In my role as UX Lead Consultant, I was engaged by Deloitte to design a modern, front-end MVP that could help global investment banks tackle one of their most deeply embedded operational challenges: fragmented and reactive Client Lifecycle Management (CLM).
A high-fidelity UX prototype was created to unify siloed workflows through modular design, data visualisation, and strategic decision support. Although a Beta was planned for 2020, the project was paused due to COVID-19.
This case study documents the full UX process—from stakeholder discovery to high-fidelity prototype delivery—of a platform built to consolidate onboarding Investment Banking Clients, servicing, compliance, and offboarding into a modular, data-driven interface.
Global banks operate on layered systems, stitched together over decades. In practice, this meant that:
Relationship Managers couldn’t prioritise clients by value or urgency
Clients were asked to resubmit the same documents across teams
Compliance risk surfaced after deals were already initiated
Offboarding was political, manual, and invisible
And perhaps most critically, no one had a single source of truth.
My challenge was to solve all of this—at the experience layer—without disrupting core banking infrastructure.
How we conducted stakeholder interviews to identify systemic pain points
How I translated hypotheses into a modular UX strategy
How I led design across five critical user flows:
Client Prioritisation
Single Customer View
Add-On Product Requests
Compliance Risk Triage
Exit Trigger Logic
The UX methods I applied to transform raw insights into actionable design
The final high-fidelity prototype delivered to senior stakeholders at Deloitte and client banks
This platform was shaped directly by interviews with client-facing bankers, compliance officers, operations teams, and banking clients themselves. We conducted workshops and SME interviews to uncover bottlenecks, redundancies, and service risks across the client lifecycle.
From these sessions, three core personas emerged—each reflecting a critical user type whose day-to-day pain points the system was designed to resolve:
“I need one place to see what’s urgent, who’s falling behind, and what’s missing.”
Modules Impacting Sarah:
“We’re always reacting—never ahead of risk. And it’s hard to prove who saw what, when.”
Reviews risk alerts and audit logs
Manages escalations and documentation trails
Struggles with versioning and audit readiness
Has limited visibility across systems
Modules Impacting Anika:
Compliance Risk Panel
SCV Panel
Exit Trigger Tracker
“I don’t always know what’s required—or when it’s been approved.”
Represents large corporate clients
Engages post-onboarding for product add-ons
Wants transparency and reduced admin friction
Prefers digital document interaction
Modules Impacting Daniel:
Add-On Product Flow
SCV Panel
As a cross-functional team, we began with an intensive discovery phase across multiple banking clients. Our focus was on uncovering common breakdowns in client onboarding, compliance, and exit processes.
We conducted:
12+ SME interviews across onboarding, compliance, and RM desks
Workshop synthesis using affinity mapping
Review of internal Deloitte CLM strategy documents
Comparative IA audit of existing portals and servicing tools
We identified six persistent, systemic problems—each causing delays, confusion, or risk exposure. Below, I’ve included direct quotes to show the emotional and operational weight of each issue.
1. No Single Customer View
“I have to ask three different teams just to confirm if KYC is valid.” — Relationship Manager, Top 5 Global Bank
→ Data was fragmented across CRMs, spreadsheets, and email threads.
→ RMs, Compliance, and Ops had different truths.
2. Manual Onboarding & Fragmented Workflows
“Every client becomes their own project manager. We make them chase us.”
— Onboarding Specialist, UK Investment Desk
→ Document duplication, approval silos, and no shared timeline.
3. Risk Surfaces Too Late
“We’re always reacting. By the time we see a red flag, the deal’s halfway through.” — 2LOD Officer, Global Compliance
→ No dashboard or alerts for compliance to triage early.
4. No Tiering or Client Prioritisation
“I don’t know if I’m spending my time on the right clients.” — RM, Commercial Banking
→ No embedded logic for revenue, SLA, or inactivity.
5. Duplicate Document Requests Across Teams
“I submitted this last month—why are you asking again?”
— Mid-Tier Institutional Client
→ Redundancy caused frustration and trust erosion.
