The Data Demands for Cross-Border Wealth Management InnovationsThe Data Demands for Cross-Border Wealth Management Innovations
Firms operating in multiple countries must also manage their data estates in compliance with many different data-related regulations.
How well are your data policies and platforms prepared to operate in multiple legal jurisdictions?
Data is powering artificial intelligence—and AI ambitions are driving investments in data and cloud platforms. With the increased use of hyperscalers (the companies that provide cloud services at a significant scale, most commonly Amazon Web Services, Google Cloud and Microsoft Azure) for data and AI workloads comes the need for wealth managers that operate in multiple countries to manage their data estates in compliance with multiple data-related regulations. Accessing, sharing and using data is increasingly complex when wealth managers operate across international borders and global regions—potentially hampering growth in new markets.
Digital and data sovereignty is the principle of ensuring that the data protection requirements for storing, processing and moving data are compliant with, and remain subject to, the local laws of the country or region where the data is collected. Data sovereignty concerns have a significant impact on planned innovations on data, AI and next-gen wealth management solutions. As data privacy laws and the concept of digital sovereignty mature, wealth managers and advisors must evaluate how well they’re prepared to implement the next generation of intelligent, AI-enabled products and services.
New Data Challenges for Wealth Managers
Data technology evolved significantly in the past decade. Regulatory and geopolitical environments have, too. Regulations that govern data privacy (the protection and secure handling of clients’ personal financial information) and AI, combined with geopolitical tensions that exist even between friendly nations, put new pressures on wealth managers to implement effective data policy and architecture. The legal construct of digital and data sovereignty has a meaningful impact on how technology and data assets must be managed and implemented.
In wealth management, most cybersecurity threats and breaches revolve around theft of client data, not of assets, making the focus on security a top concern. Digital independence is another big concern, with countries and regions taking precautions against being overly reliant on technology services delivered by foreign providers.
Governments in Europe and across Asia-Pacific are pushing for sovereignty rules. In the U.S., which the largest software and AI companies call home, data sovereignty is less of a concern, and there’s less data privacy legislation here. But even American domestic wealth managers need to be aware of considerations around the data they’re managing; they must handle it in accordance with the jurisdictions in which it falls.
Data residency (the physical location where data must be stored) and data security (the protection and safeguarding of data assets from unauthorized access) guidelines impact data storage location, retention, access and use. Data privacy regulations, data residency rules and data sovereignty concerns challenge wealth managers and payments processers to operate effectively across multiple regions.
All of the major hyperscalers now either offer or have announced the availability of sovereign cloud solutions, which ensure that data doesn’t cross physical sovereign borders. A sovereign cloud is a cloud computing infrastructure that’s physically geolocated within a specified border (state, national or regional) and that’s designed to ensure compliance with local regulations (including data privacy laws and requirements for managing industry or government data). The push toward sovereign cloud is common in the European Union (including some specific nations), along with Australia, India, Singapore, Switzerland and the United Kingdom.
Understand the Demand for Data
Data (whether structured, unstructured, or semi-structured) and AI are the building blocks for wealth management products and services. As the move toward AI fuels investment in data platforms, wealth managers must have a clear understanding of how financial data is being used. AI, a value multiplier, is driving digital wealth management initiatives and data acquisition. Analytics are increasingly valuable, driving the need for powerful data technology, which in turn continues the push for AI in this data flywheel.
Data privacy, data residency, data security and data sovereignty are the four legal and physical pillars that pertain to data assets. Understanding these—and making sure that data isn’t siloed across a financial institution’s units—is required to execute a data strategy that’s compliant with broad national regulations and industry-specific regulations within financial services. Wealth managers must respect and comply with the legal principles and laws that drive data sovereignty; they may not, however, require sovereign cloud solutions to do so.
Strategize and Implement Effective Tactics
Wealth managers and payment processors must create appropriate strategies around data sovereignty and support it with effective tactics to support growth, including the deployment of AI-enabled products and services at scale across borders. Wealth management firms must manage data jurisdictionally, make sure data is fit for purpose for ingestion into AI models, and be aware of restrictions around data and AI use (e.g., data location, privacy, and/or sensitivity).
Product managers and business leaders can evaluate, among other considerations, how the distributed data and AI infrastructure impacts client solutions and services, data monetization, and the wealth manager’s data center and cloud provider strategy for each region. Now is the time to get your data house in order and manage data as an asset for growth.
Design for Flexibility and Agility
Challenges persist. When wealth managers consider these for their data usage plans, they have the opportunity to navigate digital sovereignty issues and implement flexible, agile offerings. Bringing analytics teams, product managers, and operations managers into the data and AI governance process can help ensure the successful implementation of the data technology road.
Carefully consider the increased costs and risks. Operational complexity, a multi-geography technology footprint, and additional corporate and operational risk compliance requirements are among the factors driving data initiative expenses. On the risk side, privacy and sovereignty regulations will increase the complexity (and cost) of being compliant across multiple legal jurisdictions, with cautions around data use (or misuse) in products, services, and AI models, along with the risk of data access violations.
Also be thorough in evaluating the impact of technology complexity. Consider: sovereignty and residency requirements in data center strategy and data platform technology; on-premises vs cloud data center strategy for the management of applications and their associated data, by country/region; data storage and database technologies; data access and integration, such as for AI models and advanced analytics that need to read from multiple database locations; and legal considerations for data movement and/or replication across borders. Understanding these technological considerations will help wealth managers plan appropriately for medium- and long-term sustainability that supports cross-jurisdictional business growth goals.
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