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Investors turn cautious as crypto goes mainstream; trust in AI splits by market. Managers must prioritise plain communication, cleaner tech, and guardrailed AI to earn loyalty.

Categorized in: AI News Management
Published on: Sep 23, 2025
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Wealth Management's

Wealth Management's Digital Shift: Trust, AI, and What Managers Must Do Next

A recent global survey by Avaloq signals a clear pivot in client behavior and firm strategy. Investors are more cautious, digital assets are mainstreaming through traditional channels, and the trust gap around AI is widening in some markets.

For leaders, this isn't about adding tools. It's about fixing trust, modernising tech, and deploying AI where it actually improves advice and service.

What Clients Are Signalling

  • Close to one-third of investors are taking a conservative stance on risk.
  • 24% now hold crypto and digital assets through established institutions-almost double last year.
  • 77% prioritise clear communication over speed or novelty.
  • Mistrust remains a top churn driver-60% of US investors cite it when switching advisers.

Regional Contrasts That Matter

  • Asia: 41% actively pursue ESG; transparency on methodologies is still thin. Hong Kong shows high comfort with fully AI-driven advice (~one-third). In Singapore, 61% prefer AI-supported guidance. Instant messaging is a preferred channel.
  • US: Clients are loyal to traditional advisers and more sceptical of AI, even as 95% of US wealth managers see AI as essential.
  • Tech debt: 70% of Singaporean wealth managers report outdated systems-modernisation is urgent across markets.

Management Implications

  • Trust first: Proactive, plain-language communication beats feature launches. Publish fees, risks, and performance methods openly.
  • AI with guardrails: Pair adviser-led workflows with AI support, especially in markets that value human oversight.
  • Digital assets, managed: Offer compliant access, risk controls, and portfolio integration-not side bets.
  • ESG clarity: Disclose data sources, scoring logic, and trade-offs to avoid client confusion.
  • Messaging channels: Meet clients where they are (IM), but enable capture, surveillance, and audit trails.

Execution Roadmap (90 Days)

  • Days 0-30: Map client segments, key pain points, and high-friction journeys. Audit IM usage and recordkeeping. Identify top 5 tech bottlenecks tied to revenue or risk.
  • Days 30-60: Launch an adviser communication playbook (cadence, templates, escalation). Pilot AI-supported advice for one segment with clear disclosures and human-in-the-loop.
  • Days 60-90: Roll out compliant IM with archiving. Publish ESG methodology notes. Retire or replace one legacy component that blocks data flow or speed to service.

AI Adoption That Builds Confidence

  • Start here: Client query routing, summarisation of market notes, KYC/EDD checks, and portfolio commentary drafts.
  • Human oversight: Adviser approval for any client-facing output. Log prompts, sources, and decisions.
  • Risk controls: Bias tests, hallucination checks, PII masking, and clear opt-outs for clients.
  • Measure: Time-to-response, first-contact resolution, advice turnaround time, and client satisfaction.

Tech Debt: Where to Invest First

  • Data layer: Build a clean, permissioned client and portfolio data fabric before adding new apps.
  • APIs over patches: Standardise integrations to your core systems; avoid point-to-point sprawl.
  • Advisor desktop: Unify CRM, portfolio, and communication into a single pane to cut context switching.
  • Compliance-by-design: Automate surveillance, archiving, and disclosures inside workflows.

Communication That Reduces Churn

  • Transparency: Explain fees, risks, and performance drivers in simple language. No jargon.
  • Cadence: Quarterly model updates, monthly market briefs, and instant alerts for material changes.
  • Channels: Use IM for quick check-ins and approvals, email for summaries, portal for records.

ESG Without Confusion

  • Publish your ESG data sources, weighting logic, and limits (e.g., data gaps, sector biases).
  • Offer client-level preferences (exclusions, themes) and show portfolio-level trade-offs.
  • Avoid one-size scoring-provide context and explain methodology changes over time.

KPIs Leaders Should Track

  • Client trust index, complaint rate, and churn by segment.
  • Digital adoption: portal logins, IM usage, and e-sign share of workflows.
  • Advice efficiency: turnaround time, adviser capacity, approval-to-send rates for AI drafts.
  • Tech health: cycle time for integrations, incident rate, and cost-to-serve per client.

Bottom Line

The firms that will win combine clear, frequent communication with AI-supported advice and a cleaner tech backbone. Prioritise trust, retire legacy bottlenecks, and prove value in every interaction.

See related insights: Avaloq industry perspectives.

Upskill Your Team on Practical AI

If you're planning near-term pilots or process automation, these resources can help: