its annual customer rescreening, something that became increasingly difficult as the firm – and its customer base – grew.

BigPay also needed a solution that could be tailored in line with its risk-based approach:

“We had issues with customizability, as most platforms offer a standardized list of searches. We planned to have full control over the range of lists we used depending on the use case, transaction type, and country.”

Ashwin Nazareth, FinCrime Operations & Disputes Principal, BigPay

Integrated, customized screening and monitoring

The firm needed a flexible, unified platform that could scale across multiple markets and handle volume spikes during periods of peak demand. But with its previous solutions, streamlining these complex processes wasn’t possible – it involved too many touchpoints and manual processes. What’s more, BigPay needed a solution to automate workflow processes for name screening and adverse media searches, freeing up analyst time for more in-depth investigations.

That’s where ComplyAdvantage’s customer screening and transaction monitoring came in. BigPay was able to custom-build a single proprietary interface connecting multiple tools, trackers, and databases via a single API. The financial services firm also set up unique screening profiles for its individual markets, providing proportional controls for different products and transaction types – such as remittance and e-money. Accessible search profile configuration and fuzziness fine-tuning streamlined the process of aligning with new regulations.

“We now have the benefit of researching sanctions, PEPs, and adverse media all at the same time from a large number of sources rather than using multiple tools and databases. The time saved comes from only having to research the alerts, rather than wasting time looking for them.”

Ashwin Nazareth, FinCrime Operations & Disputes Principal, BigPay

Collaborative risk management

Throughout the process, BigPay has been able to partner with its customer success manager at ComplyAdvantage, who applies industry-wide best practices to ensure the solution is performing well and saving time in key areas.

“Customer support has been fantastic, especially with a dedicated account manager who resolves our issues promptly and keeps us up to date on our account performance,” said Nazareth. This included advice on “where we should be focusing our innovation and technological enhancements. In fact, two of our major time-saving innovations came directly from recommendations during the account review cycles.”

In the next few years, BigPay wants to sharpen its focus on key typologies affecting virtual financial services, such as fictitious identities, mule accounts, and scams. Nazareth also noted the increasing importance of collaborative data in financial crime risk management, both within the financial services industry and between financial firms, law enforcement, and regulators. Trends like these will only increase the need for the kind of high-quality, holistic data ComplyAdvantage provides.

“There’s no other solution currently on the market quite like ComplyAdvantage,” commented Nazareth. “And what it can do, it does exceptionally well.”

The post BigPay improves analyst efficiency with integrated customer screening & transaction monitoring appeared first on ComplyAdvantage.

In a webinar with industry experts from the Financial Action Task Force (FATF) and leading research and advisory firm Celent, discussions centered on how technology can be used to close gaps in the negative news screening process. Based on their conversations, this article explores how financial institutions (FIs) can mitigate common challenges and reduce risk in adverse media with machine learning (ML).

Common adverse media challenges

Sifting through the noise to locate relevant data

When dealing with negative news screening, the main challenge analysts face is having to sift through vast amounts of data to identify relevant information. One major issue is the prevalence of irrelevant or noisy data. For example, searching for “Tiffany Palmer” on Google will generate over 70,000 results, even when using specific keywords like fraud or money laundering. This means it can be difficult to find the relevant information. For people with common names, such as John or James Smith, the number of search results can balloon to around 30 million, making it a daunting task to find the right information.

When analysts are unable to narrow down their search, difficulties can arise. They may have some information about their customer, such as their date of birth or location, but using tools like Google to refine their search is not always practical. Many try to read through all the available pages, but it’s not an effective or time-efficient solution. It remains hard to distinguish between relevant and irrelevant information, and it can be challenging to determine if two people with the same name are the same person. 

Accessing up-to-date information

Another challenge relates to keeping track of a customer’s risk information over time. It’s not practical to research millions of results for every update. To tackle this issue, some companies hire multiple analysts to read articles and use basic rules to filter out irrelevant data. However, this approach is limited since it either restricts the amount of information each analyst reviews or requires more analysts to cover the vast amount of data.

