Overview
What is Adverse Media Monitoring
Evan (formerly Evelyn AMM) is a pre-built AI Agent focused on automating adverse media monitoring (AMM) or Negative News. Evan's tasks involve searching for and reviewing news about a person or company to determine if conducting business with them would incur a reputational risk or potential involvement with criminal activity. It is a vital part of the Know Your Customer (KYC) and Anti-Money Laundering (AML) processes for banks and other financial institutions.
Adverse Media Monitoring investigations are essential for uncovering a client's involvement with money laundering, fraud, organized crime, and terrorism. Screening ensures that firms are not unwittingly involved in illegal activity.
Why our customers deal with Adverse Media Monitoring
Regulatory bodies force banks and other financial institutions to perform searches on companies, their top executives, and shareholders. Bank regulators demand reliable operation and security control over Adverse Media Monitoring processing. Incompliance incurs heavy financial penalties and often causes long-term reputational damage.
How Adverse Media Monitoring process is handled today
Research on Adverse Media is mostly manual. Hence, this process is time-consuming and costly.
Central banks have dozens to hundreds of analysts who scan news feeds and aggregators. They review thousands of articles to determine risk. Over 95% of articles are removed because they are false positive alerts and are not relevant to the initial search request.
Benefits of Adverse Media Monitoring automation
Automating Adverse Media Monitoring provides the following benefits:
- Screen more significant amounts of information
- Simplify and standardize the screening process
- Reduce non-compliance risk by finding more relevant and complete adverse information
- Reduce documentation time
- Reduce manual efforts (gain of ~70%)
- Achieve real-time monitoring of events
- Provide operational control and security
- Improve employee satisfaction
Implementation of WorkFusion's Adverse Media Monitoring automation provides the following additional transformational benefits:
- Consistent, unbiased decision-making
- Faster response to customer requests
- Rapid scale-up of processing
- Better risk management through faster awareness of adverse news
Adverse Media sources
Sources include:
- Traditional news sources and media
- Social media and Internet forums
- Regulatory filings and databases, for example, SEC and FINRA disciplinary actions
- Blogs and other non-traditional media
- International organization databases, for example, the World Bank's Stolen Asset Recovery DB
Business Process overview
A Business Process (BP) represents the core workflow and design of any automation within the Work.AI platform. The Adverse Media Monitoring solution includes three BPs:
- Adverse Media Monitoring (Core BP)
- Adverse Media Monitoring Ad hoc Investigation
- Adverse Media Monitoring File Ingestion
Core BP
The core BP contains a suffix with the version number, for example, v3.7. For customers using WorkFusion v10.2.7+, the variation version is indicated after the AI Agent version.
The image below demonstrates the core BP at a high level. Additional information for each step is provided below. Within each process, one or more sub-processes can exist.
The following numbers correspond to the workflow graphic above.
Adverse Media Monitoring Input. For each search request (for instance, entity name), WorkFusion fetches news articles by calling API from pre-defined news sources, gathering text and metadata (such as title, date, and URL) from the articles.
The figure below shows the sub-processes within this step. If multiple providers are configured, the search request is split into distinct requests to each provider.
Adverse Media Monitoring Processing. The unstructured text from each article, including the title, is processed to identify the risk materiality and relevance to the searched entity. The machine learning approach, architecture, and logic used to conduct this analysis include identifying risk factors, negative keywords, categorizing articles, and additional constraints, such as demographics or other information.
A report is generated if no results are found for an entity or the Manual Task is disabled.
If results are found for an entity and the Manual Task is enabled, WorkFusion creates a task for users within Workspace to review the findings. You can access Workspace directly through the Workspace application user interface or embedded in an institution's case management or client lifecycle management system. For more details on the review process, see the guide.
The figure below details the sub-processes within this step:
Prepare articles for ML and process ML results. Articles are prepared to be processed by the ML model. Depending on the media provider, the preparation can require the text to be parsed or reformatted.
Are all articles processed through ML? The model checks if it processed all articles for the entity. Articles are processed in batches. Note that, in some instances, an article can't be processed. Common reasons for this include, but are not limited to, the following:
The article is in a language that is not supported. At the moment, only articles in English or Spanish are supported.
The media provider is Google API, and the source website is unavailable due to scheduled or unexpected maintenance.
The content is unavailable in HTML, for example, an image of a government's most wanted poster.
The article's content is too small to be processed (under 50 words).
The article's content is too large to be processed and skipped due to a runtime error. The current limitation is 10,000 words.
Execute machine learning model. The machine learning model is executed over additional articles as needed. This and the previous steps are executed iteratively until all articles eligible for model screening have been processed.
Merge Searches. Merges the results returned from different news providers.