6. Offboarding Was Risky, Manual, and Invisible3. Risk Surfaces Too Late
“It takes three months and four approvals just to close an inactive account.” — Ops Lead, Exit Process Review
→ No shared rules engine, risk scoring, or audit log visibility.
My Design Approach
From the six systemic pain points we identified during discovery, I translated each into a clear hypothesis and a targeted UX feature module.
My goal wasn’t to build another portal. It was to give each role in the CLM ecosystem the one thing they needed most, right when they needed it—through visual clarity, action-first hierarchy, and intuitive IA.
Working closely with Deloitte’s CLM strategy team and our technical stakeholders, I proposed five MVP modules. Each module corresponds to a specific lifecycle phase—and maps directly back to validated user needs.
The dashboard applies lightweight data visualisation principles to reduce cognitive load:
| Visual Element | Purpose |
|---|---|
| Tier Cards | Quantify client distribution and alert concentration |
| Alert Chips | Encode risk state without needing detailed rows |
| Table Sorting | Enable dynamic data prioritisation on SLA or Tier |
| Tooltips | Reveal hidden escalation logic without overwhelming UI |
This approach blends data clarity with interaction efficiency—allowing fast orientation without traditional charts.
One of the most frequent challenges raised during stakeholder interviews was this:
“I don’t know if I’m spending my time on the right clients.” — Relationship Manager, Tier 1 Desk
Relationship Managers (RMs) were working with up to 80 clients at once, yet had no system that clearly indicated:
Who was high-value or high-priority
Where service-level agreements (SLAs) were at risk
Which clients had outstanding documentation or activity red flags
Instead, they relied on spreadsheets, emails, and disconnected CRM entries. No alerts, no triage, and no actionable hierarchy.
If we surface Tier, SLA, activity status, and recommended actions in a single dashboard view, then RMs can prioritise their client base in real time—without waiting for email alerts or Excel updates.
This hypothesis guided the structure of what became the RM Dashboard: a tactical control centre for RMs, built with fast visual scanning, colour-coded logic, and modular flexibility.
Hick’s Law: Limit decision fatigue by surfacing only key actions per client row
Progressive Disclosure: Show escalation flags and tier at a glance; full notes on hover
Fitts’s Law: Large, easily clickable CTAs (“Upload Docs”, “Escalate”)
Information Scent: Colour-coded badges (Tier), chips (SLA/Dormant/Risk) guide scanning
User Control & Feedback: Sorting, filtering, and hover previews aid confidence
Accessibility (WCAG 2.1 AA): Colour + icon logic ensures visibility under all conditions
Atomic Design: Cards, chips, buttons, rows, and tags are reused across modules
Stacked Tier Cards above a master client table
Row-by-row logic with columns: Client, Tier, Status, Next Action, Last Interaction
Inline chips showed SLA status, Dormant flags, and Document requests
Sorting toggles on Tier and SLA columns
“Next Action” logic pre-populated (e.g. Escalate, Upload, Exit)
Tier Cards: Glanceable view of Tier 1–3 volumes + alert count
Table Layout: Scannable, sortable, hover-enhanced
Alert Chips: Immediate visual of risk and SLA status
“Next Action” Column: Removes ambiguity and adds accountability
A clear breakdown of client volume by tier
Alerted clients surfaced by risk state
A precise next action per client row
Full interaction history and task ownership
The KYC Heatstrip and tag-driven tables exemplify lightweight, embedded data visualisation:
| Element | Purpose |
|---|---|
| KYC Heatstrip | Single-row, colour-coded visual of document status distribution |
| Status Tags (Table) | Repeat logic (icons + text) improves scannability and clarity |
| Timeline Panel | Visual clustering of events without heavy charting |
| Inline CTAs | Show only one required action per doc = reduce decision fatigue |
This is not chart-heavy, but decision-lightweight—designed for speed, accuracy, and clarity across teams.
