In the era of digital transformation, analytics has become central to modern wealth management, but better decisions don’t start with more dashboards or models.
They start with data you can trust as the foundation layer.
For many advisors and portfolio managers, that might sound odd. However, in practice, it is surprisingly difficult to achieve. Data arrives from multiple custodians, systems interpret it in different ways, and teams often find themselves spending more time reconciling numbers than analyzing portfolios.
In the first episode of our From Data to Decisions series, Dennis Hagander, Sales Director at WealthArc sits down with Stratos Mavrogiannis, Vice President of Aladdin Wealth Tech from BlackRock, to unpack a question that many wealth managers have asked themselves:
“How can I actually trust the information I’m making decisions on?”
Because when the numbers behind a portfolio are uncertain, every decision that follows becomes uncertain.
🎥 Watch Episode 1 embedded here:
Disclaimer: This content is for professional clients and qualified investors only. The views expressed are those of the speakers and do not constitute investment advice or a recommendation to buy or sell any financial instruments.
The hidden problem many wealth managers face
You prepare for a client review and notice that the portfolio numbers look slightly different depending on which system you open. The custodian data might not match the reporting platform. Performance calculations may vary depending on the source.
So the team starts digging.
Spreadsheets appear. Exports are downloaded. Mappings are checked. Numbers are reconciled.
By the time everything lines up, valuable hours have been spent verifying the data rather than interpreting it.
As Dennis explains in the conversation:
“Unconsolidated and inconsistent data across custodians forces wealth managers to spend time reconciling numbers in Excel instead of advising clients.”
It is rarely a dramatic failure. More often, it is a series of small inconsistencies that inadvertently slow down the investment process.
But over time, these inefficiencies add up hours of work that could be spent with clients.
Where portfolio data typically breaks down
Data problems rarely come from a single system.
They usually appear when data moves between systems.
In most wealth management firms, portfolio data flows through several layers:
- Custodian feeds
- Portfolio management systems
- Order management systems
- Reporting tools
- Analytics platforms
Each system is designed for a different purpose, so each one interprets the same data slightly differently.
Those interpretations introduce variation.
As Stratos explains during the discussion, this variation is inevitable to some extent. The real challenge is bringing these perspectives together into a consistent view of the portfolio.
When firms cannot do that automatically, manual work fills the gap.
Exports are created. Mapping tables are maintained. Validation checks are added. Excel becomes the unofficial reconciliation engine.
Not because people prefer spreadsheets, but because they need a way to maintain control.
The real impact on portfolio analysis
When data is inconsistent or incomplete, the first thing that suffers is portfolio analysis.
Stratos highlights a common pattern.
Wealth managers spend increasing amounts of time checking whether the data is correct before they can even begin analyzing the portfolio itself. That uncertainty erodes confidence in the numbers and, ultimately, in the insights derived from them.
The knock-on effect reaches client conversations as well.
If advisors are unsure whether the data is fully accurate, explaining portfolio behavior becomes more difficult.
This is why tools like BlackRock’s Portfolio 360 are designed to analyze normalized and structured portfolio data. When integrated with platforms like WealthArc, wealth managers can explore portfolio characteristics, risk exposures, performance drivers and stress scenarios with greater clarity.
But even the most sophisticated analytics tools rely on something fundamental.
Clean and accurate data.
What “trustworthy data” really means
The term trusted data is widely used across wealth management. But it can feel abstract.
During the discussion, Stratos describes three qualities that define trustworthy portfolio data.
Timely
The data must be current. If the numbers are outdated, the insights will be as well.
Reconciled
The data must be consistent across all custodians, systems, and reports.
Contextual
The numbers must be explainable. Advisors need to be able to understand why a portfolio looks the way it does, not just seeing figures.
When these three elements are present, wealth managers can clearly focus on interpretation rather than verification.
Why data trust changes behavior
There is also an emotional dimension to data quality that is often overlooked.