Some may choose to ignore the problem, while others only focus on performing adverse media checks on a small group of high-risk customers. Unfortunately, this may not effectively address possible risks since those involved in financial crimes may not be easily identifiable as high-risk customers.

Confirming the information is reliable

With information coming from various sources, including fake news, satirical content, and extremist websites, assessing the quality and credibility of the data becomes difficult. Thorough diligence on each source becomes necessary, adding complexity to the process.

Relying solely on well-known sources, such as national-level newspapers, is not advised, as this approach may miss individuals and risks not considered nationally important. The emphasis is on identifying risks before they become widely known, highlighting the need for a comprehensive and efficient solution to address the challenges of adverse media screening.

How machine learning can help

ML offers automation, providing the capability to continuously monitor vast amounts of media without being restricted to a specific set. This ensures FIs are aware of potential risks that may impact them. Additional features of ML that can help mitigate the common challenges listed above include:

• Consistency and accuracy: ML can significantly reduce human errors arising from repetitive tasks by delivering consistent and highly accurate in analysis. The model makes decisions consistently and improves over time, continuously learning from the increasing data it processes. 
• Multilingual screening: ML’s ability to cover multiple languages and scripts surpasses the limitations of human linguistics. Monitoring various languages allows for broader coverage of media sources. Events or information that may only be available in languages other than English can be captured, preventing crucial details from being overlooked.
• Data gathering and categorization: ML also aids in automating the process of identifying new information and distinguishing it from previously encountered data. This automation ensures organizations stay up-to-date on the risk associated with their existing customers while avoiding overwhelm by excessive alerts about redundant information.
• Swift screening: This ensures a better customer experience during the onboarding journey. Furthermore, it instills confidence by providing up-to-date customer information. Unlike traditional periodic reviews, ML enables continuous monitoring, guaranteeing the latest data on customers’ risk profiles.

Factors driving development in machine learning today

Accessibility

Firstly, the ability to access advanced infrastructure has significantly improved, allowing smaller organizations to access previously limited resources to larger entities. Cloud service providers offer readily available and cost-effective hardware for tasks like data retrieval and processing, leveling the playing field for various companies.

Advanced hardware and infrastructure

Secondly, remarkable advancements in machine learning, particularly in hardware and infrastructure, have played a crucial role in driving developments in ML. Silicon chips designed for ML tasks have become more powerful and accessible. This has allowed organizations to harness ML models’ potential without investing heavily in expensive servers and technology. Furthermore, the availability of cloud services allows them to operate efficiently in their chosen regions, accommodating diverse data requirements and regulatory constraints.

Natural language processing

Moreover, the progress in ML techniques, exemplified by advancements in natural language processing, has revolutionized the field. What was once considered impractical is now a reality, with ML becoming a potent tool in combating financial crime and identifying adverse events with remarkable accuracy.

Relevancy

The influx of real-world data has fueled the growth of ML, making it more relevant and applicable to solving significant problems. The industry now boasts around a million people dedicated to hand-labeling and annotating ML training data, making this valuable resource accessible through various mechanisms.

The Role of Tech and Talent in Adverse Media

Uncover the motivations behind investing in more advanced screening solutions in tandem with how and where to leverage talent best.

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Adverse media screening approaches

Despite the well-known challenges of adverse media screening and the awareness of these technological advancements, the widespread effective, integrated adoption of these solutions remains limited. Various factors may be influencing this hesitation among different organizations, despite the potential benefits these technologies offer.

As a result, attempts have been made to address the negative news problem through different approaches. 

The human analyst approach

As mentioned previously, the first approach involves employing human analysts to review news and manually create searchable profiles. However, this method has limitations, as it is constrained by the number of analysts hired, which restricts the scope of media coverage. Additionally, challenges such as language disparities and lack of consistency persist.

