Anchorline
Anchorline is an agentic guidance layer built inside Borealis, a full-service Canadian retail bank. Everything a customer does day to day is here — Interac e-Transfers, bills, registered investing, credit, mortgage — and running through all of it is an AI that tells them where their next dollar should go, explains why, and never moves it without approval.
The Application
Borealis, working end to end — e-Transfers, bills, registered investing, credit and mortgage, with Anchorline running through all of it.
Design System
The visual and verbal rules that keep the bank monochrome, the AI unmistakable, and every recommendation legible.
UX Research Hub
The archetypes, hypotheses and traceable evidence that justify every product decision in the package.
A whole bank, with an opinion
This is the working product, not a picture of one. Move real money between real accounts, send an Interac e-Transfer, pay a bill, contribute to a TFSA, pay down the Visa — every balance on every screen updates as you go. Anchorline sits inside all of it, and the same decision follows you when you switch instruments.
Try it end to end: send an e-Transfer, pay the Visa, contribute to the TFSA — or approve what Anchorline is recommending. Balances update everywhere, and switching instruments keeps your place.
Anchorline holds the centre tab on mobile and a pinned sidebar slot on web, plus a floating button that follows you onto every screen in the bank.
Contextual violet cards appear inside Accounts, Cards, Investments and Borrow — the AI shows up next to the money it's talking about, not in a separate silo.
The home hub is the first thing a customer sees: what's recommended this week, what it's worth, and the approve / adjust / not-now choice.
Badges and "needs your approval" pills mark the tiles that warrant attention — and disappear the moment the customer decides, including when they decide to hold.
What the prototype actually does
| Area | Flow | Depth | Canadian specifics modelled |
|---|---|---|---|
| Anchorline | Recommend → explain → approve / adjust / decline → receipt → progress | Full flow | Buffer-first allocation, high-interest debt priority |
| Move money | Interac e-Transfer — recipient, amount, account, review, confirm | Full flow | Autodeposit vs. security question, $0 fee, transfer limits |
| Move money | Pay a bill — payee, amount, date, review, confirm | Full flow | Canadian billers, post-dated payments |
| Move money | Between accounts · Deposit a cheque | Full flow · Entry point | Same-day settlement, mobile cheque hold periods |
| Invest | Contribute to TFSA / RRSP / RESP — account, amount, review, confirm | Full flow | Contribution room tracking, CESG grant on RESP, RRSP deadline |
| Cards | Credit card detail → make a payment (min / statement / custom) | Full flow | Minimum payment, statement balance, 22.9% APR, due date |
| Borrow | Mortgage · HELOC · Credit score | Full flow | Fixed-rate renewal date, HELOC room, TransUnion score |
| More | Rewards · Statements · Security · Alerts · Branch/ATM · Insurance | Entry point | CDIC deposit insurance notice, void cheque / direct deposit |
What's invariant vs. what adapts
| Dimension | iOS | Responsive Web | Tablet |
|---|---|---|---|
| Navigation model | 5-tab bar, Anchorline raised in the centre | Grouped sidebar, Anchorline pinned in violet | Master-detail — nav list + full detail pane |
| Dashboard density | Low — one decision in view at a time | High — two-column, plus a persistent explain rail | Medium — nav and content together, no scroll-hunting |
| Approval experience | Thumb-reachable card, full anatomy inline | Inline card + always-open "why" rail | Inline card + explain block in the detail pane |
| Multi-step flows | One step per screen, progress bar in the header | One step per screen, wider review table | One step per screen, wider review table |
| Escalation to a human | Identical on all three — a "Talk to someone" link inside every recommendation and every at-risk state | ||
| The trust rule | Identical on all three — the AI prepares, the customer approves. Nothing moves on its own. | ||
A bounded decision-support system
Anchorline's AI is not described as magic — it is a responsible, explainable system with clear inputs, a fixed prioritisation order, explicit approval boundaries, and a defined behaviour for when it doesn't know enough. Every rule below is what makes the trust rule enforceable in code, not just in copy.
Recommendation priority order
Protect the buffer
A minimum safety cushion is defended before any other move is proposed.
High-interest debt
Proposed whenever its rate outweighs the near-term value of any savings goal.
Goal-priority saving
Allocated by the user's stated order once buffer and debt are healthy.
Investment (secondary)
Proposed only once the above are stable — always prepared, never executed autonomously.