When portfolio managers trust their data, they approach decisions differently.
They become more decisive. They feel more comfortable explaining outcomes. Conversations with clients become clearer and more confident.
Stratos describes this shift simply:
“Trust in data translates into confidence in conversations with clients explaining portfolio outcomes.”
In other words, reliable data does not just improve analysis. It improves the entire advisory process.
The cultural shift inside investment teams
Once firms establish a strong data foundation, something interesting happens internally.
Meetings move from discussions around “Are these figures correct?” to “Which strategy is right?”. Teams stop troubleshooting data discrepancies and start focusing on portfolio construction, client outcomes, and growth.
At the same time, the amount of data wealth managers must analyze continues to grow. Global portfolios now involve multiple asset classes, currencies, exposures and macroeconomic factors.
The challenge is no longer accessing data.
It is turning complex data into actionable insight.
The compounding benefits of fixing data foundations
When wealth management firms successfully secure their data foundation, the benefits tend to spread across the organisation.
Stratos describes this as a compounding effect.
- Clean data leads to accurate reporting.
- Cleaner reporting enables stronger analytics.
- Better analytics lead to more confident portfolio managers.
- Confident managers have more effective conversations with their clients.
It is not one improvement, but a chain reaction.
Key takeaways for wealth managers
For wealth managers navigating increasingly complex portfolios, the conversation highlights an important principle: better analytics begins with better data foundations.
Portfolio analytics depends on reliable data
Even the most advanced analytics tools cannot produce meaningful insights if the underlying data is fragmented or inconsistent.
Data challenges affect any system
Problems typically affect any system if not accurate regardless if portfolio management system, reporting tools or analytics platforms just to name a few.
Trusted data should be timely, reconciled and contextual
Wealth managers need data that is current, consistent across systems and explainable in client conversations.
Data trust improves advisor confidence
When investment teams trust their data, they communicate more clearly with clients and make decisions with greater confidence.
Strong data foundations create compounding benefits
Cleaner data improves reporting, analytics, operational efficiency and client outcomes across the organisation.
Questions wealth managers should ask about their portfolio data
For many firms, data challenges emerge gradually and become part of the daily workflow.
These questions can help wealth managers assess whether their current infrastructure supports reliable decision-making.
How much time does our team spend reconciling data manually?
If portfolio managers regularly verify numbers before analysis begins, the underlying data layer may be fragmented.
Do portfolio figures match across reporting tools and analytics platforms?
Inconsistencies between systems often signal integration or interpretation issues.
How confident are advisors when explaining portfolio outcomes to clients?
If teams hesitate because they are unsure whether the data is fully aligned, trust in the data foundation may be weak.
Can our systems scale with increasing portfolio complexity?
As portfolios expand across asset classes and markets, manual reconciliation becomes harder to sustain.
Do we have a single source of truth for our investment data?
Without a centralized data layer, firms often rely on multiple interpretations of the same information.
Answering these questions honestly can reveal whether a firm’s data infrastructure supports modern wealth management workflows.
Build your trusted data foundation with WealthArc
In a world where wealth management data analytics is central to every strategic decision, your firm’s success depends on the quality and reliability of the data feed.
WealthArc’s technology is built to:
- Connect to any custodian and data providers globally
- Provide clean, normalized, and reconciled investment data
- Deliver a single trusted data layer that seamlessly integrates and interacts with platforms such as BlackRock Portfolio 360 or any other Portfolio Management System, AI WealthTech Application or LLM
If your firm wants to stop managing data and start using data to drive better decisions, we’d be happy to show you how this foundation can work in practice.
👉 Book a chat with the WealthArc team to explore how a trusted data layer, integrated with leading analytics platforms like BlackRock Portfolio 360, can transform your reporting, risk analysis, and client conversations.
Disclaimer: References to BlackRock and Aladdin Wealth are for informational purposes only. This content does not constitute investment advice or a recommendation. All opinions expressed are those of the speakers.
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