Data Alone Isn’t Enough: The Next Stage of AI Readiness

Earlier in this series, we discussed why “having good data” is one of the most important first steps in any artificial intelligence strategy. Clean, accurate, and organized information creates the foundation AI systems rely on to generate meaningful insights and support better decision-making.

However, data quality is only one piece of the equation. For Family Offices and wealth management organizations, AI success also depends on the infrastructure, governance, integrations, and operational processes surrounding that data. Even strong datasets can create challenges when information is fragmented across systems, managed inconsistently, or difficult to access in real time.

The next stage of AI readiness is about creating an environment where data can move efficiently, securely, and intelligently across the organization. In this article, we’ll explore what that looks like in practice and why operational readiness is becoming just as important as data quality itself.

Phase 1: Data Governance and Stewardship

Effective data management requires clear governance structures that define roles, responsibilities, and decision-making authority. Who owns the data? Who is responsible for data quality and integrity? Who approves sensitive data access requests? Who sets data retention policies? Clear answers to these questions are essential.

In family offices, governance is further complicated by the involvement of multiple stakeholders: family members, investment staff, external advisors, and service providers, each of whom may have different views on data priorities, privacy requirements, and acceptable uses. Establishing and maintaining consensus requires active governance mechanisms.

For AI specifically, governance policies must address additional questions: What data can be used for model training? How should models be validated before deployment? What level of human oversight is required for AI-generated recommendations? How are model decisions documented and explained? Who can deploy new AI capabilities?

Governance must also extend to third-party service providers. How are they using your data? What safeguards are they maintaining, particularly for the most sensitive information?

Phase 2: Foundation Building

Before deploying sophisticated AI capabilities, family offices must establish solid data foundations. This phase focuses on four priorities:

• Comprehensive data inventory. Catalog all data sources, document their contents and update frequencies, identify gaps and quality issues, and map data flows between systems. This baseline understanding clarifies what data resources exist and where improvement is needed.
• Data consolidation. Deploy a data lake or similar solution to create a unified view of family office assets and eliminate siloed information.
• Data quality processes. Implement validation rules, exception reporting, and correction workflows. Define data ownership and accountability. Establish metrics for measuring quality and track improvements over time.
• Data catalogs. As data ecosystems grow in complexity, the ability to find and understand available data becomes critical. Data catalogs inventory available datasets, document their contents and lineage, and facilitate discovery. For AI implementations, they help data scientists identify relevant datasets, support model debugging, and facilitate impact analysis when data sources change. Maintaining comprehensive data catalogs, however, requires dedicated effort and appropriate tooling.
  
  

Phase 3: Targeted AI Pilots

With foundational data infrastructure in place, family offices can begin experimenting with AI through targeted pilot projects. Pilots serve multiple purposes: demonstrating value, building internal expertise, uncovering unforeseen challenges, and refining implementation approaches.

Successful pilots share common characteristics. They address well-defined problems with measurable outcomes, leverage data that is already relatively clean and accessible, have executive sponsorship and appropriate resources, and include mechanisms for capturing lessons learned.

Example pilot projects might include:

• Portfolio rebalancing optimization using machine learning to minimize tax impact
• Document processing automation for extracting data from fund statements or K-1 tax forms
• Anomaly detection for identifying unusual transactions or market movements
• Natural language processing for analyzing investment research reports or earnings call transcripts
  
  

Phase 4: Scaling and Integration

Successful pilots provide the foundation for broader AI adoption. The scaling phase focuses on expanding AI capabilities across additional use cases, integrating AI insights into decision-making workflows, and building organizational muscle memory for maintaining and improving AI systems.

This phase requires balancing expansion with sustainability. Adding new AI capabilities without corresponding investments in data infrastructure, governance, and talent can produce poor results. Successful scaling requires disciplined program management, continued focus on data quality, and ongoing capability development.