The keyword-based approach

The second approach adopted by FIs is a keyword-based method. While more scalable and automated, it has drawbacks, including a higher likelihood of false positives. Using keywords like “shoot,” “killed,” or “terrorize” can yield results with varying contexts, making it difficult for financial services firms or compliance departments to obtain relevant information. Conversely, this approach may also fail to capture critical information in an article when specific keywords are absent.

The machine learning approach

Considering the limitations of these two approaches, why do some organizations remain hesitant to adopt an ML-based approach to adverse media screening? 

• Skill gaps: The first challenge lies in the intersection of compliance expertise and machine learning skills, both of which are specialized. Combining these skills and approaching the problem from both perspectives is crucial, but forming such a team takes time and effort.
• Competitive hiring market: Recruiting ML experts is a tough challenge as these skills are in high demand, especially when competing with larger technology companies for the same talent.
• Data management: Acquiring the right data is vital for training machine learning models. While various data sets exist, solving specific problems demands millions of training examples. Building and managing this data, along with quality control, trial and error, and the associated expenses, are unavoidable challenges.
• Training: Shifting from traditional, explainable rule-based systems to more accurate ML approaches can be difficult for some firms. The new approach offers higher accuracy, but understanding individual decisions may be challenging initially. Educating and demonstrating the benefits can help overcome this hurdle and gain analysts’ comfort with the new approach.

Adverse Media by ComplyAdvantage

ComplyAdvantage has developed an innovative approach for its adverse media screening process. The API-led system comprises two main components. Firstly, there is a search bar where customers can input a person’s name and relevant identifying information, such as country or date of birth. The system then processes this data to identify potential risk profiles that match the customer’s search criteria, aiding the onboarding process.

The second part of the process involves gathering information from various sources on the internet. ComplyAdvantage utilizes ML technology to analyze and categorize this unstructured data, creating profiles for unique individuals and organizations that can be later searched for in the adverse media screening process. 

ComplyAdvantage ensures that the database is constantly updated in real-time, providing up-to-date information for searches and ongoing monitoring of existing customers. The ML algorithms read through the media information, identify relevant individuals and organizations, classify adverse media categories, and consolidate this data into comprehensive profiles.

This ML-based approach offers several advantages from a compliance perspective:

• Enhanced decision-making: The consolidated profiles make decision-making more efficient by presenting relevant information in a user-friendly format. 
• Fewer false positives: Having detailed profile information, such as birth year, associated countries, and specific adverse media categories, empowers organizations to filter out false positives and focus on high-risk cases. 
• Increased efficiency: By automating mundane tasks and providing accurate results, the machine learning-based approach frees compliance teams to focus on more critical and creative work, enhancing the organization’s ability to identify genuine risks effectively.

Why invest now?

Given the benefits of ML, the question arises: Why is now the right time to leverage this technology to solve adverse media challenges? 

Two key factors contribute to the urgency. 

1. Firstly, the challenges surrounding adverse media screening are growing increasingly complex, with an exponential increase in media volume and its rapid, ever-changing nature. Various publications and sources continuously release articles that undergo real-time editing, necessitating efficient information processing.
2. Secondly, the stakes have risen significantly as regulators demand that financial services companies maintain stringent monitoring practices. 

The convergence of these factors emphasizes the magnitude of the problem at hand. Nevertheless, technological advancements have provided the means to tackle these challenges effectively.

The post Reducing risk in adverse media with machine learning appeared first on ComplyAdvantage.

“Digital banks want to help their customers have a seamless and fast banking experience,” explains Valentina Butera, Head of AML and AFC Operations. “But the challenge is these things benefit customers and criminals alike. Technology is developing fast, but criminals are developing their ways fast too.” 

For every fraudulent customer it onboards, Holvi experiences high rates of payment recall, police requests, and seizures. The digital bank looked to AI-driven solutions to improve its efficiency and accuracy in detecting high-risk customers without disrupting legitimate customers. 