Guidance vs. control preference
| Mode | What changes |
|---|---|
| Guided | AI prepares full recommendations by default; fewer decisions surfaced per session. |
| Balanced | AI recommends; trade-off framing shown more prominently for the user to weigh. |
| Manual-leaning | AI surfaces analysis and scenarios; the user builds the allocation, AI checks it. |
When the AI is assertive, cautious, or abstains
| Posture | Trigger |
|---|---|
| Assertive | High-confidence data, clear priority order, no conflicting goals. |
| Cautious | Recent life-stage change, thin data history, or a stressed-state signal. |
| Abstains | Confidence below threshold, or the action falls outside approval boundaries. |
Confidence & explanation strategy
Full recommendation with one-line rationale; approve in one step.
Recommendation shown with an explicit caveat on what's uncertain.
No specific number proposed — the system explains what data would raise confidence.
Approval boundary rules
| Action | AI may prepare | AI may auto-execute | Approval required |
|---|---|---|---|
| Transfer between eligible accounts | Yes | No | Always |
| Recurring contribution setup / edit | Yes | No | Always |
| Goal contribution reallocation | Yes | No | Always |
| Savings rule change | Yes | No | Always |
| Open a new product | No | No | Out of scope, v1 |
| Execute an investment trade | Simulation only | No | Out of scope, v1 |
| Act on incomplete / low-confidence data | No | No | Never |
Auditability
Every recommendation, its confidence score, the data snapshot behind it, and the user's decision (approve / adjust / decline) are logged as one traceable record — the same record structure a compliance reviewer, a support agent, and the user's own approval-history screen all read from.
Trust as architecture, not messaging
These patterns are built into the interface itself — not stated as values in a marketing page. Each one maps to a specific, always-present piece of UI.
AI disclosure
A persistent "Recommended by Anchorline AI" mark on every AI-authored element — never blended into system copy.
Explanation pattern
What, why, data used, benefit, trade-off — the same six fields, every time, in the same order.
Confidence communication
A visible chip and, where relevant, a percentage — never confidence implied only by tone.
Fairness & bias awareness
Recommendation logic reviewed across archetypes for disparate impact before each release; flagged in the research hub's stakeholder view.
Privacy signalling
"Data used" is shown at the point of every recommendation — not buried in a separate privacy centre.
Human escalation
"Talk to someone" inside every approval panel and low-confidence state, carrying full context to the agent.
Customer control
Guidance level, data inputs, and any standing rule can be paused or reversed by the user at any time.
Post-action transparency
Every approved action produces a plain-language receipt — what happened, why, and how to undo or adjust it.
Audit trail
Recommendation, confidence, data snapshot, and decision logged as one traceable record per action.
What the product says when it's unsure
"We don't have enough recent data to recommend confidently yet. We're missing a clear view of your regular bills. You can add them now, or hold steady — nothing needs to move today."
Failure handling
- A failed transfer never retries silently — the user sees exactly what didn't complete and why.
- If a recommendation was based on data later found to be wrong, the user is proactively told, not left to notice.
- System outages fall back to the last-known-good state; no approval is ever inferred from stale data.
An instrument, not an interface
The design language is near-monochrome and hairline-ruled: white surfaces, 1px borders instead of shadows, and hierarchy carried by weight and scale rather than colour. Exactly one saturated hue exists in the product, and it belongs to Anchorline — so the agentic layer is never mistaken for the bank.
Design principles
Nothing moves until the user says so — the interface never implies otherwise.
One recommendation at a time. Depth is available, never defaulted to.
The AI's voice is always proposing, never announcing something done.
Reasoning is shown, not sold. No urgency copy, no artificial scarcity.
Momentum is shown as real trend lines, not points, streaks, or badges.
Hairlines and white space over shadow and glow. The one gradient in the system marks Anchorline.
Brand & product adjectives
Colour strategy
The bank is monochrome — paper, ink, and a hairline. Violet is reserved exclusively for Anchorline, which makes AI-authored content self-evident without a single badge. Status colour is a separate semantic layer, never the accent.
Typography strategy
One family, four weights. Instrument Sans runs everything, with hierarchy coming from weight, size and tracking rather than a second typeface. Figures are tabular everywhere so columns of money align; a mono face is held back for reference codes only.