Best Practices and Recommendations

Start with Data, Not Algorithms

The allure of sophisticated AI models can tempt organizations to prematurely focus on algorithm selection and model development. Resist this temptation. No algorithm, however advanced, can compensate for poor-quality or inaccessible data. Invest first in data infrastructure, quality, and governance, including the unglamorous but essential work of data cleaning, standardization, and consolidation.

Embrace Incremental Progress

Transformative AI capabilities are built incrementally, not through sweeping all-at-once implementations. Start with focused projects that deliver tangible value quickly, use early wins to build momentum and secure resources, and iterate based on experience. This approach reduces risk, facilitates learning, and maintains stakeholder engagement.

Build Privacy and Security In

Security and privacy cannot be afterthoughts. Design data architectures with privacy preservation from the outset. Implement encryption, access controls, and audit logging while consistently evaluating outside vendors rigorously on their security practices.

Develop Governance and Internal Capabilities

Establish a clear governance structure and processes early. Invest in internal capabilities through hiring, training, and hands-on experience. Even small family offices can cultivate basic data literacy and AI fluency among existing staff; internal expertise enables more effective vendor management and supports long-term sustainability.

Measure and Monitor

Establish metrics for evaluating AI initiatives. Track data quality indicators, model performance, user adoption rates, and business impact. Regular monitoring surfaces issues early, supports continuous improvement, and demonstrates value to stakeholders. What gets measured gets managed, and that principle extends to third-party providers as well.

Build vs. Buy

Organizations must determine the right approach to their data management challenges. Building internal capabilities offers control and customization but requires significant investment. Purchasing packaged solutions from third-party providers can enable faster, more cost-effective deployment but may sacrifice flexibility. A hybrid approach, combining in-house capabilities with external service providers, potentially guided by consultants or advisors, is another viable path. The right choice depends on organizational size, available resources, and technology sophistication.

How Archway Can Help

The data challenges described in this post are precisely the problems the Archway Platform was designed to solve. For nearly 25 years, Archway has helped family offices and financial institutions aggregate, consolidate, standardize, and manage their key financial data and documents.

The Archway Platform addresses core data readiness challenges in several ways:

• Consolidated data in a single environment. The platform brings together accounting and investment data across custodians, asset classes, and currencies, eliminating the fragmented, multi-silo environments. With a single, reconciled source of financial truth, AI tools have the clean, comprehensive dataset they need to function effectively.
• Structured, auditable financial data. Archway's foundational general ledger automatically books journal entries as transactions are processed, producing well-labeled, consistently formatted data as a natural byproduct of normal operations, exactly what AI systems require.
• Alternative investment data ingestion. Through ingestion tools and partnerships with companies like Canoe Intelligence and Arch, the platform streamlines the extraction and processing of alternative investment data. Capital calls, distribution notices, K-1s, and fund statements are among the most persistent data gaps for family offices seeking AI-ready data, and they are handled more efficiently within the platform.
• Built for complexity and scale. The platform is designed for the unique demands of UHNW family offices, including multi-entity structures, multi-generational ownership, and multi-asset portfolios. As data needs grow, the platform scales with them.

For family offices looking to build the data foundation that makes AI possible, Archway provides both the technology and operational support to get there.

Artificial Intelligence will reshape wealth management, but the firms that benefit most will be those building to enable it. That means investing in the data infrastructure, governance, and processes outlined throughout this series, not just pursuing AI on its own.

The question is not whether AI will transform the industry. It will. The more important question is which organizations will be ready to harness it effectively.

In a previous post, Catherine Fankhauser, Partner and Practice Leader of Family Office Advisory Services at Ernst & Young (EY), joined our CEO, Anthony Abenante, to outline five steps Family Offices should take when starting an AI journey. "Having good data" topped the list. In this post, I want to go deeper on what that means in practice.

AI Demands Better Data

Artificial intelligence represents more than an incremental technology upgrade, it offers a fundamental transformation in how family offices can operate. Advanced AI systems promise capabilities that were once the stuff of science fiction: real-time portfolio optimization across all asset classes, predictive analytics for market movements and liquidity needs, automated compliance monitoring, intelligent tax optimization, and natural language interfaces for complex financial queries, analysis, and reporting.