Holvi uses ComplyAdvantage to onboard and screen its customers against adverse media, sanctions, and politically exposed persons (PEP) lists. It also uses ComplyAdvantage’s transaction screening, monitoring, and fraud detection products. Holvi also recently deployed Smart Alerts to optimize the efficiency of its transaction monitoring using AI. “We needed a dynamic way of fighting financial crime,” says Butera.

Fighting fast-changing fraud typologies

Butera’s team chose ComplyAdvantage’s Fraud Detection solution for its AI-based capabilities. “It was an easy decision for us, we immediately saw it had the latest technology, and the AI capabilities were something we were really interested in trying,” she explains. “We also knew the implementation would be extremely smooth.” 

AI-driven alert optimization

Holvi also recently deployed Smart Alerts, an AI-driven tool that helps analysts prioritize the transaction monitoring alerts that pose the greatest risk to the organization. “It is the latest AML technology,” Butera says. The digital bank sought a holistic approach, finding that static rules often used by legacy financial institutions were ineffective at keeping pace with criminals. 

“The implementation of Smart Alerts was the smoothest implementation of tech that we have ever experienced. We did not experience any downtime or any interruption of business operations – not even for a second,” says Butera. 

Butera’s team quickly saw efficiency benefits as a result. Forty percent of Holvi’s high-priority alerts are true positives, compared to less than one percent of low-priority alerts. This automation has made Butera’s day-to-day work more productive. “As a Head of AML Operations, I know what alerts to prioritize and what my team needs to focus on.”

A deepening partnership

Through its deployment of ComplyAdvantage’s suite of products across onboarding and monitoring, Holvi is able to onboard customers speedily without compromising on its compliance obligations. “We know we can serve our legitimate customers while at the same time keeping a solid risk-based approach.”

Holvi has partnered with ComplyAdvantage for several years. “We believe our partnership with ComplyAdvantage will definitely continue to grow. We have grown together, and this is very nice to have in a partnership. Our needs have always been met, even though they are ever-changing,” says Butera. 

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Although no universally agreed definition or approach to adverse media screening exists, it is widely taken to mean searching media sources to find any possible negative news about the individual or business entity being onboarded (or refreshed in the case of existing customers) that might pose a risk to financial institutions in terms of money laundering or terrorist financing.

There are a number of difficulties that quickly begin to emerge at a practical level. What risks are relevant? How do I find relevant risk information? How do I decide if the information found is significant? How much time and effort should I put into finding adverse media? What should I do if the information found is inconclusive?

Unlike sanctions or even politically exposed person (PEP) screening which are binary – the entity is either sanctioned or not and an individual is either a PEP or not – adverse media screening covers a varied range of potential risks related to predicated criminal offenses that result in the proceeds of criminal activity. This can range from all forms of trafficking, fraud, cybercrime, and terrorist financing to intellectual property theft. The closest guidance to defining what risks these are was provided by the Financial Action Task Force (FATF) which lists over 20 specific crimes that lead to money laundering.  The extent to which these categories of crime are reflected in the regulations and legislation of individual countries varies considerably, but there is increasing convergence in adopting this range of offenses in major financial jurisdictions such as the EU, USA, UK, and Singapore. 

Recognizing the need for standardization in the way banks approach adverse media screening in their due diligence operations, the Wolfsberg Group recently published an FAQ Guide in their series on negative news screening.

Yet a huge challenge remains for any regulated entity: How to synthesize the vast amounts of data available in the public domain from the array of data points across the entire internet including deep web, surface web, websites, blogs, and social media as well as broadcast and print media. How do firms find the proverbial ‘needle in the haystack’ – the actionable risk intelligence on an individual or business customer that could be indicative of a crime?

