{"id":11142,"date":"2026-05-18T03:02:04","date_gmt":"2026-05-18T03:02:04","guid":{"rendered":"https:\/\/chartergroupadmin.com\/index.php\/2026\/05\/18\/data-governance-framework-steps\/"},"modified":"2026-05-18T03:02:04","modified_gmt":"2026-05-18T03:02:04","slug":"data-governance-framework-steps","status":"publish","type":"post","link":"https:\/\/chartergroupadmin.com\/index.php\/2026\/05\/18\/data-governance-framework-steps\/","title":{"rendered":"10 Steps to Build a Data Governance Framework"},"content":{"rendered":"\n<p>Data governance is essential for fund administrators to ensure accurate data for tasks like NAV calculations, compliance reporting, and investor records management. Without it, firms risk regulatory fines, reporting errors, and lost investor trust. This guide outlines a 10-step process to establish a reliable data governance framework tailored for fund administration:<\/p>\n<ol>\n<li><strong>Define the Scope<\/strong>: Focus on high-risk areas like investor records or NAV calculations.<\/li>\n<li><strong>Set Objectives<\/strong>: Use measurable goals like reducing errors or improving data completeness.<\/li>\n<li><strong>Assign Roles<\/strong>: Establish accountability with clear roles (e.g., data owners, stewards).<\/li>\n<li><strong>Inventory Data Assets<\/strong>: Map critical data sources and flows across systems.<\/li>\n<li><strong>Develop Policies<\/strong>: Create rules for data quality, access, retention, and privacy.<\/li>\n<li><strong>Implement Controls<\/strong>: Use validation checks, access reviews, and retention schedules.<\/li>\n<li><strong>Select Tools<\/strong>: Use data catalogs, quality management systems, and lineage trackers.<\/li>\n<li><strong>Monitor Compliance<\/strong>: Track KPIs like data incident rates and compliance rates.<\/li>\n<li><strong>Handle Issues<\/strong>: Log exceptions and resolve them with structured workflows.<\/li>\n<li><strong>Refine the Framework<\/strong>: Regularly review policies, roles, and processes to stay aligned with regulations and operational needs.<\/li>\n<\/ol>\n<p><strong>Key takeaway<\/strong>: A structured governance framework reduces risks, improves efficiency, and ensures compliance in fund administration. Firms that implement these steps often see fewer errors, faster reporting, and stronger data management practices.<\/p>\n<figure>         <img decoding=\"async\" src=\"https:\/\/assets.seobotai.com\/undefined\/6a0a5c4d800645b46e62da0f-1779071974862.jpg\" alt=\"10 Steps to Build a Data Governance Framework for Fund Administration\" style=\"width:100%;\"><figcaption style=\"font-size: 0.85em; text-align: center; margin: 8px; padding: 0;\">\n<p style=\"margin: 0; padding: 4px;\">10 Steps to Build a Data Governance Framework for Fund Administration<\/p>\n<\/figcaption><\/figure>\n<h2 id=\"how-to-properly-structure-data-governance-framework\" tabindex=\"-1\" class=\"sb h2-sbb-cls\">How to Properly Structure Data Governance Framework<\/h2>\n<p> <iframe class=\"sb-iframe\" src=\"https:\/\/www.youtube.com\/embed\/9gBA57PPM1o\" frameborder=\"0\" loading=\"lazy\" allowfullscreen style=\"width: 100%; height: auto; aspect-ratio: 16\/9;\"><\/iframe><\/p>\n<h6 id=\"sbb-itb-9792f40\" class=\"sb-banner\" style=\"display: none;color:transparent;\">sbb-itb-9792f40<\/h6>\n<h2 id=\"step-1-define-the-governance-scope\" tabindex=\"-1\" class=\"sb h2-sbb-cls\">Step 1: Define the Governance Scope<\/h2>\n<p>Before diving into policies or assigning roles, it&#8217;s essential to set clear boundaries for your governance framework. Without defined limits, teams risk spreading their efforts too thin. Saad Amrani Joutey from <a href=\"https:\/\/www.fygurs.com\/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\" style=\"display: inline;\">Fygurs<\/a> explains it well:<\/p>\n<blockquote>\n<p>&quot;The best governance programs start narrow and expand deliberately.&quot; <\/p>\n<\/blockquote>\n<p>A practical approach is to begin with <strong>2\u20133 high-risk areas already suffering from poor data quality<\/strong> &#8211; like delayed NAV calculations, reconciliation errors, or compliance reporting gaps. While over 80% of organizations have data governance initiatives, fewer than 25% rate their programs as effective. The key difference often lies in scope: programs that are too broad struggle to deliver results. By starting small, you can focus on critical data areas that need immediate attention.<\/p>\n<h3 id=\"identify-key-fund-data-domains\" tabindex=\"-1\">Identify Key Fund Data Domains<\/h3>\n<p>To begin, assess these core fund administration data domains:<\/p>\n<table style=\"width:100%;\">\n<thead>\n<tr>\n<th>Domain<\/th>\n<th>Fund Administration Examples<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td><strong>Investor Records<\/strong><\/td>\n<td>PII, subscription\/redemption data, contact info, investor management data<\/td>\n<\/tr>\n<tr>\n<td><strong>Accounting<\/strong><\/td>\n<td>NAV calculations, financial records, transaction history, revenue reporting<\/td>\n<\/tr>\n<tr>\n<td><strong>Compliance<\/strong><\/td>\n<td>Regulatory templates, audit trails, consent records, privacy policies<\/td>\n<\/tr>\n<tr>\n<td><strong>Reporting<\/strong><\/td>\n<td>Fact sheets, client portal data, internal tools<\/td>\n<\/tr>\n<tr>\n<td><strong>Master Data<\/strong><\/td>\n<td>Vendor codes, location data, reference codes, fund categories<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>Not every domain requires immediate attention. Focus on those with the <strong>highest risk or the most frequent changes<\/strong>. For example, investor records often involve sensitive PII and regulatory exposure, while accounting data directly impacts NAV accuracy and investor reporting.<\/p>\n<h3 id=\"set-operational-boundaries\" tabindex=\"-1\">Set Operational Boundaries<\/h3>\n<p>Next, define the data to govern, its ownership, and its location. Beyond identifying data types, think about the operational environment &#8211; especially in multi-jurisdiction fund administration. This is particularly important for administrators managing data across multiple entities, regions, or technology setups, whether cloud-based, hybrid, or on-premises.