These capabilities, however, are built on a foundation of quality data. Unlike traditional software that can function on partial or inconsistent inputs, AI systems depend fundamentally on comprehensive, well-structured, and properly labeled datasets. The AI readiness gap facing family offices is therefore not primarily about AI technology itself -- it is about the underlying data infrastructure required to make AI effective.

The Data Challenges Facing Family Offices are Unique

Family offices differ from other financial organizations in four critical ways, and understanding these differences is essential to addressing their data challenges:

• Diverse asset portfolios. Family offices manage holdings that extend well beyond public securities to include private equity, real estate, hedge funds, collectibles, family businesses, and other alternative investments. Each asset class generates different types of data with varying levels of reporting frequency, standardization, and transparency.
• Multiple external service providers. Family offices typically work with custodians, prime brokers, fund administrators, tax advisors, and legal counsel, each maintaining separate data systems with different formats and update frequencies. This creates a naturally fragmented data environment where consolidation is a persistent challenge.
• Sensitive family information. Beyond financial assets, family offices manage estate plans, philanthropic activities, and personal data that require strict confidentiality. These privacy requirements can conflict with the data aggregation and sharing mechanisms that AI systems typically rely on.
• Wide variation in size and sophistication. Many single-family offices operate with lean teams and limited technology resources, making large-scale data initiatives especially challenging.

Fragmentation: The Core Data Problem

The most pervasive data challenge facing family offices is fragmentation. Investment holdings data are frequently dispersed across an array of disconnected systems, creating several problems for AI implementation. Machine learning algorithms require integrated datasets to identify patterns and generate insights and when data resides in isolated silos, AI systems lose the holistic view essential for meaningful analysis.

Data silos also increase the risk of inconsistency and duplication. The same investment may be recorded differently across systems, which confuses AI models and can lead to erroneous conclusions.

The Multi-Custodian Problem

Many family offices maintain relationships with multiple custodians to access specialized services, manage counterparty risk, or accommodate the preferences of individual family members. While this diversification offers operational benefits, it significantly complicates data management.

Historical Data Gaps

AI and machine learning models typically require substantial historical data to train effectively and identify meaningful patterns. Family offices may have years of investment history, but accessing that data in structured, usable formats is often difficult. Legacy systems may have been replaced, historical records may exist only on paper or in PDFs, and data standards may have shifted over time.

Even when historical data exists electronically, it may rely on outdated categorizations or lack key fields needed for modern analysis. Without adequate historical data, AI models cannot perform back-testing or learn from past market cycles.

Privacy Requirements

Family offices manage highly sensitive information that extends well beyond financial data to include personal family matters, health information, estate plans, philanthropic intentions, and business strategies. Protecting this information can limit or complicate access to certain datasets needed for AI implementation.

Family Offices Must Evolve

Many family offices rely on legacy technology systems that were never designed with AI integration in mind. These systems may lack modern APIs (Application Programming Interfaces) or data export capabilities that AI tools require.

The rapid evolution of AI also means that a leadership team's expertise can quickly become outdated. Continuous learning is essential. Family office staff need opportunities to develop new skills, experiment with emerging technologies, and stay current with industry developments, which requires investment in training, professional development, conference attendance, and collaboration with academic institutions or industry groups. Organizations that cultivate a learning culture -- one where experimentation is encouraged and failure is tolerated -- are better positioned to adapt to technological change.

Finally, family offices are not static entities, and data infrastructure must accommodate growth without requiring constant re-architecture. An AI platform that performs well with $500 million in assets across 50 positions may struggle when a portfolio grows to $2 billion across hundreds or thousands of positions spanning multiple asset classes and jurisdictions. Scalability must be a design priority from the outset.