Quite apart from the time taken, the cost of acquiring, processing, and acting upon any information found, and then ensuring that information found can be trusted, compliance analysts need exceptional skills to interpret often conflicting information.

How can this problem be overcome? Traditionally, banks have relied on a combination of sources including structured and unstructured data sets which are curated by specialist firms but are costly. Google searches are still heavily relied on by many firms despite the obvious shortcomings of using search engines for financial crime compliance. They are low-cost but ineffective. 

New solutions are essential. For example, regulators in the United States have added sharper teeth to FATF guidelines by enforcing the customer due diligence (CDD) rule requiring covered financial institutions to maintain “appropriate risk-based procedures” to continuously monitor and update customer information.

Technology in adverse media solutions is leading a revolution in this area by enabling firms to acquire meaningful and relevant risk intelligence quickly and efficiently and without the mountains of media findings found by traditional methods needing to be read and interpreted by analysts. A combination of machine learning and natural language processing technology can be trained to find media articles of relevance including in local languages in the selected areas of predicated offenses that relate to money laundering and terrorist financing risks. 

This revolution in adverse media screening is delivering actionable intelligence, empowering organizations to manage higher levels of risk, and for compliance teams to spend their time analyzing, interpreting, and understanding real risk rather than reading endless articles.

In today’s complex environment, financial regulators are on high alert for money laundering risks. Financial institutions should look for better solutions to conduct adverse media screening and avoid manually carrying out screening with a simple one-time Google search. An adapted adverse media screening solution can successfully automate the timing of screening based on a financial institution’s designated parameters, access and validate a larger number of credible sources, scan a massive trove of information, and reduce the number of false positives potentially clogging up the investigation and escalation phase process.

Celent report: Maximizing the Value of Adverse Media Monitoring

For this report, leading research and advisory firm Celent interviewed global banks from across the world, providing practical tips on how adverse media can be integrated into an existing AML value chain.

Download now

To explore more about the practical benefits of adverse media for compliance teams, explore the pieces below:

• Delivering a risk-based approach with adverse media
• How can adverse media reduce reputational risk?
• The importance of adverse media for enterprise-wide risk assessments
• The business case for adverse media in banking

The post How to make adverse media searches actionable and useful for banking appeared first on ComplyAdvantage.

In other words, conducting an EWRA helps compliance teams define an anti-money laundering (AML) risk rating methodology/model for all obligated entities to comply with AML regulations. If done correctly, it brings a consistent approach and, importantly, the application of risk mitigation processes based on sound principles to every division or domain of the organization. 

Put simply, criminals test the weak spots in a bank’s AML defenses and look to exploit them. An EWRA is a tool to ensure that ‘gaps’ don’t exist. 

At the heart of the EWRA is the risk-based approach which involves a three-step process: 

1. Assess the risks
2. Understand them in detail
3. Put in place appropriate risk mitigation measures and plug gaps in defenses

Higher risks need to be mitigated with adverse media data designed to provide in-depth and specific information on any risk category pertinent to money laundering and terrorist financing. Historically, financial institutions have often overlooked adverse media as an essential risk indicator in combating financial crime, considered a low priority in customer due diligence (CDD) associated mainly with reputation risk. Even if its use is recognized, solutions often rely solely on search engines and are inadequate. In practice, adverse media screening is more significant than estimated, should form an integral part of risk profiling, and is intrinsic to any risk management framework.

One of the main weapons in the fight against financial crime is using adverse media to monitor financial crime risk. Regulators everywhere are beginning to realize its importance as they advocate implementing a risk-based approach by regulated entities. Adverse media can inform an enterprise-wide risk assessment of new and existing customers, providing risk intelligence that goes beyond PEPs and sanctions screening. Used correctly, it can provide a vital defense for banks, protecting them from ‘bad actors’ looking to launder the proceeds of crime.