<\/p>\n<p>Clear boundaries around data ownership and location not only ensure regulatory compliance but also improve reliability &#8211; two key themes from the introduction. For example, in offshore jurisdictions like the <a href=\"https:\/\/chartergroupadmin.com\/index.php\/2017\/02\/22\/cayman-islands-hedge-fund-administration\/\" style=\"display: inline;\">Cayman Islands<\/a>, governance must align with local regulations while also adhering to global standards like <a href=\"https:\/\/en.wikipedia.org\/wiki\/General_Data_Protection_Regulation\" target=\"_blank\" rel=\"nofollow noopener noreferrer\" style=\"display: inline;\">GDPR<\/a> and <a href=\"https:\/\/oag.ca.gov\/privacy\/ccpa\" target=\"_blank\" rel=\"nofollow noopener noreferrer\" style=\"display: inline;\">CCPA<\/a>. A <strong>federated model<\/strong> can be effective here: a central governance team sets overarching standards, while domain-level teams manage day-to-day implementation. This approach balances consistency with the flexibility needed for multi-jurisdiction operations.<\/p>\n<p>Matt Sullivan, Director of Technical Account Management at <a href=\"https:\/\/www.alation.com\/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\" style=\"display: inline;\">Alation<\/a>, emphasizes the importance of starting small:<\/p>\n<blockquote>\n<p>&quot;You start off small with a small set of data and a small set of policies, and then eventually you mature out to more robust processes and tackle additional data domains.&quot; <\/p>\n<\/blockquote>\n<p>To avoid confusion and delays, assign a clear business owner and priority level to each domain before advancing to policy development and control implementation.<\/p>\n<h2 id=\"step-2-set-governance-objectives-and-principles\" tabindex=\"-1\" class=\"sb h2-sbb-cls\">Step 2: Set Governance Objectives and Principles<\/h2>\n<p>Once your scope is clear, it\u2019s time to determine what governance should accomplish and the rules that will guide its daily operations. Without clear goals, governance risks becoming just another unused document. To avoid that, focus on creating specific, measurable objectives and establishing principles that keep governance effective and actionable.<\/p>\n<h3 id=\"define-measurable-governance-goals\" tabindex=\"-1\">Define Measurable Governance Goals<\/h3>\n<p>Goals like &quot;improve data quality&quot; sound good but lack the clarity needed to measure success. Saad Amrani Joutey emphasizes this idea:<\/p>\n<blockquote>\n<p>&quot;If you cannot quantify the impact of your governance program, you cannot justify its continued investment.&quot; <\/p>\n<\/blockquote>\n<p>To make goals actionable, use the <strong>SMART framework<\/strong> &#8211; objectives should be Specific, Measurable, Achievable, Relevant, and Time-bound. For example, in fund administration, you might aim to &quot;reduce NAV reporting errors by 20% within six months&quot; or &quot;ensure 95%+ of required investor record fields are populated within 90 days.&quot; These types of goals not only give your team a clear target but also provide leadership with tangible proof of progress.<\/p>\n<p>A 90-day timeline is a good starting point for achieving early wins and building trust in the governance program. Below is a table that demonstrates how to structure objectives across key areas in fund operations:<\/p>\n<table style=\"width:100%;\">\n<thead>\n<tr>\n<th>Objective Category<\/th>\n<th>Key Focus Areas<\/th>\n<th>Measurable Metric Example<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td><strong>Data Quality<\/strong><\/td>\n<td>Accuracy, Completeness, Timeliness<\/td>\n<td>% of required fields populated (Target: 95%+) <\/td>\n<\/tr>\n<tr>\n<td><strong>Compliance<\/strong><\/td>\n<td>Privacy, Audit Trails, Retention<\/td>\n<td>Number of policy violations or audit findings <\/td>\n<\/tr>\n<tr>\n<td><strong>Efficiency<\/strong><\/td>\n<td>Automation, Interoperability<\/td>\n<td>Reduction in time spent on manual data reconciliation <\/td>\n<\/tr>\n<tr>\n<td><strong>Access<\/strong><\/td>\n<td>Security, Least Privilege<\/td>\n<td>Average time to respond to data access requests <\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h3 id=\"establish-governance-principles\" tabindex=\"-1\">Establish Governance Principles<\/h3>\n<p>While goals define <em>what<\/em> you\u2019re working toward, principles outline <em>how<\/em> you\u2019ll achieve them. For fund administration, four key principles stand out:<\/p>\n<ul>\n<li><strong>Accountability<\/strong>: Ensure every data attribute has a designated owner who is responsible for its accuracy and upkeep.<\/li>\n<li><strong>Consistency<\/strong>: Use uniform validation rules across teams to eliminate discrepancies and debates over conflicting data.<\/li>\n<li><strong>Traceability<\/strong>: Maintain a clear history of data from its origin through every transformation, which is critical for audits and investor trust.<\/li>\n<li><strong>Enablement<\/strong>: Structure governance to empower teams to work efficiently, not slow them down.<\/li>\n<\/ul>\n<blockquote>\n<p>&quot;Data Governance isn&#8217;t about putting up barriers; it&#8217;s about enabling control and confidence for those who use the data.&quot; &#8211; Arkon Data <\/p>\n<\/blockquote>\n<p>These principles should be more than just words in a policy document. Share them with every team involved in data handling and integrate them into onboarding, training sessions, and governance council discussions. As Arkon Data wisely notes, &quot;Data governance without structure is just an empty promise&quot;. Principles give your governance framework the structure and clarity it needs to succeed.<\/p>\n<h2 id=\"step-3-assign-roles-and-decision-rights\" tabindex=\"-1\" class=\"sb h2-sbb-cls\">Step 3: Assign Roles and Decision Rights<\/h2>\n<p>With your objectives and guiding principles established, the next step is to assign clear and accountable roles throughout the organization. As Jenna O&#8217;Jea from <a href=\"https:\/\/www.analytics8.com\/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\" style=\"display: inline;\">Analytics8<\/a> explains:<\/p>\n<blockquote>\n<p>&quot;For data governance to be successful, every stakeholder &#8211; be it a C-level executive, a data steward, or a member of the IT department &#8211; needs a clear understanding of their responsibilities.