Understanding your organization’s various entities and their interrelated relationships is crucial for any risk management program. Over the years, the regulated sector has increasingly adopted new financial crime compliance systems. In addition, it is now starting to use the latest advanced analytics technologies to help monitor and detect suspicious activity effectively. Yet, even in their current form, these controls are not sufficient on their own. There are still gaps that prevent truly effective financial crime compliance. These shortfalls are often traced back to an organization’s data management processes and their ability to provide a trusted understanding of the true identity of the entity and the connected relationships.
How can the industry understand entities better and efficiently identify links and relationships across their data while maintaining operational effectiveness? This missing puzzle piece—identity resolution— makes entity-centric financial crime prevention possible, providing organizations with what can be identified as a single truth.
Offering a comprehensive view of the entity, supported by their data, provides compliance teams a clearer understanding of the entity, improves the accuracy of suspicious activity detection, streamlines investigations and enhances reporting quality. This single truth also enables a seamless customer experience. The best part is that much of today’s identity resolution engines leverage artificial intelligence (AI) and machine learning so that results only get better over time.
Identity Resolution Visualizes Data
Identity resolution is the process of creating links among a plethora of data records and using those links to visualize and understand the data better. During this linking process, identity resolution can recognize when two observations are the same entity, despite some differences, and when two observations are not the same entity at all, despite some similarities.
Identity resolution is necessary for financial crime operations. Financial services organizations continue to expand the amount of internal and trusted third-party data they access and use to strengthen compliance and detect suspicious activity with quicker and greater accuracy. With all this data on hand, it is imperative to use technology that streamlines the data input via deduplication, expediting any data linkage processes to safeguard data quality and processing times.
Critical to data streamlining and the linkage process, identity resolution provides an extra layer of intelligence on top of existing data by determining relationships already present in the different components of the datasets. This derived knowledge can create network views of the data that compliance systems can easily understand and interpret.
Not only does identity resolution find existing links among data, it also further monitors the data for behavioral patterns between entities and effectively identifies hidden relationships throughout each entity’s network. In addition, this technology adds the necessary context to the various data points across internal and external data sources to enrich customer profile data, providing a consolidated, precise view of the entity and its relationship network. This consolidated view gives compliance teams the information needed to manage risk quickly and effectively to make informed decisions confidently.
Risk-Rating Entities and Other Benefits
The current approach to identity resolution provides a range of benefits, from improved suspicious activity monitoring and detection to increased investigation speed and reduced operational costs. Because identity resolution deduplicates entities in real time, it allows for a single, centralized and reliable view of the entity and its risk and uncovers identifying hidden links and obfuscated records. This improved understanding enables entities to be appropriately risk-rated and segmented, ensuring appropriate monitoring is performed on the entity based on a comprehensive and trusted knowledge of their risk. Ultimately, this leads to higher-quality alerts and reduced false positives based on a clearer understanding of what should be normal and abnormal for each entity.
The elimination of duplicate entity data enables investigators to trust they have a single view of all risks and relationships associated with the entity, even if those relationships were previously hidden and unknown. It also avoids false positives resulting from multiple potential alerts for the same duplicated entity and eliminates the need to search for entity data across multiple records. This means that investigators will always have a more accurate view of all the parties involved, shortening the data gathering and research phases of investigations, improving the productivity of investigators and analysts and resulting in faster yet higher-quality investigation outcomes.
Identity resolution is a critical contributor in bolstering data quality, ensuring that organizations have the data clarity necessary to provide clear and accurate evidence of suspicious activity on relevant compliance reports or regulatory filings. Advanced capabilities in this process also allow for better data matching during know your customer (KYC) and screening processes, shortening the time it takes to review and approve new customers.
Unified third-party data also becomes easier to manage with advanced identity resolution. Being able to resolve external data quickly and accurately against the correct internal entity data records increases the ability to identify and detect high-risk activities, mitigating financial crime risk. Resolved entities also make the process of automatically searching third-party data more effective because there will only be one callout for the data rather than multiple callouts for the same data.
Another advantage is that some identity resolution engines use a plug-and-play approach, allowing organizations to improve decision certainty in mere days without interruptions to productivity.
Immediate Access to Financial Crime’s Ecosystem
Since there is an end-to-end benefit of identity resolution that can provide a substantial impact across an entire financial crime ecosystem, today’s financial institutions are looking to integrate and embed these capabilities across the whole spectrum of their financial crime platform fully, from KYC to screening, transaction monitoring, fraud detection and surveillance monitoring. Compliance teams will have immediate access to such critical components as real-time data resolution, relationship enrichment and hidden network identification with fully embedded identity resolution.
With its constant learning and improvement, embedded identity resolution allows organizations to enhance customer experiences, improve suspicious activity detection, streamline investigations and deliver accurate, high-quality reporting today. An integrated approach does not interrupt existing data enrichment processes and flows and allows any external data flow to be switched on at any time, seamlessly. Ultimately, identity resolution plays a vital part in Customer Lifecycle Risk Management by building relationships and understanding links across multiple datasets, enhancing the detection and investigation of suspicious activity, achieving positive outcomes, and delivering effectiveness across financial crime and compliance programs.
Ted Sausen, director, AML subject-matter expert, NICE Actimize, NJ, USA, Ted.Sausen@niceactimize.com