Preparing for What’s Next

AI has the potential to reshape how family offices operate, but meaningful results depend on the strength of the data foundation beneath it. For many organizations, the challenge is not a lack of information, but fragmented systems, inconsistent reporting, and operational complexity that limit visibility and scalability. As portfolios expand across asset classes, entities, custodians, and jurisdictions, these challenges only intensify, increasing the need for structured, integrated, and reliable data.

In Part 2, we’ll explore what it takes to move forward in practice, including how to strengthen data strategy and align the right operating model. Effective AI starts with disciplined accounting and a clear operational foundation. At Archway, we combine purpose-built technology with deep accounting expertise to help family offices bring structure and consistency to increasingly complex environments.

In a recent post, we outlined five focus areas for starting an AI journey, with Get Educated as the essential first step. Given the enormous amount of buzz and hype surrounding AI, we wanted to point you toward sources that go beyond the headlines and offer substantive, fact-based information and perspectives.

Below is a curated list of educational resources for Family Offices looking to build their AI knowledge. We start with our top recommendations: MIT, Stanford, and Harvard, three institutions at the forefront of AI research and among the most authoritative sources for insights on artificial intelligence trends and developments. Leading AI platforms OpenAI and Claude also offer helpful educational content. For current news and developments, Forbes and Wired are solid starting points. We've also included online courses for those seeking deeper immersion, a selection of books offering both accessible and in-depth perspectives, and research from several leading consulting firms.

Top Recommendations

• MIT Technology Review – No hype; written by practitioners. technologyreview.com | MIT AI News
• Stanford AI Index Report – hai.stanford.edu/ai-index
• Stanford Digital Economy Lab – digitaleconomy.stanford.edu
• OpenAI – Leading AI platform; research, tools, and product updates (ChatGPT). openai.com
• Claude – Leading AI platform; research, tools, and product updates. claude.ai
• The Batch (DeepLearning.AI) – Explains what matters in AI. deeplearning.ai/thebatch
• Harvard Business Review – AI case studies. hbr.org
• Artificial Intelligence News – Trends and real-world applications. artificialintelligence-news.com
• Forbes AI – forbes.com/ai
• Wired – Artificial Intelligence – AI use cases and analysis. wired.com/tag/artificial-intelligence

Educational Courses ‍

• Coursera – AI courses and specializations from Stanford and DeepLearning.AI, including Andrew Ng's "Machine Learning" and "AI for Everyone." coursera.org
• edX – Courses from MIT, Harvard, Microsoft, and others, covering foundational to advanced AI topics. edx.org
• Udacity – Nanodegree programs in AI, Machine Learning, Deep Learning, and more, with a hands-on project focus. udacity.com
• Udemy – A wide range of AI courses for all levels, with practical, real-world applications. udemy.com
• DataCamp – Specializes in data science and AI through interactive coding tutorials and projects. datacamp.com
• Google AI – Free tutorials, resources, and hands-on labs via the "Learn with Google AI" portal. ai.google

Books and Reading Material‍

• You Look Like a Thing and I Love You by Janelle Shane – Funny and accessible; a great introduction to how AI actually works.
• The Second Machine Age by Andrew McAfee and Erik Brynjolfsson – Written for a general audience; no technical background required.
• AI Superpowers by Kai-Fu Lee – Examines the real-world impact of AI across industries and geographies.
• Artificial Intelligence: A Modern Approach by Stuart Russell and Peter Norvig – The definitive AI textbook.
• Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville – A comprehensive guide to deep learning techniques.
• Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow by Aurélien Géron – Practical projects and clear explanations for building AI applications.

Consulting Firms

• McKinsey – State of AI report. mckinsey.com
• Boston Consulting Group – AI insights and research. bcg.com
• EY – Family enterprise and family office perspectives. ey.com
• Campden Wealth – Research focused on family offices and wealth. campdenwealth.com
• Family Office Exchange (FOX) – A leading association for family offices; sponsors peer research and education on technology issues. familyoffice.com

This list is by no means exhaustive, but we've aimed to highlight some of the most respected and accessible sources available — a solid starting point with a range of options to suit different learning styles and goals. We believe now is the time for family office leaders to begin their AI journey and, as we said in our earlier post, take the AI plunge. Have fun, and good luck; we're always here to help.