&quot; <\/p>\n<\/blockquote>\n<p>When roles are unclear, progress in governance can grind to a halt. In fact, 73% of digital transformation initiatives face delays due to governance bottlenecks. Setting clear roles and responsibilities ensures smoother decision-making processes, especially in fund administration.<\/p>\n<h3 id=\"key-governance-roles\" tabindex=\"-1\">Key Governance Roles<\/h3>\n<p>Effective governance in fund administration typically revolves around five core roles:<\/p>\n<ul>\n<li><strong>Executive Sponsor<\/strong>: Usually the Chief Data Officer (CDO) or Chief Operating Officer (COO), this person provides the authority and resources to drive the governance program forward.<\/li>\n<li><strong>Data Owners<\/strong>: Senior business leaders, such as a CFO or VP of Operations, who are accountable for specific data areas (e.g., investor records or financial reporting). They approve access requests and ensure compliance within their domains.<\/li>\n<li><strong>Data Stewards<\/strong>: These are the hands-on experts responsible for monitoring data quality, maintaining the business glossary, and serving as a bridge between business and IT teams.<\/li>\n<li><strong>Data Custodians<\/strong>: Focused on the technical side, they handle storage, encryption, backups, and access controls.<\/li>\n<li><strong>Regulatory Compliance Officer<\/strong>: Ensures data practices align with regulations like <a href=\"https:\/\/www.irs.gov\/businesses\/corporations\/foreign-account-tax-compliance-act-fatca\" target=\"_blank\" rel=\"nofollow noopener noreferrer\" style=\"display: inline;\">FATCA<\/a>, <a href=\"https:\/\/www.oecd.org\/en\/topics\/sub-issues\/international-standards-on-tax-transparency\/tax-transparency-resource-centre.html\" target=\"_blank\" rel=\"nofollow noopener noreferrer\" style=\"display: inline;\">CRS<\/a>, and AML &#8211; key requirements in fund administration.<\/li>\n<\/ul>\n<p>These roles form the foundation of a governance framework that enables consistent policy execution. While business leaders take accountability, IT teams are tasked with implementing the necessary controls.<\/p>\n<h3 id=\"decision-making-and-policy-approval\" tabindex=\"-1\">Decision-Making and Policy Approval<\/h3>\n<p>After defining roles, the next step is to establish a structured decision-making process to minimize delays. A <strong>Governance Council<\/strong>, composed of senior leaders from various functions, should meet monthly to approve policies, resolve cross-domain conflicts, and provide strategic direction. To streamline decision-making, a tiered structure can help prioritize and address issues efficiently:<\/p>\n<table style=\"width:100%;\">\n<thead>\n<tr>\n<th>Level<\/th>\n<th>Resolver<\/th>\n<th>Target Resolution<\/th>\n<th>Type of Decision<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td><strong>Level 1<\/strong><\/td>\n<td>Data Steward<\/td>\n<td>Same day<\/td>\n<td>Routine questions and standard process execution<\/td>\n<\/tr>\n<tr>\n<td><strong>Level 2<\/strong><\/td>\n<td>Data Owner<\/td>\n<td>2 business days<\/td>\n<td>Issues requiring business judgment or domain trade-offs<\/td>\n<\/tr>\n<tr>\n<td><strong>Level 3<\/strong><\/td>\n<td>Cross-Domain Forum<\/td>\n<td>1 week<\/td>\n<td>Issues affecting multiple domains<\/td>\n<\/tr>\n<tr>\n<td><strong>Level 4<\/strong><\/td>\n<td>Governance Council<\/td>\n<td>2 weeks<\/td>\n<td>Strategic changes and major policy exceptions<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p><em>Source: <\/em><\/p>\n<p>To clarify task responsibilities, use a RACI matrix to define who is Responsible, Accountable, Consulted, and Informed. Regularly review these role assignments &#8211; ideally every 90 days or whenever there\u2019s a major regulatory update. Embedding governance responsibilities into <a href=\"https:\/\/chartergroupadmin.com\/index.php\/careers\/\" style=\"display: inline;\">job descriptions<\/a> and performance evaluations ensures accountability over the long term. This approach lays the groundwork for the next step: mapping data inventory and lineage in Step 4.<\/p>\n<h2 id=\"step-4-inventory-data-assets-and-data-flows\" tabindex=\"-1\" class=\"sb h2-sbb-cls\">Step 4: Inventory Data Assets and Data Flows<\/h2>\n<p>Once roles and decision-making structures are in place, the next step is to build a clear understanding of your data landscape. Without a detailed inventory of your data and its flow, governance policies lack a proper foundation.<\/p>\n<h3 id=\"identify-critical-data-sources\" tabindex=\"-1\">Identify Critical Data Sources<\/h3>\n<p>Fund administration relies on data from multiple domains, each with its own systems and risks. Key areas to focus on include accounting systems (used for NAV reporting), investor portals, AML\/KYC compliance records, valuation inputs, fee schedules, capital call records, distribution logs, and tax exports. Additionally, map out the tools and systems like ETL\/ELT pipelines, MDM systems, and API connectivity platforms that support regulatory reporting and client services.<\/p>\n<p>One major challenge is that many data sources remain unmanaged &#8211; stored in local files or shared drives &#8211; rather than in controlled databases. The table below provides an overview of the main data domains and their associated sources:<\/p>\n<table style=\"width:100%;\">\n<thead>\n<tr>\n<th>Fund Admin Data Domain<\/th>\n<th>Critical Data Sources<\/th>\n<th>Key Systems\/Tools<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td><strong>Financial\/NAV<\/strong><\/td>\n<td>Accounting systems, valuation inputs, fee schedules<\/td>\n<td>MDM, ETL pipelines, signed snapshots<\/td>\n<\/tr>\n<tr>\n<td><strong>Investor\/LP Data<\/strong><\/td>\n<td>Investor portals, capital calls, distribution logs<\/td>\n<td>CRM, signed document repositories<\/td>\n<\/tr>\n<tr>\n<td><strong>Compliance\/Regulatory<\/strong><\/td>\n<td>AML\/KYC records, tax exports, regulatory templates<\/td>\n<td>Data catalogs, audit trails<\/td>\n<\/tr>\n<tr>\n<td><strong>Operational\/Product<\/strong><\/td>\n<td>Fact sheets, website feeds, <a href=\"https:\/\/chartergroupadmin.com\/index.php\/2024\/03\/17\/ai-hedge-fund-administration\/\" style=\"display: inline;\">AI-driven analytics tools<\/a><\/td>\n<td>API-driven connectivity, metadata repositories<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>To avoid duplication and streamline updates, assign a dedicated owner to every data attribute. This ensures that updates come directly from those who are most familiar with the information.