Every Dollar is a Decision
Not every customer, product, or market is profitable β but the patterns that separate them are buried in millions of transactions, balances, and behaviors no reporting team has time to read. AI can read them.
What follows is what your bank looks like when it does...
Book a Discovery CallProfitability Intelligence Demo
The bank is fictitious. The data is not. AI recognized the patterns and benchmarks inside real banking data and rebuilt them as 40,000+ account-level profit records β every margin, cost driver, and relationship below behaves the way a real bank behaves.
Click through the live dashboard below, CEO to Relationship Banker. Every view drives a different decision from the same source.
Now imagine what we could do with your live data.
Wise Bank — Where the Quarter's Profit Came From
The anchoring view: overall profitability, its sources, and the short list of items worth leadership attention.
Profit Waterfall — Total Bank iWhat it shows: how the quarter's profit is built β Net Interest Margin, Fee Income, then Cost to Serve, Overhead, and Provision. Toggle between the total bank and each book: within-book economics drive decisions, not cross-book comparison.
Decision it drives: the one-chart answer to "how did we make money this quarter?"
Balances by Customer Segment iWhat it shows: each segment's balance footprint, stacked by deposit vs. loan balances. Consumer segment labels in navy, business in red.
Decision it drives: where the balance sheet actually lives β the scale context behind every profitability conversation.
Hover a bar for that segment's profit split.
Profit Flow — Revenue to Economic Value iWhat it shows: the quarter's full profit flow in one picture β each market segment's revenue by type, merged into Total Revenue, distributed to the five cost components and Profit, with Profit resolving into the Capital Charge and Economic Value Added.
Decision it drives: the one-chart narrative of where every revenue dollar went β the anchor for the deeper cuts on every other tab.
Where our customers revenue becomes economic value.
AI-Derived Actions to Review iWhat it shows: the highest-signal findings across the whole ledger, each phrased as a decision to review β not a conclusion. Every number is computed directly from the quarter's data; confidence and readiness are stated on each item.
Decision it drives: the leadership agenda. Humans own accountability; the analysis recommends.
Is the bank earning its cost of capital — and where isn't it?
From reported profit to economic value: the same ledger, carried through tax and a capital charge at the stated hurdle.
Profit-to-EVA Waterfall — Deposit Book iWhat it shows: the path from net interest margin to economic value added within the selected book β revenue, cost to serve, overhead, provision, tax, and the charge for capital at the 10% hurdle.
Decision it drives: within-book economics β which levers move this book's value, on its own terms rather than blended with the other side of the balance sheet.
Hover any bar for the running total.
Capital vs. Economic Return — Deposit Book iWhat it shows: each product in the selected book plotted by the capital it consumes (x) against the economic value it produces (y). Products below the zero line earn less than the 10% hurdle on their capital.
Decision it drives: which products in this book to lean into, and which need repricing or runoff to release capital.
Bubble = product. Hover for capital composition.
EVA by Segment iWhat it shows: economic value added by customer segment after the capital charge β consumer segments in navy, business segments in red.
Decision it drives: segment strategy and capital allocation between the consumer and business franchises.
EVA by Branch — Deposit vs. Loan Share iWhat it shows: each branch's economic value added, stacked by where it comes from β the deposit book vs. the loan book.
Decision it drives: the intervention list, with the diagnosis built in: a weak branch with a strong deposit stack has a lending problem, and vice versa.
Funding vs. Lending Engine iWhat it shows: how net interest margin splits between the deposit franchise (FTP credit for the funding it provides, minus interest paid) and the loan book (interest earned, minus FTP charge for funds used).
Decision it drives: whether deposit gathering or lending is actually the margin engine β informs rate-setting posture on both sides.
Cost Allocation Layers iWhat it shows: the three cost layers by product family β direct activity-based cost to serve, allocated unused capacity (paid-for capacity the activity didn't consume), and allocated overhead.
Decision it drives: whether the allocation basis is defensible β and separately, whether unused capacity is a pricing problem or a capacity-management problem.
Where do I grow, fix, or exit?
Segment-first economics for the retail and business bank. Select a segment to re-cut every panel below.
Segment P&L Matrix iWhat it shows: the standard profit breakdown β Balance | Net Interest Margin | Fee Income | Cost to Serve β for every segment side by side. Selected segment highlighted.
Decision it drives: which segments fund the franchise vs. consume it; where coverage and pricing attention concentrate.
Product Profit Pareto — iWhat it shows: products ranked by profit contribution within the selected segment, with cumulative share.
Decision it drives: the short list of products that deserve pricing and process attention in this segment.
Channel Cost Mix by Segment iWhat it shows: activity-based channel costs (teller, ATM, electronic, wire, statement, card) per segment.
Decision it drives: where channel-migration campaigns would actually move cost β which segments are branch-heavy vs. digital.