Spacing, layout & iconography
- Base unit — 4px grid, 8px rhythm for component spacing, 24px for section rhythm.
- One idea per screen — a recommendation, a check-in, a decision. Depth sits behind "why" and "details," never inline by default.
- Iconography — single-weight line icons only (1.5–1.6px stroke); no filled glyphs, no coins, rockets, or lightning bolts.
- Corner language — 8–12px radii on cards and controls, 24–34px on device-level surfaces; nothing fully pill-shaped except real actions and toggles.
Motion & component philosophy
- Motion communicates state, not delight — a number settling, a status changing, a panel opening. 150–220ms, standard easing.
- No celebratory animation on money movement; confirmation is calm, not confetti.
- Components are composable "instruments" — cards, panels, and tiles share one elevation language: hairline border first, shadow only at the topmost layer (modals, approval sheets).
- prefers-reduced-motion is honoured everywhere; nothing depends on animation to be understood.
Trust-signalling & accessibility rules
- Every AI-authored element carries a small Recommended mark — never presented as a neutral system statement.
- An explanation ("why") is always adjacent to a recommendation, never hidden behind extra taps.
- Confidence is always visible where an approval is requested — never only in a details screen.
- Status is never colour-only: every pill pairs colour with a word and a dot glyph.
- Text contrast holds WCAG AA minimum (4.5:1 body, 3:1 large text) in both themes.
- Tap targets ≥44×44pt on iOS and tablet; ≥40×40px on web with visible focus rings.
- Approval flows are fully operable and announced via screen reader — amount, action, and consequence read in one pass.
- No information is conveyed by animation or hover alone; every state has a static equivalent.
Content tone & microcopy rules
| Situation | Instead of | Anchorline says |
|---|---|---|
| Debt recommendation | "You're wasting money on interest!" | "Paying the Visa now saves about $47 in interest this month." |
| Low confidence | "We couldn't calculate this." | "We don't have enough recent spending data to recommend confidently yet." |
| Approval CTA | "Optimize now" | "Approve this transfer" |
| Nothing to do | (silence, or a forced tip) | "Holding steady is the right move this week — nothing needs your approval." |
| Missed goal | "You failed to reach your goal." | "You're a little behind pace. Here's one adjustment that gets you back on track." |
Recommendation card — anatomy
- Recommended tagMarks this as AI-proposed, not a system fact.
- Headline actionOne sentence, plain language, the amount and destination.
- One-line rationaleThe "why," always present, never a tap away.
- Confidence chipHigh / Medium / Low, shown at a glance.
- Primary actionsApprove · Adjust · Not now — three ways out, never one.
Approval panel — anatomy
- WhatThe exact action and amount, stated plainly.
- WhyThe reasoning, in the user's terms.
- Data usedWhat inputs influenced this — balances, goals, spend pattern.
- Expected benefit / trade-offWhat improves, and what the honest cost is.
- What happens next & what's editableConfirms this isn't a one-way door.
- Confidence & escalationConfidence level, plus a visible path to a human.
Progress & status visualisation language
Real trend line vs. target line — never a badge or streak count.
Shown with the one action that would restore pace — never alarm-coloured alone.
Framed as an option to redirect surplus, not pressure to "optimize more."
Cross-platform behaviour rules
| Stays constant | Adapts by platform |
|---|---|
| Colour tokens, type roles, iconography, motion timing | Navigation model (tab bar / sidebar / split view) |
| Recommendation & approval panel anatomy (all fields, every field order) | Panel presentation (sheet / modal / inline) |
| The trust rule — recommend, explain, approve | Control density and how much planning depth is shown by default |
| Microcopy voice and terminology | Layout structure (single column / multi-column / master-detail) |
A command centre, not a findings deck
The hub is internal-first — built for product, design, research, and compliance stakeholders to trace every product decision back to evidence, and to see, at a glance, what is known, what is assumed, and what still needs validating.
Research objectives
- Establish what "trustworthy financial guidance" means to a low-confidence retail customer.
- Determine the guidance-vs-control preference distribution across life stages.
- Identify the exact moments explanation is required for approval, vs. optional.
- Validate that trust-led engagement predicts recommendation follow-through better than urgency-based nudging.
Critical unknowns
- Does explanation depth increase approval speed, or slow it past a usable threshold?
- How much does trust decay after one incorrect or poorly-timed recommendation?
- What's the right re-engagement pattern for a user like Marcus who disengages under stress?