<\/p>\n<p>The next step is to analyze how this data moves between systems and how it is retained, completing the governance framework.<\/p>\n<h3 id=\"analyze-data-lineage-and-retention\" tabindex=\"-1\">Analyze Data Lineage and Retention<\/h3>\n<p>After cataloging your data sources, it&#8217;s crucial to map how data flows across systems and define retention policies. Knowing where data resides is only part of the equation &#8211; you also need to track its movement and transformation. In fund administration, this is often referred to as data lineage, which boils down to answering a critical question:<\/p>\n<blockquote>\n<p>&quot;Lineage is more than a diagram&#8230; in private markets, lineage means answering a simple but high-stakes question: where did this number come from, who changed it, when, and under what approved process?&quot; &#8211; datastore.cloud <\/p>\n<\/blockquote>\n<p>A reliable way to manage this is by treating operational data &#8211; such as capital calls, NAV marks, and fee amendments &#8211; as <strong>immutable events<\/strong> instead of overwriting records. Combine this with cryptographically signed snapshots to capture the exact state of data at specific points in time. This approach simplifies quarterly closes and investor reporting while ensuring accuracy and traceability.<\/p>\n<p>Documenting transformation logic is equally important. Processes like fee calculations, FX conversions, and allocation rules should be stored as versioned code, allowing you to recreate prior periods when needed.<\/p>\n<p>Retention policies should align with both regulatory and contractual obligations. In private markets, retention periods are often longer than in other industries. Embed these retention requirements directly into your lineage documentation to ensure clarity on how long data persists as it flows through systems. Whenever possible, automate archiving and disposal processes to minimize manual errors.<\/p>\n<h2 id=\"step-5-create-governance-policies-and-standards\" tabindex=\"-1\" class=\"sb h2-sbb-cls\">Step 5: Create Governance Policies and Standards<\/h2>\n<p>Once you\u2019ve mapped your data flow, the next step is to establish formal policies that ensure proper data management throughout fund administration. These policies translate your documented knowledge into enforceable rules, creating a framework for data handling. They also set the stage for implementing quality controls, managing access, and monitoring compliance, which will be covered later.<\/p>\n<h3 id=\"policy-areas-to-address\" tabindex=\"-1\">Policy Areas to Address<\/h3>\n<p>To build a strong governance framework, focus on five key policy areas: <strong>Data Quality<\/strong>, <strong>Access &amp; Security<\/strong>, <strong>Metadata<\/strong>, <strong>Lifecycle<\/strong>, and <strong>Privacy<\/strong>. Each of these addresses specific risks, but together, they create a complete operational model.<\/p>\n<blockquote>\n<p>&quot;Data governance is the operating model that defines who can take what actions, on what data, in what situations, and using what methods.&quot; &#8211; Saad Amrani Joutey, Data Governance Expert <\/p>\n<\/blockquote>\n<p>Here\u2019s how these policy areas align with fund administration needs and the standards you\u2019ll need to define:<\/p>\n<table style=\"width:100%;\">\n<thead>\n<tr>\n<th>Policy Area<\/th>\n<th>Focus for Fund Administration<\/th>\n<th>Key Standards to Define<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td><strong>Data Quality<\/strong><\/td>\n<td>Validation logic and point-of-entry checks<\/td>\n<td>Completeness, Accuracy, Freshness SLAs<\/td>\n<\/tr>\n<tr>\n<td><strong>Access &amp; Security<\/strong><\/td>\n<td>Role-based access and least privilege<\/td>\n<td>Encryption, Masking, Audit requirements<\/td>\n<\/tr>\n<tr>\n<td><strong>Metadata<\/strong><\/td>\n<td>Single version of truth for KPIs\/Terms<\/td>\n<td>Naming conventions, Formatting, Lineage<\/td>\n<\/tr>\n<tr>\n<td><strong>Lifecycle<\/strong><\/td>\n<td>Regulatory compliance (GDPR\/CCPA)<\/td>\n<td>Retention periods, Archival, Disposal<\/td>\n<\/tr>\n<tr>\n<td><strong>Privacy<\/strong><\/td>\n<td>Consent and subject access rights<\/td>\n<td>Data classification (Public vs. Restricted)<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>For <strong>data quality<\/strong>, set standards across six dimensions: Completeness, Accuracy, Consistency, Timeliness, Uniqueness, and Validity. This structured approach can deliver tangible results. For example, one financial firm reported a jump in customer data completeness from 72% to 96% after implementing these standards.<\/p>\n<p>When it comes to <strong>access management<\/strong>, follow the <em>Principle of Least Privilege (POLP)<\/em>. This means users only get the minimum access needed for their role. Organize data into clear categories: <strong>Public<\/strong> (accessible to all), <strong>Restricted<\/strong> (limited to specific roles), <strong>Confidential<\/strong> (need-to-know basis), and <strong>Prohibited<\/strong> (sensitive data like PII with legal restrictions).<\/p>\n<p>Drafting policies requires consistency. Each policy should include the following sections: purpose, scope, statement, roles, compliance measures, exceptions process, and review schedule. This structure ensures policies remain auditable and adaptable as regulations change.<\/p>\n<p>Standardized policies also depend on clear definitions, which leads us to the next step: establishing naming conventions.