A data-driven approach to identifying beneficial owners
Our third instalment of our ultimate beneficial ownership (UBO) series delves into the intricacies of a data-driven approach to identifying beneficial owners. We previously explored the challenges of UBO identification and the evolving regulatory landscape. Now we turn our attention to the pivotal role of delivering data driven UBO identification to enhance compliance efforts.
Amidst the complexity of UBO compliance, a consistent challenge emerges: the fragmented landscape of data. Jurisdictions around the globe define and document beneficial ownership in different ways. Subsequently, banks find themselves navigating a wide array of standards and sources. This problem is not static. It is compounded by the ever-evolving global thinking around what constitutes a beneficial owner and what action should be taken.
Inside the walls of financial institutions, the challenge deepens. Information is stored in different formats and scattered locations. This means that, as regulations tighten, the onus on compliance teams grows exponentially. No longer is their role a simple checkbox exercise. Today, it is about making risk-based decisions, deeply anchored, and evidenced in data. Yet, many are bogged down by outdated infrastructure.
With all this in mind, it becomes evident that the success of UBO identification on a global scale hinges not only on the data itself, but on the holistic approach and process that integrates this data seamlessly. From sourcing accurate external information to optimizing internal storage, processing, and analysis, data stands at the heart of the UBO process, shaping the future of any successful compliance program.
The fragmented data landscape
Navigating the UBO landscape begins with the challenge of gathering data from multiple disparate sources. There is an absence of standardization across datasets. Also combined with the need to trace individuals and entities across borders and corporate structures. As such this often necessitates manual comparison, a burdensome process fraught with potential inaccuracies.
Another significant issue arises from the varied accessibility of UBO registries. While some are readily available to the public, others remain restricted or gated. As a result, affecting the speed at which crucial data can be accessed. Furthermore, the reliability of these data sources varies widely.
This fragmented landscape is further complicated by the need to determine which data is most relevant in each context.
As we transition to a more automated, data-centric approach, the foundation for transformation lies in building robust processes. By clearly orchestrating data pipelines and enforcing robust quality standards, these processes set the stage for the next evolution: perpetual monitoring and the repeatable production of digital UBO profiles through automation.
Harnessing technology for a data-driven approach
The evolution in technology has brought forth sophisticated tools that streamline the UBO data gathering process. Advanced data analytics, machine learning algorithms, and intelligent process automation (including automated data validation systems) now allow for the efficient extraction and analysis of UBO data from diverse sources. For instance, matching and merging data across data sources is now automatable with leading technology solutions. These technologies also streamline data primacy decisions and normalize information to reveal deeper ownership structures.
Central to this transformation is data driven UBO identification. This approach prioritizes the quality and reliability of data. To cultivate this data-centric mindset, firms can start by conducting comprehensive data audits. These can be overseen by cross-departmental data governance committees, to identify gaps and inconsistencies in their current UBO datasets.
Building a digital ecosystem
The next strategic move involves building a digital ecosystem. Such an approach allows for integration with top-tier global providers and vendors. Firms can access refined, standardized, and up to date UBO data wherever and whenever needed. Working with specialized vendors also brings advanced analytics capabilities and ensures alignment with global best practices.
As banks migrate to this data-centric paradigm, powered by automation, they unlock a multitude of benefits. By minimizing the scope for inconsistencies or gaps in their data, banks significantly reduce the risk of error in UBO identification. Accurate data, when embedded within streamlined processes, also underpins the creation of repeatable digital UBO profiles.
Digital know your customer (KYC) profiles
These profiles not only save significant analyst time in data collection, analysis, and formatting but also bolster knowledge management across the enterprise. With these tasks automated, analysts can now focus on making incisive, risk-based decisions on the highest priority cases. Overall, a data-driven approach to UBO enhances the bank’s competitive edge by increasing business agility and reducing operational cost savings.
Looking ahead – The future of UBO identification
A data-driven approach to UBO provides a holistic view of potential risks. It also safeguards banks from significant financial setbacks and bolsters confident decision-making. By leveraging innovative technology for automation, banks can unearth previously obscured connections between beneficial owners. At the heart of UBO success lies a foundation of robust and trusted data. This underscores the importance of the processes, governance and technology that empower this data when navigating the complex realm of beneficial ownership.