David O'Kane, Head of Product, Archway

Below is a recap of the keynote fireside chat from Archway's Immersion Lite Conference in Dallas, presented from the perspective of Archway’s CEO, Anthony Abenante.

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Family Offices & Artificial Intelligence: Getting Started

I recently had the opportunity to sit down with Catherine Fankhauser, Partner and Practice Leader, Family Office Advisory Services at Ernst & Young (EY), where she shared her insight on Family Offices and how they are approaching the utilization of Artificial Intelligence (AI). She brought a well-informed perspective given that she spends 100% of her time with Single Family Offices (SFOs) in areas including operations, governance, and risk.

As we began our conversation, there was clear agreement that AI represented lots of things to lots of people; discussion and debate is clearly ubiquitous at this point, both professionally and personally. As EY works with a broad swath of Family Offices, I asked Catherine to provide insight into how they’re collectively thinking about the implications of AI adoption for their operations. In effect, what's driving both their motivation to adopt AI as well as their fear of its implications?

Further, a growing – and now prevailing – swath of their clients is fully aware that they can no longer ignore AI but just don’t know how to get started. It's as if people are lined up with their toes at the edge of a swimming pool, looking to see which of their friends have jumped in. They’re seeing other organizations in their ecosystem -- like banks and investment firms -- getting in said pool. And as a result, they ask: should we get in the AI pool as well? She thought many are waiting for that first real use case representing a tangible reason to take the plunge. In many ways, her swimming pool analogy was a perfect way to summarize current state.

And, at the same time as they are standing by that AI pool, we see these Family Office leaders reading about the vast amounts of money pouring into projected required infrastructure to facilitate LLMs by the likes of Alphabet, Meta, and Microsoft. So instead of asking how cold the water is, they should be asking how and/or where to commence their respective AI journeys. What should they be thinking about in a practical way, as to not get stuck in a sinkhole of discovery while overspending and ending up with intangible results

Given all the above, the natural next question to pose was around how people should think about getting started?

What follows are Catherine’s suggested five areas of focus for initiating an AI journey…

1. Get Educated‍

When people talk about AI, they employ a uniquely different and growing vernacular. Get educated on the types of AI, its componentry and its terms. To be clear, not all these terms are interchangeable: Robotic Process Automation is not machine learning; Large Language models (LLMs) are not agentic AI. Simply put, it’s imperative to get educated.

Further to that point, I made reference to a growing set of great sources of AI information available and that Archway plans on subsequent posts highlighting many of these resources as we all collectively learn, develop, and share better AI deployment and utilization practices. Stay tuned.

2. Have Good Data‍

Catherine stressed that AI capabilities and functionality are only going to be as good as the data it is processing. Bad data = bad output, rendering AI utilization of no use. She gave the example of an EY client Family Office where the client was having a horrendous time with wash sales and preparing tax returns. EY has an AI tool to analyze all your different accounts and come up with your wash sales. Unfortunately, the Family Office couldn't make use of the tool because they couldn't generate the data to feed it. We both agreed that now is time to start getting your data organized into modernized data storage structure(s) housed in a repository where you can aggregate all your data sources.

3. Access Control‍

When thinking about access control, I typically conjure images of keeping the humans away from technology. This is not what Catherine meant. She was saying, conversely, to keep the technology away from the humans (and their sensitive data and information…). AI does not discriminate. It will take everything -- including highly sensitive data -- and use that information to train itself. Organizations need to think about how they are going to put a fence around the AI while being judicious around what data to feed it. Catherine stressed the need to perform curative work around properly ringfencing and/or deleting data that shouldn’t be consumed by an LLM. This work is just one of the many steps around forward AI governance that will need to be developed, evolved and continuously applied with unfailing rigor.