<\/p>\n<h3 id=\"establish-naming-conventions-and-definitions\" tabindex=\"-1\">Establish Naming Conventions and Definitions<\/h3>\n<p>Using consistent terminology is crucial, especially for regulatory reporting, where discrepancies can be costly.<\/p>\n<blockquote>\n<p>&quot;Standardising business rules ensures everyone interprets data the same way and applies the same checks before information is published.&quot; &#8211; FE Fundinfo <\/p>\n<\/blockquote>\n<p>A centralized business glossary helps eliminate inconsistencies. Define key terms like &quot;NAV&quot;, &quot;AUM&quot;, or &quot;distribution date&quot; and assign a domain owner to oversee updates. Storing these definitions in a data catalog, rather than a static spreadsheet, ensures they stay relevant and linked to workflows.<\/p>\n<p>Naming conventions should also address data formats. For instance, standardize all dates to MM\/DD\/YYYY and currency values to USD with two decimal places. Automated validation at the point of data entry can catch errors before they spread to other systems.<\/p>\n<blockquote>\n<p>&quot;The fastest way to reduce inconsistency is to define who is responsible for each data field.&quot; &#8211; FE Fundinfo <\/p>\n<\/blockquote>\n<p>Assign a data steward to enforce these standards across business and IT teams. This role is critical for maintaining consistency and ensuring everyone adheres to the agreed-upon rules.<\/p>\n<h2 id=\"step-6-set-controls-for-quality-access-and-retention\" tabindex=\"-1\" class=\"sb h2-sbb-cls\">Step 6: Set Controls for Quality, Access, and Retention<\/h2>\n<p>To enforce your documented policies effectively, you need controls for validation, access, and retention. These controls take the policies and standards you developed in Steps 4 and 5 and put them into action. This approach helps reduce risks tied to NAV calculations, investor reporting, and regulatory compliance.<\/p>\n<h3 id=\"define-data-quality-validation-processes\" tabindex=\"-1\">Define Data Quality Validation Processes<\/h3>\n<p>Preventing errors at the source is key to maintaining data quality. Automated validation at ingestion is a powerful way to achieve this. As FE Fundinfo explains:<\/p>\n<blockquote>\n<p>&quot;Validation at the point of entry prevents errors from spreading. It also improves regulatory confidence by ensuring data lineage can be demonstrated with clarity.&quot; <\/p>\n<\/blockquote>\n<p>By implementing automated validation rules, you can catch issues like missing fields, format mismatches, or out-of-range values before they affect NAV calculations, investor reports, or regulatory filings. Continuous monitoring further improves quality by flagging stale prices or duplicate records before they impact critical outputs. These measures are crucial when you consider that poor data quality costs businesses an average of <strong>$12.9 million annually<\/strong>, and data professionals spend up to 80% of their time cleaning data instead of analyzing it.<\/p>\n<p>To ensure accountability, set up an escalation workflow. This system assigns flagged issues to a data steward, prioritizes their resolution, and logs outcomes for audit purposes. This not only reinforces compliance but also provides a clear trail for audits.<\/p>\n<h3 id=\"access-reviews-and-retention-schedules\" tabindex=\"-1\">Access Reviews and Retention Schedules<\/h3>\n<p>Once validation controls are in place, the next step is to enforce strict access reviews and retention schedules. These measures work together to protect sensitive data from risks like unauthorized access or unnecessary storage.<\/p>\n<p>Start with <strong>Role-Based Access Control (RBAC)<\/strong> combined with multi-factor authentication. Apply the <em>Principle of Least Privilege<\/em> to limit access to only what is necessary. Regular access audits are essential to identify and revoke permissions that are no longer needed, preventing issues like permission creep.<\/p>\n<p>Retention schedules are equally important. Each data category &#8211; whether it\u2019s investor records, trade data, or compliance documents &#8211; should be aligned with the legal retention periods outlined by regulations like GDPR or <a href=\"https:\/\/en.wikipedia.org\/wiki\/Digital_Operational_Resilience_Act\" target=\"_blank\" rel=\"nofollow noopener noreferrer\" style=\"display: inline;\">DORA<\/a>. Automating the disposal process ensures data is deleted when it\u2019s no longer needed. As <a href=\"https:\/\/lumenalta.com\/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\" style=\"display: inline;\">Lumenalta<\/a> highlights:<\/p>\n<blockquote>\n<p>&quot;Retaining data beyond its required period increases storage costs and security risks, while premature disposal results in lost information.&quot; <\/p>\n<\/blockquote>\n<p>The table below summarizes the key controls across quality, access, and retention:<\/p>\n<table style=\"width:100%;\">\n<thead>\n<tr>\n<th>Control Category<\/th>\n<th>Operational Control<\/th>\n<th>Purpose<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td><strong>Quality<\/strong><\/td>\n<td>Automated validation at ingestion<\/td>\n<td>Blocks errors before they reach downstream systems <\/td>\n<\/tr>\n<tr>\n<td><strong>Quality<\/strong><\/td>\n<td>Data profiling &amp; cleansing<\/td>\n<td>Identifies duplicates and missing values in critical fields <\/td>\n<\/tr>\n<tr>\n<td><strong>Access<\/strong><\/td>\n<td>Role-Based Access Control (RBAC)<\/td>\n<td>Restricts sensitive data to authorized users only <\/td>\n<\/tr>\n<tr>\n<td><strong>Access<\/strong><\/td>\n<td>Periodic permission audits<\/td>\n<td>Removes stale access and prevents permission creep <\/td>\n<\/tr>\n<tr>\n<td><strong>Retention<\/strong><\/td>\n<td>Automated disposal protocols<\/td>\n<td>Deletes data at the end of its legal lifecycle <\/td>\n<\/tr>\n<tr>\n<td><strong>Retention<\/strong><\/td>\n<td>Archival procedures<\/td>\n<td>Moves inactive data to secure, low-cost storage <\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2 id=\"step-7-select-tools-and-workflow-support\" tabindex=\"-1\" class=\"sb h2-sbb-cls\">Step 7: Select Tools and Workflow Support<\/h2>\n<p>Now that you&#8217;ve established your controls in Step 6, the focus shifts to finding the right tools to enforce them effectively. These tools should integrate smoothly into your existing workflows, ensuring that governance becomes a natural part of your operations.