However, until now, adverse media screening has been a costly and time-consuming process relying heavily upon manual checks of large quantities of articles obtained from unstructured media data sources or from search engines such as Google. As such, banks have only used adverse media screening in a small percentage of high-risk customer situations. Many still solely rely on search engines. Unfortunately, this can easily result in important information being missed. 

As banks and financial institutions grow in size and complexity, consistency and scale become key issues, and a bank needs to take a more strategic approach to adverse media screening. 

Monitoring customer risk and ensuring compliance processes are implemented consistently across the business becomes more complex, especially if the organization is multi-jurisdictional or multi-divisional.  Added to this pressure is the rise of digital financial services often pioneered by FinTechs, which has fuelled customers who increasingly demand a seamless, swift onboarding experience. 

AML controls can get left behind. Often put in place when the business was at a different or early stage of its development, IT systems become outdated, and there is a considerable reliance on manual processes. 

Fortunately, AI-driven adverse media tools are available to help. It is now possible to implement adverse media screening across all customers both at the onboarding stage and in the ongoing monitoring of existing customers. This is important in a dynamic and ever-changing risk landscape where the traditional approach of carrying out periodic KYC checks on a customer at a frequency based on the initially assigned risk category may mean risks remain hidden, in some cases, for several years.

AI-driven adverse media screening solutions are designed to support dynamic customer risk scores. This allows a bank to precisely define the categories of risk it wishes to see for a particular customer, only generating alerts when a risk profile changes significantly. 

As banks continue to grow, they need to ensure that adverse media checks can scale with their customer bases. In particular, they need to ensure their alerts avoid generating high numbers of false positives that have to be cleared manually and risk slowing down customer onboarding.

Effectiveness will remain a hot topic in banking AML compliance – but this has to be achieved cost-effectively. When operating at scale, effectiveness, efficiency, and onboarding times become critical success factors and will directly impact a bank’s competitiveness in the years to come.

Conducting an AML-focused enterprise-wide risk assessment is one of the cornerstones in fighting money laundering. Adverse media screening helps teams make more informed decisions toward risks and identify higher-risk situations where a bank’s response can be quicker because real-time screening takes place.

Celent report: Maximizing the Value of Adverse Media Monitoring

For this report, leading research and advisory firm Celent interviewed global banks from across the world, providing practical tips on how adverse media can be integrated into an existing AML value chain.

Download now

To explore more about the practical benefits of adverse media for compliance teams, explore the pieces below:

• How to make adverse media searches actionable and useful for banking
• Delivering a risk-based approach with adverse media
• How can adverse media reduce reputational risk?
• The business case for adverse media in banking

The post The importance of adverse media for enterprise-wide risk assessments appeared first on ComplyAdvantage.

The benefits of adverse media screening

Adverse media or negative news screening is searching for information relevant to a customer’s AML/CTF risk profile. It is one of the best ways of building an accurate and precise profile of the counterparty risk for a bank while anticipating potential future threats. Configuring a system that supports both a bank’s business goals and compliance obligations while synchronizing with existing internal tools also improves overall operational efficiency. 

A bank cannot manually check thousands of news stories every day in multiple languages. Compliance and AML professionals are painfully aware that manual checks can be time-consuming, costly, and ultimately frustrating. Using traditional unstructured adverse media databases and search engines means reading, digesting, and interpreting dozens of articles or more. Many will be duplicates or irrelevant and often unrelated to the subject. Ultimately, this leads to decisions being taken without the best available information. 

Regulations 

Regulatory bodies have emphasized the need to construct accurate risk profiles for banking clients despite differing AML regulations. They have made screening for negative media an essential legal requirement for know your customer (KYC) onboarding protocols, continued customer due diligence (CDD), and enhanced due diligence (EDD) on potentially high-risk customers. 

In the United States, the Financial Crimes Enforcement Network (FinCEN) requires financial institutions to comply with the Bank Secrecy Act (BSA). Adverse media screening is also instrumental in supporting SAR filing.