Filter merged transactions. Filters the completed sub-transactions.
Collect articles. Sets an investigation status for the transaction and groups the results based on rules and ML results.
Manual Task required. The model checks to determine if a Manual Task should be created within Workspace. These settings are configured when setting up the AMM variation in Control Tower.
Prepare data for Manual Task. If the Manual Task is enabled, the data from the ML model is prepared to be reviewed within the Workspace interface.
Adverse Media Monitoring vX.X.X. A Manual Task (or investigation) is created for each screened entity within Workspace. More information about the review process can be found in the guide.
Process Manual Task result. Once a user saves, skips, or closes an investigation, the results are processed.
Manual Task submitted. Checks to determine if the Manual Task is submitted (or closed) versus if it is saved or skipped. When not submitted, it is returned to the queue for an analyst to complete their review of the investigation.
Adverse Media Monitoring Output. A detailed audit trail is created in a standardized PDF (narrative report) or HTML format. The report contains the analyst's decisions on article materiality, cited articles, a confidence score for each article, static URL, keyword citations, full article text, and the final decision and adjudication for the investigation. More information on the output can be found in the guide.
The figure below details the sub-processes within this step.
Generate HTML Report. The results from the investigation are processed, and an HTML version of the report is generated during this step.
If the Manual Task was used, the results also include information the analysts provided during their review.
Is PDF report required? Checks to see if the customer requested a PDF version of the report. This is determined by the parameter set when configuring the AMM variation in Control Tower.
Generate PDF report. Generates a PDF report, if required.
Generate Rest Output. Generates the output for the REST API.
Send Billing Information. Sends Billing events to the Billing Platform.
Record analytics. Audit trail data is prepared for visualization in the WorkFusion Analytics dashboard. For additional information, refer to the guide.
Process batch of transactions. Check whether the execution requires batch processing for combined results generation for each batch. By default, every execution process results in a batch unless it is started via REST API.
Adverse Media Monitoring Batch Processing. In this step, every single transaction is arranged into user-specified batches to be processed together and generate combined result reports, such as a combined report and quality control report for each batch.
The graphics below details the sub-processes within the step:
Merge all transactions. Arrange each transaction into the specified batch. Each batch could contain one or more transactions.
Filter merged transactions. Filters every transaction, allowing only the batch transaction to proceed.
Generate combined report. Generates a combined results report for each batch of transactions
Generate quality control report. Generates a combined quality control report for each batch of transactions.
Split per transaction. Splits all transactions inside a batch into their own individual transactions.
Generate BP Output. Generates a results row for each screened entity. The row contains all the information gathered throughout the execution.
Adverse Media Monitoring Ad Hoc Investigation
The Ad Hoc Investigation BP allows you to create an ad-hoc search screen within Workspace for analysts to initiate investigations as needed.
The figure below demonstrates the Ad Hoc Investigation BP at a high level. Additional information for each step is provided below.
The numbers below correspond to the workflow above:
Split Ad hoc investigation tasks is triggered when a user starts the Ad hoc investigation BP. The Ad hoc investigation tasks are split based on whether or not the Human in the Loop feature is enabled in the configuration for the associated variation.
AMM Ad hoc investigation initialization creates an ad-hoc search screen within Workspace for analysts to use.
Submit Adverse Media Monitoring Investigation Request. Once an analyst submits a search request, WorkFusion fetches news articles by calling API from pre-defined news sources, gathering text and metadata (URL, title, date) from the articles.
Start main AMM BP. During this step, the core BP is run.
Return record to the queue returns the ad-hoc search screen to the queue.
Wait for Manual Task Review. The step is used only if Human in the Loop is enabled. During this step, individual investigations are submitted and marked as complete.
Wait for main AMM BP completion. The BP continues until it is stopped in Control Tower. This allows analysts within Workspace to run as many investigations as needed on an ad-hoc basis as long as the BP is running.
Adverse Media Monitoring File Ingestion
This BP looks for new CSV files in the configured S3 directory every minute and initiates a new investigation if a new file appears.
The numbers below correspond to the workflow above:
Amm FileIngestion Monitor. Monitors the S3 folder for a new file to start the BP according to the settings in the UI configuration.
AMM File Ingestion. The CSV file from S3 is parsed, and the input data is prepared for an NSS or AMM run.
Use Metadata? This is the rule based on the Do you want to use available meta data to adjudicate articles first? setting in the UI configuration. If the setting is Yes, the NSS BP is executed first.
Execute NSS. Synchronously executes the NSS Business Process.
Process NSS results. Processes the results from NSS.
Is it the last record? This is the rule that checks if it is the last transaction from the NSS response. If set to No, it ignores the result.
Run AMM. Asynchronously starts the main AMM Business Process.