- Where is the line between "helpful nudge" and "pressure," in this specific product's voice?
Problem framing & jobs to be done
"Help me know where my next dollar should go, without needing to become a finance expert to trust the answer."
When money moves (payday, a bill, a windfall), tell me the smartest next step and let me approve it in seconds.
When my situation changes, help me re-plan without starting over.
Show me I'm making progress in a way I can believe, not just a number that moved.
Behavioural tensions & trust barriers
| Tension | What's happening | Design response |
|---|---|---|
| Wants help / fears judgment | Users avoid tools that feel like a scorecard on their choices. | Non-evaluative language; momentum framing over comparison. |
| Wants automation / fears losing control | Auto-pilot budgeting apps have burned users with silent changes. | Recommend-then-approve as an absolute rule, always visible. |
| Wants simplicity / needs to trust the math | Oversimplified advice reads as untrustworthy to confident users (Elaine, Devon). | "Why" always available, depth on demand, never forced. |
| Engages when stable / avoids when stressed | Debt-stressed users (Marcus) disengage exactly when guidance matters most. | Low-pressure re-entry points; no guilt-based nudges. |
Evidence types & confidence weighting
| Evidence type | Example | Confidence weight |
|---|---|---|
| Behavioural / transactional data | Actual transfer & approval logs from pilot cohort | High |
| Moderated usability testing | Task-based sessions on approval & explanation comprehension | High |
| Diary studies | Weekly check-in reactions over 6–8 weeks per archetype | Medium |
| Survey / attitudinal | Trust and satisfaction self-report | Medium |
| Expert / heuristic review | Compliance & accessibility audit | Medium |
| Internal stakeholder assumption | Unvalidated product hypothesis | Low — flagged |
Hypothesis tracking
| ID | Hypothesis | Status | Evidence | Linked decision |
|---|---|---|---|---|
| H-01 | Explaining "why" at the point of approval increases approval rate vs. a bare CTA. | Supported | Moderated testing, n=24 | Approval panel anatomy (§03) |
| H-02 | A visible guidance-level toggle increases trust for high-confidence users (Builder, Stabilizer). | Partially supported | Diary study, 2 archetypes | Guidance-vs-control model (§07) |
| H-03 | Debt-stressed users disengage after a single "you're behind" framing. | Supported | Diary study + support transcripts | Reset archetype copy rules (§02) |
| H-04 | Investment layer visibility before debt payoff reduces trust in the recommendation engine. | Unvalidated | None yet — planned study | v1 scope: save/debt first (§01) |
| H-05 | A confidence chip alone (without a number) is sufficient for approval comprehension. | Unvalidated | None yet — planned study | Confidence & explanation strategy (§07) |
Research → decision → solution traceability
| Insight | Product decision | Solution area | Design system rule |
|---|---|---|---|
| Silent auto-changes destroy trust | All meaningful actions require explicit approval | Approval & confirmation flow | Approval panel anatomy |
| Shame language causes disengagement | Non-evaluative, coach-toned microcopy | Weekly progress flow | Content tone rules |
| Confident users distrust oversimplification | "Why" always present, depth on demand | Recommendation flow | Recommendation card anatomy |
| Guidance preference varies widely by archetype | Guided / Balanced / Manual modes | Guided setup + AI logic | Cross-platform control density |
Prioritisation framework
Research and design backlog scored on: Trust Impact × Reach × Evidence Confidence, divided by Effort. Anything touching approval, explanation, or money-movement trust is weighted 2× regardless of score — it is treated as a compliance-adjacent surface, not a growth lever.
Internal stakeholder views
- Product — plan acceptance & follow-through by archetype, prioritisation backlog.
- Design — component-level usability findings, accessibility audit trail.
- Compliance & risk — approval-boundary adherence, audit log completeness, fairness review status.
- Research — hypothesis status, evidence confidence, open validation queue.
Open questions for future validation
- What confidence threshold should suppress a recommendation entirely rather than show it as "low confidence"?
- Does tablet's side-by-side planning view change approval speed or comprehension vs. mobile's sequential flow?
- How should the product reintroduce itself to a user who disengaged for 60+ days during a financial setback?
- What's the right disclosure moment for investment-layer eligibility without it reading as a sales trigger?