The EU’s 6th Anti Money Laundering Directive (6AMLD) mandates banks to perform enhanced due diligence for high-risk customers. At the same time, Financial Action Task Force (FATF) guidelines recommend using adverse media searches as part of an enhanced due diligence process. 

The pressure is on banks and all AML-regulated financial institutions to find more efficient and cost-effective ways to fulfill their regulatory obligations while alleviating pressure on budgets and maintaining customer satisfaction.

A risk-based approach

The FATF emphasizes the risk-based approach for mitigating money laundering risks, and under its guidelines, adverse media screening is an important way to help develop accurate customer risk profiles. Politically Exposed Persons (PEPs) and other higher-risk relations are better monitored and receive an extra layer of scrutiny. 

Adverse media and AI 

As a result, many firms are turning to innovative solutions to automate processes and reduce the manual and ineffective processes that still characterize many AML control frameworks in US banks and financial institutions. 

Last year, the FATF published a significant report in this area called ‘Opportunities and Challenges of New Technologies for AML/CFT,’ setting out the case for investing in new technology to improve the speed, quality, and efficiency of measures to combat money laundering and terrorist financing. It states that these technologies can help financial institutions and supervisors assess the risks they face more accurately and quickly. When implemented using a risk-based approach, new technologies can also improve financial inclusion, bringing more people into the regulated financial system and thereby reinforcing the effectiveness of AML/CFT measures. 

The business case and evidence for investing in new technology solutions have never been stronger, with new AI-based adverse media screening and ongoing monitoring solutions changing the onboarding landscape with real-time and dynamic customer profiling.

The new generation of adverse media screening solutions aims to provide a 360-degree view of customers across both individuals and legal entities. This creates a more rounded and informed view of potential risk during the assessment process with a more accurate risk score at the beginning of the customer relationship. It also ensures that ongoing monitoring is more focused on potentially riskier relationships, providing alerts in real-time should a risk profile change significantly.

Adverse media as an investment

Building a business case to support investment in AML systems has never been easy. Boards of directors tend to view AML compliance as a cost to the business as opposed to investing in anti-fraud solutions that can be more easily tied to the bottom line. However, there has been a marked increase in interest from boards and executives following several high-profile breaches, resulting in huge fines and considerable management time spent dealing with the fallout. Boards now accept that adverse media screening is essential to managing the spectrum of risks that a firm is exposed to. This is moving beyond the ‘established’ range of money laundering and terrorist financing risk into human trafficking, human rights abuses, modern slavery, and environmental crime. AI-based adverse media screening solutions can be trained to monitor all relevant risk areas in real-time if necessary.

Ease of integration and operational efficiency

The final puzzle to consider in the business case is the ease of integration and associated professional services costs. Integrating an adverse media solution into an existing workflow should maximize the operational efficiency of a bank’s risk mitigation program with minimal integration costs.

Using adverse media banks can radically improve their efficiency and effectiveness by viewing AML compliance not just as a regulatory requirement but as part of its core strategy to enhance competitiveness. 

Celent report: Maximizing the Value of Adverse Media Monitoring

For this report, leading research and advisory firm Celent interviewed global banks from across the world, providing practical tips on how adverse media can be integrated into an existing AML value chain.

Download now

To explore more about the practical benefits of adverse media for compliance teams, explore the pieces below:

• How to make adverse media searches actionable and useful for banking
• Delivering a risk-based approach with adverse media
• How can adverse media reduce reputational risk?
• The importance of adverse media for enterprise-wide risk assessments

Footnotes:

1. Cost of Compliance Report 2022: Officers face competing priorities & future planning – Thomson Reuters Institute 
2. https://www.fatf-gafi.org/publications/fatfrecommendations/documents/opportunities-challenges-new-technologies-for-aml-cft.html 
3. https://www.wolfsberg-principles.com/articles/publication-negative-news-screening-faqs 

The post The business case for adverse media screening in banking appeared first on ComplyAdvantage.