Don’t you think it’s a cause for caution when a limited partner (LP) asks you:
Why do they receive their performance updates weeks after a major market move?
Why doesn’t their dashboard include a metric relevant to them?
Why do their reports look identical to everyone else’s?
This mismatch can cause LPs to pause and wonder if you truly understand their portfolio and if their risk preferences and capital strategies are being taken into account.
Research confirms it. PwC reports that many high-net-worth investors want more personalization in their wealth management relationship, but only a third feel that’s what they currently experience.
Yet here you are: stuck using manual processes and static templates that not only slow you down but also force standardized reports, leaving no room for contextual data. And with the trust factor already shaky, competitors who adapt faster already have an advantage over you.
Fret not. In this blog post, you’ll learn how AI-driven personalization can help rebuild that trust and the role tools like RAISE play in supporting fund managers in delivering investor-ready insights.
The Cost of Staying Generic
Three risks directly affect how LPs see your fund and how your team operates from day one:
1. Clarity gets lost
When your updates don’t reflect investor-specific benchmarks, questions are bound to pile up. For instance, a report might show net IRR at the fund level, but an LP who focuses on cash yield won’t find the metric they care about, i.e., payout ratios.
This translates into more work for you because you now have to spend extra time clarifying numbers and fixing the report instead of discussing a strategy that would be beneficial for the LP.
2. Fundraising pace slows
LPs look at more than just returns. They pay attention to how clearly reporting reflects the way they evaluate performance. If they don’t find any personalized insights from you, that impression will also follow into their fundraising conversations.
For example, an LP may want to see sector exposure broken out by geography before committing additional capital. If your standard packet doesn’t provide that, your team will have to rework the data mid-fundraise.
By the time the clarification is ready, another manager who already provides that level of information may have secured the allocation.
3. Compliance pressure increases
LP expectations often depend on where they’re based and the rules they operate under. With cookie-cutter reports, you risk overlooking the specific requirements tied to their domicile or regulatory environment.
For example, a European investor may expect SFDR-aligned disclosures, while a US-based LP may focus on tax transparency. If your template squeezes both into the same format, you create extra back-and-forth and expose your team to scrutiny during reviews.
Fun Fact: Institutional investors spend 40% of their due diligence time verifying data accuracy. — Preqin’s Future of Alternatives 2024
Also Read: The Role of Automation in Reducing Costs and Risks for Fund Managers
AI as the Enabler of True Personalization
You get it: LPs want more than a quarterly snapshot. The real question is, how do you deliver that level of personalization at scale without overwhelming your team in the long run? That’s where AI can make a huge difference.
According to Deloitte, fewer than 10% of private funds are using AI in core functions. But that number is expected to rise to as much as 25% in portfolio valuation over the next 5-7 years. Let’s explore how AI can help you personalize fund management.
| What AI Does for You | Benefit You Provide to LPs |
|---|---|
| Transforms static dashboards into investor-level views that reflect unique benchmarks, risk preferences, and historical performance | LPs get the sense that their specific priorities are being tracked, not averaged into a group summary. |
| Sends automated alerts on portfolio changes or compliance milestones, , adjusting the level of scrutiny to match the actual risk | LPs see updates in context, and you’re able to save time answering the same queries across multiple accounts |
| Applies predictive analytics to highlight patterns and emerging risks across holdings | LPs can easily see where their fund may be headed and what factors are shaping that outlook. |
Personalization in Practice with RAISE
Theoretically speaking, the value personalization brings to the fold is very much visible. However, how does it play out when you use RAISE?
It combines fund administration, investor engagement, and compliance into a single, robust platform, specifically excelling in generating custom AI-driven client insights for fund managers. Let’s consider a scenario:
1. Investor reporting that speaks their language
An LP logs into RAISE Connect and finds their portfolio benchmarked against the exact indices they track. They can view returns in the context of their own risk profile instead of scanning through a generic PDF. For you, that means fewer one-off requests and less manual data repackaging.
2. Compliance reviews that adapt in real time
A compliance officer uses RAISE CRA to review a new investor profile. Instead of walking through the same checklist every time, the platform applies AI-driven risk scoring. Low-risk investors move through quickly, while high-risk cases are flagged for deeper review.
Also Read: RegTech in Action — How RAISE CRA is Redefining Compliance
3. Capital calls without delays
When an administrator updates a capital call in RAISE FAS, the change is reflected instantly in investor dashboards. LPs see the update in context with their commitments, and you avoid the cycle of calls and clarifications that follow email-only communication.
4. Dynamic portfolio oversight
As a fund manager, you rely on RAISE PMS to track portfolio health. AI-driven predictive data highlights where returns could shift or risks could rise, giving you the chance to address concerns before investors raise them.
Roadmap to AI-Driven Personalization: How to Get Started
Contrary to popular belief, adopting AI for personalization doesn’t happen all at once. It develops in stages, each one setting the foundation for the next:
1. Centralize and standardize investor data
The first step is to take stock of all your investor data. Right now, it probably sits across spreadsheets, PDFs, emails, and internal systems.
To customize anything, you first need to see it clearly in one place. That means consolidating your records, cleaning them, and tagging them so you know which industry metrics, compliance files, and contribution schedules matter to each LP.
| Pro Tip: Set a clear timeline for this clean-up and assign responsibility to different teams. For example, give investor relations three weeks to reconcile contact data, finance two weeks to validate commitments, and compliance a month to review KYC records. |
2. Standardize and configure systems
Once your data is in one place, define a consistent format for it. Standardize how valuation dates are entered, how distribution notices are archived, and how investor onboarding data is captured. Then, configure your reporting platform to ensure that those profiles accurately reflect the priorities of each LP.
| Pro Tip: Even something as simple as how you record “location” matters. One team might write “US,” another “USA,” and another “United States.” Therefore, decide on one format for each data element, whether it’s currencies, dates, or risk categories, to prevent small inconsistencies. |
3. Pilot personalization in one area
Rather than rolling out everything at once, test personalization where it can show quick results. You might begin with automated dashboards for a small group of LPs or utilize predictive insights in portfolio monitoring for a single fund. Whatever it is, start small and then scale up.
| Pro Tip: Imagine piloting with five LPs in your flagship fund. You set up dashboards that show each one their preferred benchmark: one compares against MSCI Europe, another against S&P 500, and a third against sector-specific indices. When you meet them, ask what was useful and what was missing. Their feedback will guide us in further improving the rollout. |
4. Embed personalization across the firm
Sorting out technology is just one side of the coin. You also need to train your teams so that they can properly understand how to use the new workflows. Additionally, document the steps to enable reporting, compliance, and fund administration to follow the same approach.
| Pro Tip: Before scaling firmwide, run a “personalization audit” once a quarter. Ask your team: Does every LP have their profile set up correctly?Are dashboards still showing relevant metrics?Are compliance checks aligned with current regulations? This discipline ensures personalization remains accurate and credible as your investor base evolves. |
Treat Personalization as a Strategic Advantage
The future of fund management is not only about managing capital efficiently. It’s about showing investors that you understand how they define success, and reflecting that understanding in every interaction.
Fund managers who incorporate personalization into their operating model will stand out, as they align their processes with what investors value most: clarity, relevance, and trust. AI gives you the leverage to do this without stretching your team thin.
From automating day-to-day reporting to surfacing forward-looking insights, it allows you to deliver a level of transparency that feels personal, while keeping your operations consistent and scalable.
If you want to see how this can translate into your own workflows, explore how RAISE helps fund managers and administrators move from standardized reporting to personalized investor experiences.
Book a demo with RAISE to see how personalization can strengthen your LP relationships.
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