4. Privacy Policy‍

Catherine added that Family Offices need to think about the other aspects of managing their data, aside from Access Control. They need to determine what data is off limits: How long should it be kept? Who has access to the data? Do we have a retention policy? What is our privacy policy? She suggested that once you come up with those parameters, memorialize them and make sure they are clearly understood.

In addition to internal data, think about the data your venders have access to as well: What information do our lawyers, accountants, and other service providers have about our organization? Do we want them to have it if they are using AI? Do we want our information training their models? These third parties need to be part of your privacy footprint.

5. Governance

This topic might be the most important area in which we spend significant time thinking about here at Archway. How best to implement and manage AI usage & deployment in your organization? Who should be the architects of your AI policy and in what form should they be structured: cross-functional team members in committee form or do you stand up a board of governance? It can -- and should -- also be manifest in a set of guidelines that everyone agrees to abide by. Catherine said to think of governance as the guardrails and controls for implementing AI throughout your complex. It determines who decides why and where AI is used, what data will be available to the language models, and who has access to results. It can also assess risks and determine if the AI capability is delivering on promised functionality. As our clients consider this question, we continue to manage Archway’s AI discovery and deployment journey with these nuanced decisions in mind.

In conclusion, we’re very grateful to Catherine for taking the time to share her insights with us. I found her five-step plan to be an insightful and effective guide for helping to frame one’s thinking around getting started with their respective AI journey. Here’s to hoping that this will help more people take the plunge and get into the pool.

Anthony Abenante | CEO Archway Group

Why Financial Institutions and Family Offices Are Adopting Outsourced Accounting and Investment Reporting Solutions to Serve Their Ultra High-Net-Worth Clients.

In some corners of the private wealth management world, the word outsourcing, sometimes referred to as business process outsourcing (BPO), has become taboo. Oftentimes considered synonymous with offshoring, outsourcing has erroneously been painted as cheap work performed by unskilled labor.

But it only takes a bit of due diligence to find that these negative connotations are often an inaccurate portrayal of the true value of an outsourced service offering.

To that end, like other outsourced service providers to family offices and financial institutions, Archway is frequently faced with questions about our people, our processes and our technology and, ultimately, why outsourcing may be the right solution.

To help answer this question, here are 10 reasons private wealth managers are leaning into outsourced services.

1. They enable you to grow, quickly.

A new advisor joins your firm and brings a dozen new clients into the firm. Is your team prepared to absorb the account aggregation and report preparation responsibilities that will soon follow?

When you’re in high growth mode, the last thing you want to do is realize your team is not equipped to scale. An outsourced service provider like Archway can help financial institutions and family offices smoothly onboard new clients or households, so that wealth managers can focus on helping their clients achieve their wealth goals.

2. They can enhance your quality of service.

Enhanced service quality tops the list and it’s quite a simple notion.

Instead of spending time normalizing data, performing consolidations, paying bills or preparing and reviewing report packages, private wealth managers can focus on their passion: serving their clients and delivering results that build client wealth.

3. They provide business continuity in the event of disaster or significant change.

We’ve learned some tough lessons throughout the pandemic, but one that stands out for businesses is strengthening their ability to overcome disruption. Whether you’re trying to minimize the effects of a health crisis, employee departures or just a simple power outage, having a dependable outsourced service partner helps ensure that you can continue to meet the demands and expectations of your clients despite forces beyond your control.

4. They offer workforce stability in the face of employee turnover.

Key person risk is one of the chief concerns amongst family offices and financial institutions. If an employee departs or a position needs to be eliminated, how do you ensure that your operations don’t falter?

From our vantage point, outsourced service providers should operate as a seamless extension of your internal team. Using operational documentation, thorough communication and repeatable processes, an outsourced service team can quickly take on additional responsibilities in the absence of key personnel.

5. They are built on operational expertise.

There’s an adage that says, “You can be great at one thing or good at many.” We believe that you should always strive for greatness, which may mean leveraging third-party resources to perform key tasks that sit outside of your expertise or aren’t a valuable use of your time.

