Enterprise UX · AI · 2026
Sky - A Generative AI Assistant for Bank Advisors
Sky is a virtual assistant powered by generative AI, designed for a financial institution's advisors. It delivers fast, personalized sales arguments and a unified knowledge base, integrated directly into PIC, VOCE and the Single Frontend.
Role
UX Researcher & Designer
Client
Financial Institution
Timeline
2026
Tested with
29 advisors
Skills applied
01 · Problem
Advisors were drowning in scattered information
Financial institution advisors needed to consult multiple systems and lengthy product documents to prepare a single client conversation. Information lived across PIC, VOCE and the Single Frontend, with no unified knowledge base or quick way to generate tailored sales arguments.
The cost was concrete: slower interactions, inconsistent messaging between advisors, and friction every time a client asked something slightly outside the script.
4.3
tabs per argument
Average open product tabs to prepare one sales pitch.
3
disconnected systems
PIC, VOCE and the Single Frontend, with no shared search.
~22s
copy-paste cost
Time lost per response moving text into the call script.
Concept · TO BE
Sky embedded inside the unified Branch front-end
María Rodríguez Pérez
ID 0042-118-9921 · Premium · Client since 2014
Customer
Premium
Commercial / Risk
A · Low
Personal / Work
Self-empl.
Financial
€ 84.2K
Advisor
Which mortgage offer fits a self-employed Premium client?✦ Sky
Hipoteca Variable Premium: Euribor +0.49% (TIN), TAE 3.21%. Bonifiable to +0.39% with payroll & insurance.
Source
BCOM · Mortgage Catalog 2026-Q2
Sky · Avg. response 1.2s · GenAI
02 · Process
Research-led, validated end to end
I led discovery and design across three phases: kick-off and context mapping, ideation of the AI assistant flows, and unmoderated usability testing with 29 real advisors.
- Stakeholder interviews to map daily advisor journeys.
- Heuristic review of PIC, VOCE and the Single Frontend.
- Concept prototypes for embedded vs. side-panel assistant.
- Unmoderated remote testing with task-based scenarios.
- Iteration cycles informed by qualitative + behavioral data.
Research timeline
01 · Discover
Interviews, journey mapping, heuristic review
02 · Design
Concepts, prototypes, embedded vs. side-panel
03 · Validate
Unmoderated tests with 29 advisors, iteration
03 · Research Insights
What advisors actually needed
Synthesizing interviews and test sessions surfaced four insights that anchored every design decision downstream.
- I-01
Context beats search
Advisors don't want a search engine - they want the right answer surfaced where they already are.
- I-02
Speed defines usefulness
If Sky takes longer than opening a tab, advisors will not adopt it during live calls.
- I-03
Trust requires traceability
Advisors need to see the source document behind any AI answer before they repeat it to a client.
- I-04
Tone is part of the product
Advisors trust answers that sound like a confident colleague, not a generic chatbot.
Field finding · 06
Opinion on the virtual assistant on the PIC front
How useful is having a virtual assistant?
29/29
rated it useful or very useful
“It makes it easier to have information in a single tool - we speed up service and avoid giving wrong information to customers.”
What should it be called?
04 · Usability Issues
Friction surfaced during testing
Tasks were timed and observed across 29 advisors. The issues below appeared most often and drove the highest drop in task confidence.
| Issue | Severity | Pattern |
|---|---|---|
| Long AI answers skipped under time pressure | High | Nearly universal |
| No visible source on generative responses | High | Nearly universal |
| Manual copy-paste into call script | Medium | Frequent |
| Regional banking jargon mismatched | Medium | Frequent |
| Robotic tone reduces perceived trust | Medium | Common |
| Low-confidence answers shown identically to high-confidence | High | Common |
Field finding · 02
Frequency of searching for information to guide a client
Where they look (multi-select, 83 mentions)
- BCOM portal (sales arguments)21
- PDFs / PPTs in Contact Center16
- Bank's public website12
- Ask a colleague10
- Search in emails9
- CUC - Single Knowledge Center8
- Single experience site6
- Other (The Portal)1
05 · Evidence
What the sessions actually showed
Rather than post precise percentages from a 29-person usability study - which would overclaim - here are the patterns that repeated across sessions, ranked by how consistently they showed up.
Source: unmoderated remote tests with 29 financial-institution advisors, task-based scenarios plus a short post-task survey. Bars show relative frequency across sessions - directional, not statistically significant at this sample size.
Field finding · 05
Should Sky have a maximize / minimize option?
Yes - keep maximize / minimize
132/167
No - keep it fixed
35/167
Why have it
- · Advisors choose how to view the screen for comfort - 38
- · Easier to view the offer and validate detail - 36
- · Best of both modes - 27
- · More organised, practical, accessible - 26
Why not
- · Want full view of customer info and query - 17
- · Practical to keep one fixed layout - 13
- · Avoid cluttering the screen - 2
06 · Design Decisions
A contextual assistant, never a separate app
Embedded, not standalone
Sky lives inside the tools advisors already use. No tab switching, no context loss.