Business vs. Consumer Contribution iWhat it shows: balance, profit, and servicing cost split between business and consumer customers.
Decision it drives: whether the small-business book justifies dedicated coverage investment.
Branch Economics iWhat it shows: every branch ranked by profit, with EVA beside it. Sortable.
Decision it drives: the underperformer intervention list.
| Branch | Balance | Net Interest Margin | Fee Income | Cost to Serve | Profit | EVA | Accounts |
|---|
Is each product priced for what it actually costs?
Activity-based unit economics — eight real cost components per product, not a blended average.
Activity-Based Cost Stack iWhat it shows: the eight measured cost components for this product β origination, maintenance, teller, ATM, electronic, wire, statement, card. These sum exactly to cost to serve; allocated overhead is shown separately and deliberately.
Decision it drives: fee schedule design β which activities to reprice, digitize, or discourage.
Volume Drivers iWhat it shows: the transaction activity behind each cost component. Hover a bar to see the implied unit cost (component cost ÷ driver volume).
Decision it drives: which behaviors to migrate β e.g., teller-to-electronic β and what each migration is worth.
Product Profit Waterfall iWhat it shows: how the selected product's profit is built β Net Interest Margin, Fee Income, then Cost to Serve, Overhead, and Provision.
Decision it drives: which lever moves this product's P&L β pricing (NIM), fee schedule, or cost engineering.
Rates for context:
Unit Economics by Segment iWhat it shows: for the selected product, each customer segment plotted by cost to serve per account (x) vs. revenue per account (y). Bubble size = number of accounts; navy = consumer segments, red = business. Segments below the break-even diagonal cost more to serve than they earn.
Decision it drives: segment-level pricing and channel strategy for this product β who subsidizes whom inside the same product.
Product Detail Table
| Product | Balance | NIM | Fee Income | Cost to Serve | Rev / Acct | Cost / Acct | Profit | Accounts |
|---|
Is our acquisition spend buying profitable relationships?
Cohort economics for the quarter's new accounts, plus the engagement white space in the existing book.
New vs. Established Unit Economics iWhat it shows: revenue, cost, and profit per account for the quarter's new accounts vs. the seasoned book.
Decision it drives: onboarding funnel design β and honest framing: one quarter cannot distinguish "unprofitable" from "not yet seasoned."
Where New Accounts Landed iWhat it shows: new-account count by segment (bars) vs. each segment's share of total bank profit (line).
Decision it drives: targeting β are we acquiring in the segments that actually pay?
Card Activation Opportunity iWhat it shows: the red line is the share of card-capable accounts actually active this quarter (left axis); the grey bars are what each active account generates in interchange (right axis). A low line next to a tall bar is the opportunity: many dormant accounts, each worth real revenue if activated.
Decision it drives: activation campaign sizing and targeting β dormant interchange revenue, quantified per segment.
Fee Income Penetration by Segment iWhat it shows: fee income per account by segment, split by source, plus the share of accounts generating no fee income at all.
Decision it drives: cross-sell and bundling campaign design.
New Account Detail by Product
| Product | New Accounts | Balance Gathered | Quarter Profit |
|---|
Which relationships deserve my next hour?
Relationship-level economics with account drill-down to a full profit statement — and the talking points pre-loaded.
Account Profit Statement iWhat it shows: the full account-level statement β Net Interest Margin (balance & rate, interest and FTP sides), Fee Income by source, Cost to Serve with volume and measured cost per driver, then overhead and provision to reconcile to Profit. Expected loss appears only in the risk context, never in the P&L.
Decision it drives: pricing-exception and renewal conversations backed by actual economics.
Click an account row in the relationship above to load its statement.
You've just explored AI4Finance in action.
Your team already knows the bank. AI supplies the acceleration. Together, these capabilities go live in weeks, not months.
Let's discuss bringing these capabilities to your bank
Give us a call β we'll bring a working profitability model of your bank to a Discovery Workshop, built the same way this demo was, and spend the session on how your team builds these capabilities in weeks, not months or years.
The Call
Thirty minutes, your questions, no deck. Tell us where profitability visibility breaks down today β pricing, segments, branches, or capital. We'll show you these capabilities are within reach, in both time and cost, for a bank your size.
The Workshop
Your bank's data, modeled and in front of your executive team. We prioritize the use cases against your actual economics β not hypotheticals β and leave you with a clear picture of what decision-ready looks like for your institution.
The Build
Accelerated deployment on proven architecture, run alongside your team until they own it. Your people, your platform, your capability β with AI supplying the acceleration. In weeks, not months or years.
About Armada
Twenty-five years of profitability intelligence for some of the largest banks in the world. Now, AI lets us bring that same depth β the methodology, the judgment, the decision discipline β to banks of every size, at a speed and cost that were never possible before.