By partnering with an experienced BPO team, you will be able to work with subject matter experts and highly-skilled operations professionals that are solely focused on a single function. Examples of commonly outsourced activities include portfolio reconciliation and consolidated investment reporting, personal expense management, tax preparation, partnership administration, legal services, and trust administration.

6. They help you manage risk.

In some cases, particularly amongst private banks and other financial institutions, there may be compliance requirements related to particular service offerings that necessitate the need for third-party oversight. This oftentimes translates to creating a business relationship with an outsourced service provider.

Financial institutions and family offices can further manage their risk exposure by establishing service-level agreements (SLAs) with outsourced service providers that help define the who, what and when of service delivery.

7. They allow you to customize your solutions offering.

We’ve all watched this scene play out before: you’re courting a new client who presents a unique set of wealth management demands and you need to spin up a new solution offering quickly. It can be an anxiety-inducing situation if you don’t already know what’s out there.

On the other hand, if your financial institution or family office has a pre-established relationship with an outsourced service partner, it’s much easier to explore other available services and expand your relationship on an as-needed basis. Additionally, you can craft tiered service offerings that span the range of your clientele to ensure you’re delivering the right solutions to the right clients.

8. They provide efficiencies in your back office.

Most outsourced services focus on one of two areas: highly repetitive processes or highly specialized processes. The common thread between these two areas is that they both require a significant amount of time to complete.

By allowing an outsourced service team to absorb click-heavy, recurring operations like portfolio reconciliation, or time-consuming, tedious operations like family office partnership accounting, your staff can focus on doing what they do best and not worry about the monotony of data.

9. They can offer access to purpose-built technology.

While some envision BPO firms as shops filled with endless rows of desks and people, the reality is that most outsourced service organizations rely on a key tool to help drive efficiency: specialized technology.

At Archway, our BPO teams use our proprietary family office software, the Archway Platform℠, to perform the nuanced operations that exist within family offices and financial institutions serving high-net-worth clients.

Then, using the Archway Client Portal, we can securely deliver the processed and formatted data to family office professionals, advisors and their end-clients in an intuitive, easy-to-use platform. This gives them the opportunity to engage with their financial information in an interactive, tech-forward way that may not exist if the family office was exclusively responsible for designing and developing the end-client reporting experience.

10. They can reduce your firm’s overhead costs.

Maintaining technology can be expensive, especially if you are the designer, developer, quality assurer and information systems architect.

An outsourced service partner alleviates the need to maintain the technology and the servers that run it, which can ultimately reduce your overhead IT costs. As both an experienced technology firm and an award-winning outsourcing provider, our services include hosting and server maintenance, data backup and disaster recovery, ongoing technology enhancements, software quality assurance, data collection and normalization, system connectivity troubleshooting, and product documentation and training.

We know that outsourcing doesn’t always receive the recognition and appreciation it deserves, but the benefits of partnering with an outsourced service provider are demonstrated to be plentiful for private wealth management firms.

Whether you are seeking to ease the burden of client reporting, add new concierge services like client bill payment or offload the complex process of private fund bookkeeping and reporting, Archway is prepared to work and grow alongside your firm.

Check out our full suite of technology and outsourced service solutions for family offices and financial institutions to find out how we can help you better serve your high-net-worth clients.

Archway and Canoe Forge Path to Further Advance Alts Data Management for Family Offices Using the Archway Platform

Since 2020, collaboration and a desire to solve complex financial problems have been at the core of Archway and Canoe Intelligence’s strategic partnership. Throughout the years, Archway’s experience working with nearly 600 ultra-high-net-worth families through the Archway Platform has made them acutely familiar with the challenges family offices face when it comes to collecting and reporting on alternative investment data.

Coupled with Canoe’s innovation and vision in the alts technology space, where the Canoe platform covers 42,000 active funds across $8T in Assets Under Management or Advisement for its 325 alternative investor clients, our teams knew early on there was an immense opportunity to streamline alternative investment data management within the family office space.