Trust is the growth strategy
Anchorline is framed as a trust-led engagement product, not a feature. Every downstream decision — what the AI is allowed to do, what it must explain, what ships in v1 — traces back to this framing.
Strategic frame
- Primary user — mass retail banking customer, low-to-medium financial confidence, broad age range.
- Core job to be done — "Help me make better money decisions without needing expert knowledge."
- Core user value — clear recommendations, visible progress, low effort, confidence, control.
- Core bank value — stronger digital engagement, retention, trust, selective product penetration.
- Experience tone — a smart financial coach. Never a salesperson. Never an overbearing autopilot.
v1 scope discipline
- In scope — savings behaviour, debt payoff efficiency, cash buffer health, goal-based reallocation.
- Secondary layer — investment intelligence, introduced only once saving & debt posture is stable.
- Always required — explicit approval before any meaningful money movement.
- Always available — a manual, non-AI route for every guided action.
- Out of v1 — autonomous execution, product opening, trading, action on low-confidence data.
KPI framework
| Tier | Metric | What it tells the business | What it tells the user |
|---|---|---|---|
| North Star | Trust-led engagement | Customers return because they believe the guidance, not because they're nudged. | "I trust what this tells me." |
| Secondary | Plan acceptance rate | Recommendation quality & explanation clarity are working. | "This actually fits my situation." |
| Secondary | Repeat usage (weekly check-in return rate) | The habit loop is forming without being coercive. | "Checking in feels worth it." |
| Secondary | Recommendation follow-through | Advice converts to real financial behaviour change. | "I did the thing, and it helped." |
| Secondary | Satisfaction & reduced effort | The product is lowering cognitive load, not adding to it. | "I didn't have to think hard about this." |
| Secondary | Selective product adoption | Trust converts into deeper banking relationships, earned not pushed. | "This felt like the right next step, not a pitch." |
Five people, one trust model
Anchorline's guidance logic flexes by life stage and confidence level, but the trust rule never does. These five archetypes anchor every design and AI-logic decision in the rest of this package.
The Starter
- Context
- First full-time income, $6.2k student debt, $310 average balance, irregular saving.
- Pain
- Doesn't know what "good" looks like; associates budgeting apps with being told off.
- Goals
- Build a starter buffer, stop overdraft anxiety, understand her own spending.
- Guidance
- Guided — wants the app to decide the mechanics, not the values.
- Behaviour
- Checks balance often, avoids anything that feels like a lecture, responds to small wins.
The Stabilizer
- Context
- Stable income, growing savings across 3 uncoordinated goals (trip, house, buffer).
- Pain
- Money is scattered across goals with no logic; unsure if allocation is optimal.
- Goals
- Coordinate goal priority, house down payment on a clear timeline.
- Guidance
- Balanced — wants recommendations, but expects to adjust the logic.
- Behaviour
- Uses payday reallocation heavily; compares scenarios before approving.
The Anchor
- Context
- Two kids, mortgage, childcare, RESP contributions; tight monthly slack.
- Pain
- No time or energy for financial admin; one mistake feels costly.
- Goals
- Protect the buffer, keep RESP on track, avoid new debt.
- Guidance
- Guided — values reassurance and simplicity over control.
- Behaviour
- Engages weekly at most; wants confirmation nothing has gone wrong.
The Reset
- Context
- Income drop, $14k high-interest debt across two cards, depleted buffer.
- Pain
- Feels behind and judged by every finance product he's used.
- Goals
- Stop the bleeding, rebuild a minimal buffer, a believable debt path out.
- Guidance
- Guided, cautious — needs stabilization before optimization.
- Behaviour
- May avoid the app when anxious; needs re-engagement without guilt.
The Builder
- Context
- Debt-free, healthy buffer, saving basics covered; underusing investment capacity.
- Pain
- Unsure if she's "doing enough"; existing tools feel either too basic or too salesy.
- Goals
- Confirm she's on track for retirement horizon; grow beyond savings.
- Guidance
- Manual-leaning — wants scenario tools and explainability more than automation.
- Behaviour
- Uses web/tablet for deeper planning; low tolerance for oversimplified advice.
Three journeys, optimised deliberately
These are the only three journeys the v1 product is designed to be excellent at — everything else in the IA supports them.
1 · Guided setup into a smart allocation plan
Context
Income, balances, debts, and existing goals — pulled where possible, confirmed by the user.