<\/p>\n<h3 id=\"governance-tool-categories\" tabindex=\"-1\">Governance Tool Categories<\/h3>\n<p>Each tool category addresses a specific governance need, helping you maintain consistency and control across your data processes. Here&#8217;s a breakdown:<\/p>\n<ul>\n<li><strong>Data catalogs<\/strong>: These centralize metadata and maintain a shared business glossary, ensuring terms like &quot;NAV&quot; or &quot;AUM&quot; are defined consistently across teams and systems.<\/li>\n<li><strong>Data quality management systems (DQMS)<\/strong>: Automate profiling and validation to catch errors before they impact downstream reports.<\/li>\n<li><strong>Lineage tracking tools<\/strong>: Map data movement between systems, a critical feature for audit readiness in regulated industries.<\/li>\n<li><strong>Access control platforms<\/strong>: Enforce role-based permissions and detect Personally Identifiable Information (PII).<\/li>\n<li><strong>Workflow and product mastering tools<\/strong>: Provide a single source of truth for fund attributes, ensuring consistency in regulatory templates, fact sheets, and client portals.<\/li>\n<\/ul>\n<table style=\"width:100%;\">\n<thead>\n<tr>\n<th>Tool Category<\/th>\n<th>Primary Purpose<\/th>\n<th>Key Features<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td><strong>Data Catalog<\/strong><\/td>\n<td>Discovery &amp; understanding<\/td>\n<td>Metadata management, business glossary, trust flags<\/td>\n<\/tr>\n<tr>\n<td><strong>Data Quality<\/strong><\/td>\n<td>Accuracy &amp; reliability<\/td>\n<td>Automated profiling, validation rules, quality dashboards<\/td>\n<\/tr>\n<tr>\n<td><strong>Lineage Tracking<\/strong><\/td>\n<td>Audit &amp; compliance<\/td>\n<td>Column-level lineage, impact analysis, data flow mapping<\/td>\n<\/tr>\n<tr>\n<td><strong>Access Control<\/strong><\/td>\n<td>Security &amp; privacy<\/td>\n<td>RBAC, PII detection, encryption, consent management<\/td>\n<\/tr>\n<tr>\n<td><strong>Workflow\/Product Master<\/strong><\/td>\n<td>Operational efficiency<\/td>\n<td>Approval workflows, API connectivity, single version of truth<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>For the best results, start small by focusing on high-impact areas. Many organizations that adopt this targeted approach report noticeable improvements within just 90 days.<\/p>\n<h3 id=\"integrating-tools-with-fund-administration-processes\" tabindex=\"-1\">Integrating Tools with Fund Administration Processes<\/h3>\n<p>A well-chosen tool should operate seamlessly within your current workflows. Begin by mapping your data flows &#8211; from trade ingestion to investor reporting &#8211; to identify bottlenecks and inefficiencies. Then, prioritize tools with API-driven connectivity to ensure data updates flow automatically between internal systems and external outputs like regulatory filings or client portals.<\/p>\n<p>Automation plays a key role here. As FE Fundinfo explains:<\/p>\n<blockquote>\n<p>&quot;Automation does not replace people. It frees them from repetitive tasks so they can focus on analysis, oversight and innovation.&quot; <\/p>\n<\/blockquote>\n<p>Incorporate automated validation within your ETL pipelines, streamline access requests with structured approval workflows, and use automated lineage tracking to reduce manual errors and risks. Breaking down data silos is crucial &#8211; over 75% of executives cite silos as a major barrier to internal collaboration. Proper tool integration directly addresses this issue.<\/p>\n<p>For fund administrators, embedding these governance tools into daily workflows is essential. For instance, <a href=\"https:\/\/chartergroupadmin.com\" style=\"display: inline;\">Charter Group Fund Administration<\/a> emphasizes the importance of integrating data governance to uphold strong regulatory compliance and operational efficiency.<\/p>\n<p>With these tools in place, you&#8217;ll be well-equipped to monitor compliance and measure performance effectively.<\/p>\n<h2 id=\"step-8-monitor-compliance-and-reporting\" tabindex=\"-1\" class=\"sb h2-sbb-cls\">Step 8: Monitor Compliance and Reporting<\/h2>\n<p>Once you&#8217;ve integrated your tools in Step 7, it&#8217;s time to ensure that your governance framework is functioning as intended. Monitoring is where policies shift from being theoretical guidelines to becoming actionable and measurable practices.<\/p>\n<h3 id=\"governance-metrics-and-kpis\" tabindex=\"-1\">Governance Metrics and KPIs<\/h3>\n<p>To assess the health of your governance efforts, focus on a few <strong>key metrics<\/strong> that provide clear insights. As Maarten Masschelein, CEO and Founder at <a href=\"https:\/\/soda.io\/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\" style=\"display: inline;\">Soda<\/a>, explains:<\/p>\n<blockquote>\n<p>&quot;Most data governance programs fail for a simple reason. They stop at defining the policy.&quot; <\/p>\n<\/blockquote>\n<p>The numbers back this up. Without active governance, data quality can degrade by 2% to 3% per month. In fund administration, where accurate NAV calculations and investor reporting rely on precise data, even small errors can lead to major consequences.<\/p>\n<p>Here\u2019s a breakdown of key metrics to track:<\/p>\n<table style=\"width:100%;\">\n<thead>\n<tr>\n<th>Metric Category<\/th>\n<th>KPI<\/th>\n<th>What It Measures<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td><strong>Data Quality<\/strong><\/td>\n<td>Data Incident Rate<\/td>\n<td>Number of high-impact data incidents per month <\/td>\n<\/tr>\n<tr>\n<td><strong>Data Quality<\/strong><\/td>\n<td>Mean Time to Resolve (MTTR)<\/td>\n<td>Average time from detection to resolution <\/td>\n<\/tr>\n<tr>\n<td><strong>Policy Compliance<\/strong><\/td>\n<td>Policy Compliance Rate<\/td>\n<td>Percentage of automated checks passing for Tier 1 datasets <\/td>\n<\/tr>\n<tr>\n<td><strong>Accountability<\/strong><\/td>\n<td>Owner Coverage<\/td>\n<td>Percentage of critical datasets with an assigned owner <\/td>\n<\/tr>\n<tr>\n<td><strong>Compliance<\/strong><\/td>\n<td>Volume of Exceptions<\/td>\n<td>Total documented deviations from standard policy <\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>One striking statistic: organizations that assign clear data ownership see three times fewer data quality incidents compared to those that don\u2019t. This makes tracking <strong>Owner Coverage<\/strong> a particularly impactful KPI.