Find the payments revenue leaks before they cost you.
Bicycle watches approval rate, interchange, payment success, settlement, and processing KPIs across the segments that matter. When a number moves, it explains the likely cause and recommends the next action to the team that can fix it.
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- 1Transactions downgrading on missing tax amounthigh
- 2Card-hierarchy level transition on this MCCcontributing
- 3AVS data failing to pass on the gateway feedcontributing
A dashboard shows the drop. Bicycle finishes the investigation and recommends the fix.
Start with a single revenue KPI critical to your business.
Bicycle comes with payments industry intelligence already inside. Pick one Bicycle-recommended KPI and watch it run: the KPI it watches, the causes it checks, the action it recommends to the owner, and what it keeps.
A payments problem not listed here? Book a demo and we will map it.
A dashboard shows the drop. It never finishes the investigation.
Approval rate drops. The manual chase begins.
The dashboard shows the decline. The team still checks issuers, gateways, routing, settlement, and BIN patterns by hand, across five tools and four people.
- Risk team checks top BINs
- Payment ops checks gateway health
- Engineering checks routing and retries
- Analytics pulls issuer and region cuts
- Ops argues over who owns the fix
Bicycle starts the investigation the moment the KPI moves.
It detects the drop, ranks the affected BINs and issuers, tests business and technical causes in parallel, attaches the evidence, and routes the issue to the owner with the next step.
- Detect the movement, ranked by impact
- Test business and technical causes together
- Attach the evidence, rule out the rest
- Route the safe action to the owner
- Learn the accepted cause for next time
Trained on the KPIs, patterns, and root causes of payments.
Six capabilities, set up once and run continuously. Business teams move faster, analysts keep governance, everyone trusts the number. Pick one to go deeper.
Multi-factor cause analysis
"What caused this?" turns into a three-day Slack thread across data, product, ops, and engineering, and the answer still arrives without evidence.
What Bicycle does
Open the cause summary. Ranked business and technical causes. The likely driver is named, with confidence and impact.
See the evidence. Logs, deploys, pricing changes, supplier behavior, and search relevance, with the data attached.
Know what was ruled out. The negative findings close the debate before it starts.
What it looks like for your team
When a rate spikes, the team sees the specific qualification gap, AVS failure, missing tax amount, or wrong hierarchy level, not just the aggregate move.
Capabilities work together in one continuous loop. Detect → Explain → Act → Learn.
Business teams need answers fast. Analysts ensure conclusions are trustworthy.
Same governed intelligence underneath. The payments agent for the teams who own the number, the controls for the team who owns the data.
See what changed, why, and what is safe to do.
The move finds you, ranked by revenue impact, with the cause and the next step attached. No dashboard hunt, no three-day ticket.
Govern the definitions, evidence, and safe actions.
Analysts review first-pass causes instead of rebuilding them. Leaders give the business self-service inside one governed boundary.
The agentic analytics layer on top of your stack.
Your stack stays the system of record. Bicycle turns payments signals into alerts, triage, stories, dashboards, chat, and governed actions on top of it. No rip-and-replace.
Frames the question, orchestrates the investigation, writes the story, recommends the next step. It reasons.
Detects movement, ranks drivers, computes confidence, forecasts. The numbers are calculated, not generated.
And the rest of what you run: settlement data · processor feeds · auth results · fraud signals · observability · Slack
Bicycle runs on top of your existing systems. The payments pack supplies the starting KPIs, causes, stories, and action paths.
How is Bicycle different from what a payments team already runs?
Dashboards are useful for overall payment trends, reporting, executive summaries, and recurring visibility. Bicycle complements dashboards: the dashboard tells you approval rate dropped; Bicycle tells you why and what to do next.
| What the tool does after a KPI moves | Dashboards | AI chatbots | Warehouse AI | Bicycle |
|---|---|---|---|---|
| Notices the move without being asked | Only when someone opens the right view. Thresholds fire on the total, not on one issuer or one BIN. | No. Someone has to suspect the drop and phrase the question first. | Queries can be scheduled on warehouse tables. You build and tune the detection yourself. | Watches approval rate, payment success and interchange continuously, down to issuer, BIN, merchant, gateway and model version. |
| Ranks the likely causes | No. The chart shows the decline. Issuers, gateways, routing, settlement and BIN patterns are still checked by hand, across five tools and four people. | Generates a plausible explanation. Tests no drivers in parallel and rules nothing out. | Writes the query once you decide which metric, which window and which drivers to ask about. | Tests issuer behavior, gateway degradation, model version, 3DS step-up and cohort shift in parallel, ranked by revenue impact. |
| Shows the evidence, and what it ruled out | The underlying views are there. Assembling them into an explanation is manual. | No lineage attached, so teams quietly re-check the number in a spreadsheet. | The SQL is visible. Gateway and issuer signals outside the warehouse are not. | Definition, lineage, source query and the drivers ruled out, attached to the finding. |
| Recommends the next step, and who owns it | No. At best a link through to another view. | Stops at the answer. Choosing and routing the next step stays with the reader. | A warehouse computes. It does not act. | Recommends the next step to the payments or risk owner, with the affected BINs, issuers and estimated revenue impact. |
| Keeps the action governed | Read-only, so there is nothing to govern. | Where actions exist at all, they sit outside scope, approval and rollback. | No governed path to Slack, a ticket, or a rollback. | Every action scoped, previewed, approved, reversible and logged. |
Bicycle runs on top of the stack you already report from. Your dashboards, warehouse and BI stay the system of record.
Building it yourself is the fourth option. What the other 90% costs →
Start with one KPI in your payments stack.
Bring one revenue-critical KPI, connect a trusted source, and watch Bicycle turn a prompt plus your data into a payments analytics agent. Zero to a working agent in about 15 minutes.
Grow into the full product when your team is ready.
How does a payments team find out why approvals dropped?
Bicycle watches payments KPIs continuously and catches a drop on one BIN range, issuer or lane before the overall rate moves. It tests issuer, provider and data-quality causes together, names the likely one with the evidence attached, and says what it ruled out. Bicycle recommends the next step; payments ops approves it.
Approval logs, payment attempts, auth results, gateway and processor data, settlement and interchange feeds, read where they already sit. Bicycle connects rather than migrating. One revenue-critical KPI, and a trusted source for it, is enough to begin.
Processor and gateway feeds, auth and settlement data, interchange and scheme fee statements, card hierarchy and AVS, plus the warehouse you already report from. Nothing moves, and your stack stays the system of record.
Days. Approval rate, interchange qualification, BIN, merchant, card type and settlement are modelled as first-class concepts before you start, so setup is reviewing definitions rather than writing them. You approve, edit or reject every suggestion.
You do. When approval rate or effective interchange moves, Bicycle recommends the next step to payments ops or engineering, with the BIN range, the merchant and the revenue at risk attached. Every action is scoped, previewed and logged.
Bicycle watches approval rate, interchange, payment success, settlement and processing cost. Most teams start with the one that leaks quietly: effective interchange, where transactions downgrade on missing data and the cost only surfaces once the statement lands.
Test ride Bicycle on a payments KPI.
Bring one KPI that matters. We will show how Bicycle detects the move, explains the cause, and recommends the next step on top of the stack you already run.
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