One-Time Data Capture: The Onboarding Breakthrough Driving Faster, Safer Financial Services

Onboarding in financial institutions is a data-driven process that goes beyond just welcoming a new client. It also encompasses existing clients seeking to establish new entities or open additional accounts. This sprawling task begins with a wealth of data and a web of regulatory requirements. From the outset, institutions must address Know Your Customer obligations, including Customer Due Diligence and anti-money-laundering controls. Yet these steps are only the beginning of a journey that can cascade through dozens of teams and systems. 

Across a financial institution, as many as 30 internal teams may be involved, from relationship management and operations to products and services. Externally, global sub-custodian institutions add another layer of complexity. These groups require overlapping or additional data to set up clients, entities, and accounts in their systems, creating a web that is as challenging as it is critical to navigate. 

Comprehensive understanding of the scope of onboarding: 

The complexity of client and account scenarios defines the scope. New Client, New Entity, New Account (NNN); Existing Client, New Entity, New Account (ENN); and Existing Client, Existing Entity, New Account (EEN) each demand a distinct data footprint. 

Layered on these decisions are considerations about entity structure, legal form and founding jurisdiction, and local requirements where applicable, the number of beneficial owners, and the chosen tax design. Next, account asset details are provided, including the number of accounts and the types of assets—cash, securities, physical, or digital—along with whether these assets are foreign or from emerging markets. Additionally, access rights for third-party investment managers and expected transactional activity are outlined. 

Finally, the spectrum of products and services—custody, accounting, alternatives, derivatives, foreign exchange, tax services, and more—adds its data demands. Taken together, these factors can generate thousands of data points and hundreds of documents per entity. 

Onboarding complexity arises from several interconnected factors that shape data needs, workflows, and governance. The data footprint required for onboarding varies with the chosen scenario: a path involving NNN will differ from ENN or EEN and onboarding an Existing Client with an Existing Entity but a New Account brings yet another set of requirements. In short, the combination of client status, entity status, and account activity directly influences the volume and type of data that must be captured and authenticated. 

Legal structure and founding jurisdiction determine which data must be collected to satisfy regulatory and internal standards, with the number of beneficial owners and the tax design further shaping data requirements. As corporate form and ownership evolve, so does the scope of information that must be gathered, verified, and maintained for compliance and operational purposes. 

The details surrounding accounts and assets affect data needs. Factors include the number and type of accounts, asset classifications such as cash, securities, physical assets, and digital assets, whether assets are foreign or originate from emerging markets, and the level of third-party investment management involvement. Expected transactional activity and related risk considerations also expand the data footprint, driving more extensive reporting, monitoring, and governance requirements. 

The breadth of products and services offered—custody, accounting, alternatives, derivatives, foreign exchange, tax services, and more—adds layers of data demand. Each product line contributes its own data points and documentation requirements, sometimes resulting in thousands of data points and hundreds of documents per entity. Complexity grows as more services are integrated and as regulatory and risk-management expectations evolve. 

The complexity of onboarding is rooted in multiple characteristics, such as interplay of onboarding scenarios, entity structures, asset details, and the range of products and services that may be involved. Recognizing and strategically planning for these distinct factors enables more effective data management, streamlined workflows, and resilient onboarding programs. 

Data collection challenges:

Financial institutions (FIs) are challenged by managing data across multiple segregated operating systems, each built on different platforms at different times and requiring varying data formats. This leads to data redundancy, inconsistency, and the need for manual data transformation.  

While artificial intelligence holds promise as a catalyst for data integration, many groups still rely on manual intervention at some point in the onboarding process. The systems are not only segregated; the teams entering the data are still functionally siloed across the FI, especially legal, risk, and operations. 

In addition to regulatory drivers, internal systems and processes often intensify the complexity. Manual processes and siloed teams can frustrate clients and delay onboarding. Client documentation is not always prepopulated, and many institutions present clients with hundreds of blank documents to complete. Some rely on outdated methods, such as Word or Excel forms, or basic portals. Disconnected systems lead to repetitive data requests, with as much as 60 percent of data elements duplicated across touchpoints. 

Data needed for operational setup is often not collected early enough, creating downstream gaps that may require supplementary information in response to sanctions or negative news alerts. 

Improving the client experience: 

Most financial institutions operate a mix of vendor systems and internally built platforms to handle legal, contracts, KYC, operations, products, and services. The key to reducing frustration and friction for clients lies in the institution's ability to streamline onboarding and data collection. This includes collecting all necessary data upfront during the KYC phase, sending data systematically across departments using artificial intelligence or secure APIs when systems cannot be integrated, and creating a central data process or storage that enables data reuse to minimize repetitive outreach. 

The ability to collect data once and share it across multiple systems and operating groups can significantly reduce and simplify the onboarding process for the client. What if one system could ease the burden on the client by gathering the data in a single instance? 

The payoff for financial institutions can be substantial. Time to revenue accelerates as onboarding durations shrink and profitability emerges sooner. Automation increases, driving lower costs by reducing manual data entry and eliminating duplication. And risk management improves, with fewer setup errors that could complicate regulatory reporting or client service down the line. The need for a fundamental shift in how onboarding is envisioned, designed, and executed is urgent and it is a necessary roadmap item for the more productive future of financial services and customer satisfaction.   

The acts of embracing streamlined data collection and embedding automation into the core workflow, financial institutions can reduce complexity, boost efficiency, and deliver a more seamless experience to clients who navigate a high-stakes regulatory landscape.  

The future of onboarding in financial institutions is not distant but practical and attainable, where data is collected once, trusted across systems, and used to unlock faster, safer, and more competitive service for clients around the globe.