<\/p>\n<p>For fund administration, it&#8217;s crucial to run a <strong>validation checklist<\/strong> before releasing monthly reports. This checklist should include verifying control totals (e.g., debits vs. credits), checking period-over-period movement thresholds, and reconciling data across sources &#8211; like comparing ERP balances with bank statements. At <a href=\"https:\/\/chartergroupadmin.com\/\" style=\"display: inline;\">Charter Group Fund Administration<\/a> (https:\/\/chartergroupadmin.com), these steps ensure that data is <em>decision-grade<\/em> and ready for board review without requiring additional verification.<\/p>\n<p>By keeping a close eye on these KPIs, you&#8217;ll be well-prepared to handle exceptions and resolve issues efficiently.<\/p>\n<h3 id=\"exception-handling-and-issue-logging\" tabindex=\"-1\">Exception Handling and Issue Logging<\/h3>\n<p>Detecting a problem is just the beginning; how you handle it determines the strength of your governance framework.<\/p>\n<p>Develop a repeatable process: define policies, automate checks, trigger alerts, and remediate. Log every exception centrally in your data catalog, including details like the timestamp, affected dataset, assigned owner, and resolution status. This creates a reliable audit trail that supports both internal reviews and external compliance requirements.<\/p>\n<p>Tie alerts to the RACI matrix you built in Step 3. For example, if a Tier 1 dataset fails a validation check, the alert should go directly to the person designated as <strong>Responsible<\/strong> or <strong>Accountable<\/strong> for that dataset. Avoid generic notifications that can easily be ignored.<\/p>\n<p>For recurring issues, create concise <strong>remediation playbooks<\/strong>. These should outline whether the fix can be automated or needs human intervention. As Martin Duben, Founder of <a href=\"https:\/\/www.onetribeadvisory.com\/our-expertise\/governance\/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\" style=\"display: inline;\">Onetribe<\/a>, emphasizes:<\/p>\n<blockquote>\n<p>&quot;Governance is not a project &#8211; it is a cadence.&quot; <\/p>\n<\/blockquote>\n<h2 id=\"step-9-maintain-and-improve-the-framework\" tabindex=\"-1\" class=\"sb h2-sbb-cls\">Step 9: Maintain and Improve the Framework<\/h2>\n<p>A governance framework isn\u2019t a \u201cset it and forget it\u201d kind of thing. As operational needs shift, fund structures evolve, and regulations change, your framework must keep pace. Think of it as a living, breathing system that grows and adapts alongside your data environment.<\/p>\n<p>Maarten Masschelein, CEO and Founder at Soda, explains it well:<\/p>\n<blockquote>\n<p>&quot;Effective governance behaves more like product management. You start small, prioritize what delivers immediate value, ship something that works, measure usage and impact, and iterate.&quot; <\/p>\n<\/blockquote>\n<h3 id=\"periodic-policy-and-role-reviews\" tabindex=\"-1\">Periodic Policy and Role Reviews<\/h3>\n<p>The best way to keep your framework relevant is by committing to <strong>regular reviews<\/strong>. These reviews ensure your policies, roles, and processes stay aligned with both day-to-day realities and long-term goals.<\/p>\n<table style=\"width:100%;\">\n<thead>\n<tr>\n<th>Review Frequency<\/th>\n<th>Focus Area<\/th>\n<th>Key Participants<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td><strong>Monthly<\/strong><\/td>\n<td>KPI review, urgent policy escalations<\/td>\n<td>Data Governance Council, Executive Sponsor <\/td>\n<\/tr>\n<tr>\n<td><strong>Quarterly<\/strong><\/td>\n<td>Maturity assessment, feedback loop analysis, roadmap adjustment<\/td>\n<td>Governance Lead, Data Owners, Stewards <\/td>\n<\/tr>\n<tr>\n<td><strong>Annual<\/strong><\/td>\n<td>Strategic alignment, regulatory compliance audit, role reassessment<\/td>\n<td>Executive Leadership, CDO, Risk\/Compliance <\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>The exception log from Step 8 is a goldmine for quarterly reviews. Recurring issues often highlight areas where policies are either outdated or overly rigid. Instead of overhauling policies blindly, use this evidence to make targeted adjustments that reflect how teams actually operate.<\/p>\n<h3 id=\"adapting-to-new-data-sources-and-regulations\" tabindex=\"-1\">Adapting to New Data Sources and Regulations<\/h3>\n<p>Significant changes &#8211; like new fund structures, reporting requirements, or compliance updates (e.g., FATCA or CRS) &#8211; should trigger immediate reviews. Don\u2019t rely solely on calendar-based reminders. For example, when integrating a new data source, map its lineage right away. This gives you a clear view of how it connects to downstream reports and what might break if changes occur. For firms like Charter Group Fund Administration (<a href=\"https:\/\/chartergroupadmin.com\" style=\"display: inline;\">chartergroupadmin.com<\/a>), this kind of end-to-end visibility is vital, especially when managing complex offshore fund structures across multiple jurisdictions.<\/p>\n<p>To gauge progress, use a governance maturity model. Many organizations start at Level 0 (ad hoc processes with no shared definitions) and aim for Level 2 (automated checks on critical datasets) within their first couple of years. Benchmarking against these levels helps leadership understand where the program stands and what resources are needed to advance. This step-by-step improvement process ensures your governance strategy stays effective and ready for future challenges.