Priorities
User ranks goals and sets time horizon and risk comfort.
Guidance level
Guided, Balanced, or Manual-leaning — changeable anytime.
First plan
A full allocation plan shown with the standard explanation anatomy.
Approve or adjust
Nothing activates until approved; manual edit is always available.
2 · Weekly progress check-in and adjustment
Status summary
On-track / at-risk / ahead, for each goal, debt, and the buffer.
What changed
Spending behaviour shift explained in plain terms, not just a number.
One next-best action
A single recommendation, not a list — with full explanation anatomy.
Approve, adjust, or hold
"Holding steady" is a valid, clearly stated outcome.
3 · Reallocation during a moment of change
Trigger detected
Payday, a new expense, or a goal edited by the user.
Re-run priority order
Buffer → debt → goals → investment, recalculated against new context.
Explain what changed
Why this differs from last week's plan, in one line.
Approve the adjustment
Same anatomy, same standing rule — no shortcuts for "small" changes.
One system, mapped
How the bank's own IA is organised, and how the three parts of this package feed each other — not as a metaphor, but as the literal flow of information from evidence to language to live product.
…and the app's real usage data feeds back into the Research Hub as new evidence — closing the loop.
- Homeoverview & next action
- Anchorline hub always first
- Quick actions
- Banking · Credit · Investments · Borrowing
- Move money
- Interac e-Transfer
- Pay a bill
- Between my accounts
- Deposit a cheque
- Anchorlinethe agentic layer
- Active recommendation
- Allocation plan
- Weekly progress
- Decision history
- Investments
- TFSA · RRSP · RESP
- Contribute
- GICs · Portfolios & funds
- Cards
- Card detail & statement
- Make a payment
- Cash back · Lock card
- Mortgage & loans
- Mortgage detail · lump sum · renewal
- Home Equity Line
- Credit score
- More
- Rewards · Statements · Alerts
- Security centre
- Branch/ATM · Insurance · Contact
- Settings — incl. guidance level
Where Anchorline attaches to the bank's IA
| Bank surface | Anchorline's presence | Why here |
|---|---|---|
| Home | Full recommendation hub, pinned above everything | The decision is the point of the session, so it leads. |
| Global navigation | Centre tab (mobile) · pinned sidebar slot (web) · floating button everywhere | Never more than one tap from any screen in the bank. |
| Accounts & savings | Inline card on buffer status | The buffer is the first thing the priority order defends. |
| Credit cards | Inline card quantifying interest saved | Highest-APR debt is the highest-return move available. |
| Investments | Inline card explaining why investing is gated | Explaining a withheld suggestion builds more trust than making one. |
| Mortgage & loans | Inline card explaining why it's untouched | Low-rate debt should not be prepaid ahead of a 22.9% balance. |
| Credit score | Inline card on utilisation impact | Connects an abstract score to the concrete action on the table. |
| Pay-your-Visa flow | Preset amount + rationale inside the flow | Guidance where the number is actually chosen, not after. |
The families that build every screen
| Family | Purpose | Key states | Governed by |
|---|---|---|---|
| Recommendation card | Present one AI-proposed action | Default, low-confidence, approved, declined | Recommendation anatomy (§03) |
| Approval panel | Full explanation before money moves | Reviewing, confirming, confirmed, escalated | Approval anatomy (§03) |
| Status pill | Encode on-track / at-risk / ahead / confidence | Good, watch, risk, accent | Progress language (§03) |
| Stat tile | Show one figure with its label, tabular-numeral set | Default, trending up/down | Typography strategy (§03) |
| Explanation panel | Persistent "why" — data, benefit, trade-off, confidence | Inline (mobile/tablet), persistent (web) | Approval anatomy (§03) |
| Waterfall allocator | Show buffer → debt → goals → investment split | Recommended, user-adjusted | AI priority order (§07) |
| Progress trend | Real line vs. target, not a badge | On-track, at-risk, ahead | Progress language (§03) |
| Guidance-level selector | Guided / Balanced / Manual-leaning | Selected, changed-this-session | Guidance model (§07) |
| Escalation entry point | "Talk to someone," context-carrying | Default, in-progress handoff | Trust & governance (§08) |
What ships in v1
Every screen below is built and interactive in the prototype unless marked as an entry point. Entry points render a real, labelled destination but stop short of a completing flow.