Sales arguments on demand
Generative responses are framed as ready-to-use arguments, with source citations advisors can verify.
Trust through transparency
Every AI answer surfaces the underlying documents, so advisors stay in control.
Progressive disclosure
Short answer first, expandable detail second - matched to the rhythm of a live client call.
One-click insert
Approved answers drop directly into the active call script field.
Confidence flags
Low-confidence answers are visually marked and suggest escalation paths.
07 · How it works
From advisor question to cited answer, end to end
The assistant is not a chat wrapper. Every question flows through a pipeline that routes intent, retrieves from a unified knowledge base, generates a grounded answer, and requires the advisor to verify before anything reaches the call script.
01
Advisor asks
Question typed in the embedded panel while the call script is open.
02
Router agent
Classifies intent: product spec, fees, comparison, or objection handling.
03
Retrieval
Pulls from the unified knowledge base across PIC, VOCE, and product docs.
04
Grounded answer
LLM writes a short answer first with progressive disclosure and inline citations.
05
Verify + insert
Advisor confirms tone, edits if needed, then one-clicks into the call script.
Every generation is paired with a source chip so the advisor can defend the answer live on the call. This citation-first design turned scepticism into adoption during testing.
08 · Results
Validated with advisors, not yet in production
29
advisors tested
Unmoderated remote sessions with task-based scenarios.
3
platforms integrated in the prototype
PIC, VOCE and the Single Frontend, unified into one contextual panel.
1
shared knowledge base
Consolidated the product docs advisors were previously searching across separate systems.
What the sessions told us, in plain terms: advisors could find the product information they needed without switching tools, and the short-answer-first pattern with a visible source made them more willing to actually use the generated argument on a live call. I'm deliberately not publishing productivity percentages here - the pilot hasn't run at scale, and the sample was 29 advisors in a testing environment, not a rolled-out product.
The qualitative pattern was consistent: advisors trusted answers that showed their source, and distrusted the ones that didn't. That single finding drove most of the UI decisions above.
09 · Roadmap
From research insight to staged rollout
The findings shaped a phased delivery plan: ship the embedded assistant to a controlled cohort first, harden trust and tone, then expand to the full advisor network.
Q1 · 2025
Discover & frame
Done- -Stakeholder interviews · journey mapping
- -Heuristic review of PIC, VOCE & Single Frontend
- -Problem statement & success metrics agreed
Q2 · 2025
Design & validate
Done- -Concept exploration · embedded vs. side-panel
- -Unmoderated tests with 29 advisors
- -Iteration on tone, sources & confidence flags
Q3 · 2025
Pilot
In progress- -Sky moves from prototype to a controlled advisor cohort
- -In-product feedback loop and weekly tuning
- -Every answer must show its source before it ships
Q4 · 2025
Scale
Planned- -Rollout beyond the pilot cohort
- -Multilingual sales arguments (ES · EN · PT)
- -Manager view for accuracy and escalations
2026
Evolve
Vision- -Proactive next-best-argument suggestions
- -Voice mode for live call assistance
- -Continuous fine-tuning on verified answers
10 · Findings
Research findings, by theme
Filter the insights surfaced during research and testing with 29 advisors. Each finding pairs evidence with the design decision it shaped.
Usability
Advisors expect Sky to live inside their current tools
Evidence - Most advisors instinctively looked for Sky inside PIC before checking anywhere else.
Design impact - Embedded Sky directly in PIC, VOCE and the Single Frontend instead of a separate app.
Comprehension
Long AI answers were skipped under time pressure
Evidence - In simulated calls, advisors stopped reading long responses before reaching the useful part.
Design impact - Introduced a short summary first, with expandable detail on demand.
Workflow
Switching between product docs broke advisor focus
Evidence - Preparing one argument routinely meant opening several product tabs at once.
Design impact - Shared knowledge base surfaces sources in one contextual panel.
Trust & AI
Advisors will not use answers they cannot verify
Evidence - The most repeated question during testing was 'where does this come from?'
Design impact - Every generative answer shows its source document inline.
Comprehension
Banking jargon needed to match the advisor's region
Evidence - Mismatched terminology consistently caused misreads during task walkthroughs.
Design impact - Sky adapts product terminology to the advisor's market segment.
Workflow
Copying arguments into the call script was the slowest step
Evidence - Manual copy/paste was the visible bottleneck between reading and using an answer.
Design impact - Added one-click insert into the active conversation field.
Usability
Voice and tone need to feel like a colleague, not a chatbot
Evidence - Advisors described early formal responses as robotic and 'not something I'd say to a client'.
Design impact - Rewrote prompts to a confident, peer-to-peer banking voice.
Trust & AI
Uncertainty must be visible, not hidden
Evidence - When Sky guessed without flagging it, advisors lost trust for the rest of the session.
Design impact - Low-confidence answers are flagged and suggest escalation paths.