<\/p>\n<h2 id=\"conclusion-building-a-reliable-data-governance-framework\" tabindex=\"-1\" class=\"sb h2-sbb-cls\">Conclusion: Building a Reliable Data Governance Framework<\/h2>\n<p>A solid data governance framework is critical. Without it, <strong>data quality deteriorates by 2\u20133% each month<\/strong>, and over time, this decline undermines the accuracy of reports, decisions, and audits your team depends on. The 10 steps outlined in this guide offer a practical approach &#8211; from defining the scope and assigning responsibilities to ongoing refinement &#8211; ensuring that data degradation doesn\u2019t take hold.<\/p>\n<p>These steps follow a logical progression: setting clear boundaries, fostering accountability, implementing consistent processes, and maintaining adaptability as your data environment evolves.<\/p>\n<p>The impact of this approach extends beyond operational improvements &#8211; it translates into measurable gains. Companies with mature governance programs often see a <strong>5x return on investment<\/strong>, while top finance teams spend <strong>30% less time reconciling data<\/strong> thanks to better upstream data quality. For fund administrators juggling intricate reporting requirements &#8211; like AML, CRS, FATCA, and investor disclosures &#8211; this level of efficiency isn\u2019t just helpful; it\u2019s a strategic advantage.<\/p>\n<p>The importance of this advantage is echoed by industry leaders:<\/p>\n<blockquote>\n<p>&quot;Data governance is no longer just a risk management exercise. It is a competitive advantage.&quot; &#8211; Shivam Rawat, Digital Marketing Team Lead, Algoscale <\/p>\n<\/blockquote>\n<p>Take Charter Group Fund Administration (<a href=\"https:\/\/chartergroupadmin.com\" style=\"display: inline;\">chartergroupadmin.com<\/a>) as an example. Operating across offshore jurisdictions with layered compliance demands, they rely on a robust governance framework to transition from reactive problem-solving to proactive, audit-ready systems. This allows them to meet evolving compliance standards with confidence. By starting with clear ownership and committing to ongoing improvements, the framework you establish today becomes the foundation for faster, more reliable decisions in the future.<\/p>\n<h2 id=\"faqs\" tabindex=\"-1\" class=\"sb h2-sbb-cls\">FAQs<\/h2>\n<h3 id=\"where-should-we-start-with-data-governance-in-fund-administration\" tabindex=\"-1\" data-faq-q>Where should we start with data governance in fund administration?<\/h3>\n<p>A strong approach to data governance in fund administration starts with focusing on the <strong>entire investment lifecycle<\/strong>. This means ensuring that every stage &#8211; from fundraising to investor management and fund administration &#8211; is supported by integrated technology that keeps governance front and center.<\/p>\n<p>Beyond that, making practical, focused improvements tailored to fund data governance can go a long way. These targeted changes not only help solidify your governance framework but also boost overall operational efficiency.<\/p>\n<h3 id=\"which-roles-are-needed-to-make-data-governance-work\" tabindex=\"-1\" data-faq-q>Which roles are needed to make data governance work?<\/h3>\n<p>To make data governance work, you need the right people in the right roles. Here\u2019s a breakdown of the key players:<\/p>\n<ul>\n<li><strong>Governance Council<\/strong>: This group sets the overall strategy and keeps an eye on all governance initiatives to ensure everything stays on track.<\/li>\n<li><strong>Data Owners<\/strong>: They\u2019re responsible for maintaining accountability, ensuring data quality, and making sure compliance requirements are met.<\/li>\n<li><strong>Data Stewards<\/strong>: These are the hands-on folks who handle day-to-day tasks, enforce policies, and make sure data quality standards are upheld.<\/li>\n<li><strong>Data Custodians<\/strong>: They focus on the technical side, managing infrastructure and implementing governance measures.<\/li>\n<\/ul>\n<p>Each role has a specific focus, creating a system where responsibilities are clear, and data governance can run smoothly.<\/p>\n<h3 id=\"how-do-we-measure-whether-data-governance-is-working\" tabindex=\"-1\" data-faq-q>How do we measure whether data governance is working?<\/h3>\n<p>To gauge how well data governance is working, organizations should focus on outcomes such as <strong>data quality<\/strong>, <strong>policy compliance<\/strong>, <strong>stakeholder trust<\/strong>, and the <strong>accuracy of decisions based on data<\/strong>. Key signs of success include:<\/p>\n<ul>\n<li>Better reliability of data<\/li>\n<li>Lower risks related to data management<\/li>\n<li>Alignment of data practices with overall business objectives<\/li>\n<\/ul>\n<p>Regularly tracking performance metrics and performing compliance audits are essential steps. These practices ensure that data governance not only supports informed, strategic decisions but also strengthens trust in the organization&#8217;s data.<\/p>\n<h2>Related Blog Posts<\/h2>\n<ul>\n<li><a href=\"\/index.php\/top-6-compliance-challenges-for-offshore-hedge-funds\/\" style=\"display: inline;\">Top 6 Compliance Challenges for Offshore Hedge Funds<\/a><\/li>\n<li><a href=\"\/index.php\/how-to-choose-a-fund-administrator-5-step-decision-guide\/\" style=\"display: inline;\">How to Choose a Fund Administrator: 5-Step Decision Guide<\/a><\/li>\n<li><a href=\"\/index.php\/7-key-fund-administration-metrics-every-manager-should-track\/\" style=\"display: inline;\">7 Key Fund Administration Metrics Every Manager Should Track<\/a><\/li>\n<li><a href=\"\/index.php\/5-steps-to-ensure-accurate-investor-reports\/\" style=\"display: inline;\">5 Steps to Ensure Accurate Investor Reports<\/a><\/li>\n<\/ul>\n<p><script async type=\"text\/javascript\" src=\"https:\/\/app.seobotai.com\/banner\/banner.js?id=6a0a5c4d800645b46e62da0f\"><\/script><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Practical 10-step guide to build a fund administration data governance framework\u2014scope, roles, policies, controls, tools, monitoring, and improvement.<\/p>\n","protected":false},"author":2,"featured_media":11141,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[],"tags":[],"class_list":["post-11142","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.8 - 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