| Screen | iOS | Web | Tablet | States covered |
|---|---|---|---|---|
| Home / overview | ✓ | ✓ | ✓ | Pending · approved · held |
| Anchorline hub | ✓ | ✓ | ✓ | Recommend · adjust · approved · held · escalated |
| Allocation plan | ✓ | ✓ | ✓ | Locked / unlocked investing layer |
| Weekly progress | ✓ | ✓ | ✓ | On-track · at-risk · ahead |
| Accounts list & detail | ✓ | ✓ | ✓ | Bank · registered · credit · loan |
| Interac e-Transfer | ✓ | ✓ | ✓ | 4 steps · autodeposit vs. security question |
| Pay a bill | ✓ | ✓ | ✓ | 4 steps · today vs. due date |
| Transfer between accounts | ✓ | ✓ | ✓ | 3 steps |
| Contribute (TFSA/RRSP/RESP) | ✓ | ✓ | ✓ | 4 steps · room tracking · CESG |
| Credit card & payment | ✓ | ✓ | ✓ | 3 steps · min / recommended / full |
| Mortgage & loans | ✓ | ✓ | ✓ | Default |
| Credit score | ✓ | ✓ | ✓ | Default · utilisation change |
| Activity | ✓ | ✓ | ✓ | Live — reflects every completed flow |
| Deposit a cheque | Entry point | Entry point | Entry point | — |
| Rewards · Statements · Alerts · Security | Entry point | Entry point | Entry point | — |
| Branch/ATM · Insurance · Contact · Settings | Entry point | Entry point | Entry point | — |
States that must exist, not just the happy path
| State | What the customer sees | What Anchorline does |
|---|---|---|
| Empty | "Let's set up your plan — it takes about 4 minutes." | Nothing yet; offers a guided or manual setup entry. |
| Loading | A calm, static skeleton — no spinner tricks or fake progress. | Computing against current data; no partial numbers shown. |
| Error | Plain explanation of what failed and what still works. | Falls back to last-known-good; never silently retries an approval. |
| Low confidence | "We don't have enough recent data to recommend confidently. Here's what's missing." | Abstains from a number; offers the smallest safe action or a data prompt. |
| Decision held | "Nothing needs your approval" — with the cost of holding stated plainly. | Stops asking until the next payday trigger. No nagging. |
How success is actually measured
| Metric | Definition | Target signal | Source |
|---|---|---|---|
| Trust-led engagement | Return usage correlated with approval rate, not session count alone | Rising together, not diverging | Product analytics + approval log |
| Plan acceptance rate | % of recommendations approved as-is or with minor adjustment | >60% by month 3 | Approval log |
| Repeat weekly check-in rate | % of users returning for the weekly progress flow | >50% week-over-week | Product analytics |
| Recommendation follow-through | % of approved actions still in effect 30 days later | >80% | Transaction data |
| Satisfaction / effort | Post-approval micro-survey, effort & trust framing | CSAT ≥4.3/5, low-effort ≥70% | In-product survey |
| Selective product adoption | Adoption of a recommended product only after guidance history exists | Directional, not pushed | CRM + approval log |
| Escalation rate & resolution | % of sessions escalating to a human, and time to resolve | Low volume, high resolution quality | Support system |
What this concept doesn't yet know
| Risk / gap | Why it matters | Mitigation | Priority |
|---|---|---|---|
| Confidence threshold is not yet empirically calibrated | Wrong threshold either over-abstains (erodes usefulness) or under-abstains (erodes trust) | Controlled pilot with graduated thresholds, H-05 | High |
| Re-engagement pattern for disengaged, stressed users unvalidated | The Reset archetype is highest-need and highest-churn-risk | Diary study + support transcript analysis | High |
| Investment-layer disclosure timing untested | Risk of reading as a sales trigger, damaging trust built on save/debt guidance | H-04 validation study before layer ships | Medium |
| Fairness review across archetypes not yet run on live logic | Recommendation logic could disadvantage a specific income or life-stage pattern | Formal fairness audit before GA, owned by compliance | High |
| Tablet split-view approval speed unmeasured | Side-by-side comparison could speed or slow comprehension vs. sequential mobile flow | Comparative usability test, both layouts | Medium |
| Escalation handoff context-completeness unverified end-to-end | If context doesn't reach the human agent, the trust promise breaks at the exact moment it matters most | End-to-end handoff test with support ops | High |