Future-Proofing Wealth Operations: Marco Kermaidic on Seamless AI Integration and Operational Resilience
At a recent industry dialogue on COO priorities for 2025, Marco Kermaidic, Chief Operating Officer at BNP Paribas Wealth Management in APAC, cut through the noise. His message was direct: expectations for AI are high, but value only shows up when AI is fully embedded into the operational fabric-not bolted on.
In a market with stricter regulation, rising cyber risk, and clients who expect instant, mobile-first service, operations can't be an afterthought. "Successfully integrating and embedding AI into our tools will be essential to achieving the desired improvements in client experience and operational efficiency," he said. The mandate is clear: modernise without losing client trust.
The 2025 COO Mandate: Control, Speed, and Scale
COOs now carry a dual brief: enable the business and reduce risk-at the same time. That's forcing sharper focus on a few priorities where operational leaders can create compounding benefits.
- Client experience: consistent, fast, and low-friction across every channel.
- Platform scalability: handle growth without adding headcount at the same rate.
- Data governance: turn messy data into reliable inputs for decisions and models.
These themes aren't new. What's new is the maturity of AI, automation, and data tooling that can make them real-if you rework the underlying processes.
AI Must Be Embedded, Not Adjacent
AI pilots are easy. Enterprise integration is hard. Kermaidic's point: the workflow-not just the interface-needs rethinking around intelligent automation, with data quality and security handled upfront.
Client onboarding is a prime example. Many firms digitised the front end, yet compliance, tax, and suitability checks often remain manual and jurisdiction-specific, which creates bottlenecks. "Wealth management is a trust business. You can't outsource empathy or nuance to a model. But by automating repetitive, error-prone tasks, you free teams to focus on what truly matters: the client relationship."
Making Legacy Work for You
Incumbents have dependable platforms and deep control environments-along with older systems and fragmented data. Embedding AI in that reality means re-engineering core processes, refreshing control frameworks, and fitting new tools to existing infrastructure without breaking stability.
It also means upskilling teams, building model governance, and moving the culture toward continual improvement. Talent, process, controls, and tech have to move together, or nothing sticks.
Seamless Beats "Digital"
Digitising individual steps won't cut it. The aim is a smooth end-to-end experience where compliance is felt as clarity, not friction.
- Compliance by design: build regulatory requirements into the journey from the first click.
- Seamless digital UX: make checks feel natural and guided, not like paperwork dumped on a screen.
Done well, real-time screening and automated checks reduce delays while raising accuracy. That's "regulatory agility" in action-meeting standards while improving speed and quality.
COO as Strategic Enabler in 2025
Operations have shifted from cost center to growth engine. The impact shows up in three levers.
- Digital acceleration: self-service, AI-first tooling, and selective fintech partnerships.
- Global operational agility: cross-border account setups and product expansion that work within complex regulatory demands.
- Smart cost optimization: automation, cloud, and platform consolidation that improve unit economics.
A Practical 90-Day Integration Playbook
If you lead operations, here's a tight plan that aligns with Kermaidic's direction and gets traction fast.
- Days 0-30: Map your top 3 workflows by volume and risk (e.g., onboarding, screening, post-trade controls). Inventory the data they rely on, system handoffs, and manual touchpoints. Define success metrics and control requirements upfront.
- Days 31-60: Pick 1-2 use cases for pilot (e.g., document extraction for KYC, real-time sanction screening). Stand up a secure data pipeline, model registry, and human-in-the-loop review. Embed policy rules and audit trails.
- Days 61-90: Integrate with production workflows for a limited client or product segment. Track outcomes vs. baseline (cycle time, STP rate, false positives, rework, exceptions). Close gaps in model monitoring, access control, and continuity plans.
Metrics That Matter
- Onboarding turnaround time (median, P90) and straight-through processing rate
- Manual touchpoints per case and first-pass yield
- Screening false-positive rate and case resolution time
- Model explainability coverage and audit trail completeness
- Incident mean time to detect/recover for critical workflows
Your Capability Stack Checklist
- Data foundation: governed data products, lineage, and quality SLAs
- Model operations: versioning, monitoring, bias/drift checks, human oversight
- Policy engine: rules and controls externalised from code for faster updates
- Workflow orchestration: case management with clear RACI and audit
- APIs and integration: clean interfaces into core banking, CRM, and compliance tools
- People and process: upskilling plan, playbooks, and change management cadences
Governance and Resilience: Non-Negotiables
AI at scale requires strong guardrails. Adopt clear model risk practices, document decisions, and test controls under stress. Treat resilience as a design choice, not an afterthought.
For reference frameworks, see the NIST AI Risk Management Framework and the Basel Committee's Principles for Operational Resilience.
Upskilling the Ops Org
Give teams the skills to operate AI-enabled workflows: prompt fluency, data literacy, control design, and model oversight. Start with short, applied programs tied to your live use cases.
If you need a curated starting point for operations-focused AI paths, explore role-based options here: Complete AI Training - Courses by Job.
The Bottom Line
Kermaidic's stance is pragmatic: AI is an enabler, but only if it's wired into real processes with clear controls, measurable outcomes, and teams who know how to run it. Seamless beats "just digital," and operations can be the edge-if you build for resilience and speed at once.
That's how large institutions keep trust while moving faster-one re-engineered workflow at a time.
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