Throughout our workshops and stakeholder interviews, a common friction point emerged:
“We don’t have a single place to see where the client is in the process.” — KYC Officer, Global Onboarding Team
Each team (RMs, Compliance, Ops) had access to partial information across siloed systems—email chains, PDFs in SharePoint, CRM notes, and Excel trackers. This caused:
Duplicate document requests to clients
Delays in onboarding or product fulfilment
Lack of clarity around compliance state and history
Worse, no one owned the “single view.” It was everyone’s problem—and no one’s responsibility.
If we deliver a modular, tabbed Single Customer View (SCV) combining KYC status, risk alerts, document audit logs, and a shared timeline, then teams can align faster and reduce handover delays.
The solution had to support visual triage, role-based priorities, and fast action—without overwhelming any single user.
KYC Heatstrip (visually encodes status across all documents)
Tabbed navigation (clear cognitive grouping by task)
Inline action buttons (upload, update, view—based on role and status)
Audit log with compliance notes (transparent action trail)
Sarah (RM): Views status at a glance, adds RM notes, flags missing docs
Anika (Compliance): Logs escalations, reviews doc history
Daniel (Client): Benefits passively—fewer document chases, faster service
This module uses interaction-as-visualisation rather than charts. Key elements include:
| Element | Purpose |
|---|---|
| Upload checklist | Visualise progress and gaps in real time |
| Upload status tags | “Missing”, “Invalid”, “Uploaded” – visual alert system |
| Timeline label | Review time shown to manage expectations |
| Status updates | Last Updated per doc = temporal tracking and accountability |
It’s a data-driven flow, not a chart-driven one—supporting clarity, validation, and fast internal handover.
A major pain point uncovered in both RM and Ops team interviews was the chaos of post-onboarding product requests.
“Each time a client wants something new, it’s like onboarding them all over again.” — Ops Lead, Corporate Banking
Once a client was live, adding new products (FX, lending, custody, etc.) triggered:
Confusion over eligibility
Manual back-and-forth on required documentation
No clarity on who reviews what and when
Existing processes were opaque, inconsistent, and relied on Outlook, Word forms, and PDF uploads. Clients had no visibility. Internal teams had no workflow logic.
If we provide a guided, step-by-step Add-On Product flow with eligibility filtering, document checklisting, upload logic, and submission review, we can reduce time-to-approval and internal ambiguity.
The flow had to be simple for RMs like Sarah, accountable for completeness, and easy for Compliance to validate.
Left panel with product request summary
Right panel with dynamic checklist: Mandatory, Conditional, Optional
Inline document action states (View, Upload, Replace)
Error and upload-state indicators
Final review screen with “Estimated Review Time” and submission context
Eligibility-filtered product selector
Smart document checklist (dynamic by product and client)
Upload state logic: Mandatory/Optional/Conditional
Upload and replace interaction with instant feedback
Submission screen with timeline and handoff info
Daniel (Client): Indirectly benefits—fewer doc chases and resubmissions
Sarah (RM): Initiates product request, uploads docs, tracks progress
Anika (Compliance): Receives clean, pre-filtered package with audit trail
While not using traditional charts, this module leverages lightweight data storytelling through:
| Element | Purpose |
|---|---|
| Summary Cards | Visual distribution of active risk, breaches, and queue size |
| Table with colour-coded flags | Prioritise by alert severity and ownership |
| Date + trend indicators | Week-on-week signal embedded in risk cards |
| Audit Trail | Visual evolution of risk lifecycle, actor engagement over time |
This interface balances control panel utility with visual cognitive cues to drive decisions.
In our discovery sessions with Compliance Officers and Risk Analysts, a single challenge echoed repeatedly:
“By the time we see the issue, the breach has already happened.” — Senior Compliance SME, CIB Oversight
The compliance team had no central place to:
Monitor high-risk client flags across Tier levels
Escalate KYC issues, SLA breaches, or anomalous inactivity
Track decision logs or see how risk has evolved over time
Instead, each incident was discovered through email alerts, offline trackers, or ad hoc queries. This lack of visibility delayed escalations and left the bank exposed.