Recently, the two teams have been working on the next iteration of our partnership as we develop a more robust integration between the Canoe and Archway platforms.

This integration between Canoe and Archway automates the transmission of private equity and hedge fund valuations, as well as Private Equity Call and Distribution data. Moreover, Hedge Fund subscriptions and redemptions extracted from Canoe can be effortlessly imported into Archway.

In this article, we share how the two technologies are teaming up to test and build this expanded integration—and how we believe it can level up the operational efficiency for our mutual family office clients.

Common Challenges in Alts Data Management

Alternative investors, particularly family offices, navigate a complex landscape fraught with challenges when it comes to managing alts data. Among these challenges are data silos, where crucial information is scattered across multiple systems and platforms, making it difficult to obtain a comprehensive view of investments. Additionally, the reliance on manual data entry introduces a significant risk of human error and inefficiency, consuming valuable time and resources.

Compounding these issues is the lack of standardized data formats, further complicating the integration and analysis of disparate data sources.

In response to these challenges, Archway Family Office Services and Canoe Intelligence are expanding their strategic partnership and integration methods. By automating data transmission and ensuring data consistency, the integration streamlines the process of accessing and integrating alts data. This not only enhances operational efficiency but also mitigates the risk of errors, empowering family offices to make informed decisions with confidence.

How Canoe Enhances Archway’s Platform

• Automated Fund and Allocation-Level Data Extraction: Canoe's integration with the Archway Platform facilitates automated extraction, validation, and delivery of fund and allocation-level data.
• Pricing Updates: Canoe seamlessly updates pricing information in Archway, providing alternative investment valuation data extracted as soon as received and processed.
• Effortless Management of Capital Calls and Distributions: Canoe automates the process of updating Archway with capital call and distribution transactions.
• Streamlined Subscription and Redemption Transactions: Canoe generates extracts of subscription or redemption transactions, which can be uploaded directly to Archway.

Archway’s Platform at a Glance

Archway's Platform serves as a comprehensive wealth management technology solution tailored specifically for family offices. With Archway, family offices gain access to a wide range of benefits, including a 360-degree view of clients' wealth, enhanced operational efficiency, improved data accuracy and reliability, and robust operational and client reporting.

Bringing the Integration to Life

Prior to launching beta testing for the integration in late 2023, the Archway and Canoe teams worked in concert to automate data flows, normalize values, and define accounting rules and transaction mapping across systems.

The teams collaborated on extensive internal testing to validate the effectiveness and reliability of the integration, with the intent to not only automate the transmission of alternative asset data between platforms, but to simplify the complex nature of accounting for alternative investment transactions.

Through rigorous analysis and learning, the team identified and addressed potential challenges, fine-tuning the integration to meet the unique needs and requirements of family offices.

Now in its beta testing phase, the team continues to collect invaluable real-world perspectives, helping to guide iterative improvements and ensuring alignment with client expectations.

To date, Canoe has processed 150,000+ documents on behalf of Archway’s clients. Additionally, this collaborative effort has positioned two dozen mutual clients to automate the transmission of data across 3,400+ alternative investments, underscoring the substantial impact of the integration on operational efficiency and data management accuracy.

What's Coming Next

Looking ahead, Archway and Canoe are finalizing the initial integration offering with plans to expand the universe of data available to mutual clients seeking to automate the transmission of their alternative asset data. This next phase promises to unlock new levels of efficiency and value for family offices leveraging the combined power of the Archway’s Platform and Canoe Intelligence.

As Archway continues to leverage Canoe's capabilities, clients can expect further enhancements that drive continued scale and elevate client satisfaction. With a commitment to innovation and excellence, Archway and Canoe are poised to shape the future of alts data management. Stay tuned for more updates as the integration nears launch later this year.

Disclaimer: All statistics as of March 31, 2024.

Originally published by Canoe Intelligence.