If we provide a central risk triage panel that combines flagged client alerts, risk levels, and a compliance audit trail, we can empower Compliance teams to respond earlier, faster, and with full documentation.
This would replace scattered spreadsheets and inbox searches with a shared, real-time control panel.
Law of Prägnanz – Card layout groups alert types visually
Fitt’s Law – “Escalate” and “Update” are placed inline for immediate action
Hick’s Law – Risk table filters and categories limit overload
Recognition Over Recall – Clients grouped by risk severity (colour-coded + labels)
Feedback & Visibility – Audit log shows timestamps, escalation path, and user decisions
Consistency – Chips, buttons, tables reused from previous modules (Dashboard, SCV)
Summary cards: High, Medium, Low Risk + SLA Breaches + Awaiting Review
Filterable table of client alerts: Name, Alert Type, Priority, Owner, Last Updated
Inline CTAs: “Escalate” and “Update” tied to role and alert type
Scrollable audit trail with actor history (e.g. “Sarah escalated on 11/10/19”)
Anika (Compliance Officer): Central risk triage, action triggering, and review log
Sarah (RM): Can follow up on flagged clients, understand why escalations occurred
Ops Manager: Uses card metrics to manage team load and triage efficiency
This module is built around a central scatterplot as the primary decision-support element:
| Visual Element | Function |
|---|---|
| Chart (Risk vs Inactivity) | Correlate latent inactivity with risk urgency |
| Colour-coded Dots | Red = Risky + Dormant, Yellow = Dormant, Green = Active |
| Hover/Click Labels | Expose client name, last login, Tier, £ value |
| Trend Filters | Segment by Tier or Dormancy for focused action |
| Audit Trail | Visual memory of escalation chain |
This was the most “data-dense” module—yet remained intuitive thanks to careful layout, filtering, and progressive interaction design.
A striking gap identified in both Compliance and Strategy workshops was the lack of an exit framework:
“We invest heavily in onboarding clients—but have no systematic way to exit them.” — Senior Partner, Deloitte CLM Advisory
Clients that were inactive, unprofitable, or flagged for repeated risk violations stayed on the books indefinitely. This led to:
Resource drain on RMs and operations
Exposure to regulatory scrutiny due to inactive high-risk clients
Missed opportunities to proactively flag and formalise exits
There was no logic—just legacy.
If we provide a visual interface showing clients by inactivity and risk score, backed by a filterable trigger panel and decision log, then RMs and Compliance can jointly manage proactive offboarding.
We aimed to build a shared, visual risk exit framework—something no Excel sheet could replicate.
Anika (Compliance Officer): Central risk triage, action triggering, and review log
Sarah (RM): Can follow up on flagged clients, understand why escalations occurred
Ops Manager: Uses card metrics to manage team load and triage efficiency
In 2019, I was brought into Deloitte’s Digital Forensics team to lead UX design on a strategic Customer Lifecycle Management (CLM) prototype for investment banking clients. The goal was to replace fragmented onboarding, compliance, and servicing processes with a unified, data-driven experience layer.
I designed five interconnected modules:
RM Dashboard – Client prioritisation by tier, SLA, and risk
Single Customer View – Tabbed hub for KYC, risk, and document status
Add-On Product Flow – Guided checklist and submission logic
Compliance Risk Panel – Escalation dashboard and audit trail
Exit Trigger Tracker – Inactivity vs risk scatterplot to support proactive offboarding
We ran workshops, mapped user flows, prioritised MVP features, and delivered a fully validated high-fidelity prototype—grounded in accessibility, atomic design, and real-time data visualisation.
Although well received, development was paused due to:
High initial implementation costs
Risk of disrupting live banking systems
Incompatibility with some legacy infrastructure
A Beta phase was planned for early 2020 to test functionality with engineers and IT architects. I was scheduled to return to develop the design system and lead UX handover. However, the COVID-19 crisis triggered financial reprioritisation across banks and Deloitte, halting the programme before development began.
This remains a strong example of how UX can drive strategic clarity, visual governance, and data-backed decision-making in complex enterprise environments.
