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An institutional trading business dashboard organizes client inquiries, executed flow, and relationship coverage for a desk review. Follow a worked example from inquiry, trade, revenue, and contact exports, with reconciliation checks and a coverage-only variation.
An institutional trading business dashboard compares client inquiries, executed flow, and relationship coverage by desk and product. It helps sales and trading managers decide which client situations need review and who should follow up. Its figures should come from a defined export cutoff, with business activity and coverage shown separately.
Put a short desk summary above client-product rows. The summary answers how much business the desk saw and executed. The rows identify clients with weak conversion, meaningful activity, or an overdue coverage obligation.
| Review question | Measure | Source file | Review owner |
|---|---|---|---|
| Are inquiries turning into trades? | Won inquiries / eligible inquiries | Inquiry outcomes | Sales and trading heads |
| Are we executing the larger requests? | Executed / requested notional | Inquiry export and matched blotter | Desk manager |
| Which relationships generate business? | Attributed client revenue | Approved revenue export | Finance and sales head |
| Who needs a coverage follow-up? | Eligible relationships outside cadence | Contact export and client roster | Coverage manager |
The existing client KPI catalog for sales and trading desks owns the broader measure definitions. This page brings selected measures together for a business review; institutional trading revenue analysis handles the revenue explanation in depth.
Use a unique inquiry ID, client ID, product, desk, requested notional, currency, outcome, and inquiry date. Match executions through inquiry and trade references. Keep trade status so corrected or canceled bookings do not become extra economic flow.
FINRA describes TRACE as its mechanism for reporting over-the-counter transactions in eligible fixed income securities. That transaction focus is why a desk needs its own inquiry records to measure opportunities that did not become executions.
Use consistent quantity definitions. FINRA Rule 6730 specifies transaction size and other trade-report fields, and generally uses par or principal value for eligible securities other than securitized products. The example below uses USD bond par value throughout; market value, revenue, and risk exposure remain separate measures.
Covirage is not affiliated with FINRA.
Consider an illustrative US broker-dealer, Westbridge Securities, reviewing September 2026. Its fixed income desk has three eligible client-product relationships. Each client appears in one product here, so relationship counts also equal unique client counts.
The period contains only closed inquiries. Won means the inquiry led to an execution with the desk; lost means a confirmed execution elsewhere; passed means the desk declined. These categories are mutually exclusive, and this example has no unresolved or unclassified inquiries.
| Client | Product | Inquiries | Won | Lost | Passed |
|---|---|---|---|---|---|
| Alder Asset Management | Investment-grade corporate bonds | 40 | 12 | 20 | 8 |
| Beacon Pension Trust | High-yield corporate bonds | 30 | 12 | 12 | 6 |
| Cedar Insurance | Agency bonds | 30 | 6 | 18 | 6 |
| Total | 100 | 30 | 50 | 20 |
All matched executions fall within the inquiry review population. Multiple fills count as one won inquiry, while their executed notionals are added once. The revenue column comes from finance's approved client attribution rather than an assumed spread applied to notional.
| Client | Requested par (USD) | Executed par (USD) | Revenue (USD) | Last qualifying contact |
|---|---|---|---|---|
| Alder | 100,000,000 | 24,000,000 | 120,000 | September 18, 2026 |
| Beacon | 60,000,000 | 18,000,000 | 90,000 | September 24, 2026 |
| Cedar | 40,000,000 | 8,000,000 | 40,000 | August 20, 2026 |
| Total | 200,000,000 | 50,000,000 | 250,000 |
For this review, the desk's documented cadence requires a qualifying two-way contact during September. Routine distribution messages do not qualify. The contact cutoff is September 30, 2026, and each relationship has an assigned coverage owner.
Count conversion = Won inquiries / Eligible inquiries
Notional conversion = Matched executed par / Requested par
Coverage compliance = Relationships meeting cadence / Eligible relationships
| Client | Count conversion | Notional conversion | Coverage met? |
|---|---|---|---|
| Alder | 12 / 40 = 30.0% | 24,000,000 / 100,000,000 = 24.0% | Yes |
| Beacon | 12 / 30 = 40.0% | 18,000,000 / 60,000,000 = 30.0% | Yes |
| Cedar | 6 / 30 = 20.0% | 8,000,000 / 40,000,000 = 20.0% | No |
| Total | 30 / 100 = 30.0% | 50,000,000 / 200,000,000 = 25.0% | 2 / 3 = 66.7% |
Percentages are rounded to one decimal place. Total conversion divides total numerators by total denominators. It is not an unweighted average of client percentages.
Cedar has a coverage exception and the lowest conversion in this small review population. Assign its coverage owner to inspect the inquiry outcomes and arrange appropriate follow-up. The figures do not prove that missed contact explains its conversion: products and client demand differ.
Alder and Beacon account for $120,000 + $90,000 = $210,000 of revenue. Revenue attached to relationships meeting cadence is therefore $210,000 / $250,000 = 84.0%. Keep that weighted measure beside relationship-count coverage; it answers a different management question.
Change only Cedar's last qualifying contact to September 29, 2026. Its relationship now meets the stated cadence. Everything in the inquiry, execution, and revenue exports remains unchanged.
Coverage becomes 3 / 3 = 100.0%, up from 66.7%. Revenue attached to covered relationships becomes $250,000 / $250,000 = 100.0%. Count conversion remains 30.0%, notional conversion remains 25.0%, and attributed revenue remains $250,000.
The coverage exception closes because the documented activity changed. There is no recorded improvement in executed business. This separation prevents a busy contact calendar from being read as evidence of stronger commercial results.
Prove the outcome identity first: 30 won + 50 lost + 20 passed = 100 inquiries. Reconcile executed par to the matched client blotter and revenue to finance's total. Unmatched executions need investigation before a conversion ratio is accepted.
Use business dashboard examples for other management audiences, and the quiet client analysis when the question is a change against a client's own activity history.
Bring your inquiry, execution, approved revenue, and coverage exports to Covirage; it maps the columns, and its tools compute and check the figures for the supplied review period. The external AI model explains the business differences with every figure traced to its rows. Create a free Covirage account and bring a sample of your own data.
See Covirage for trading teams for the supporting workflow.
Show client and product inquiry counts, won inquiries, requested and executed notional, attributed revenue, and coverage exceptions. Keep the reporting cutoff and definitions visible. Give each exception an owner so the review produces a relationship or execution follow-up.
Trade data describes executions, while inquiry conversion requires the desk's eligible inquiry population, including inquiries that did not become trades. Use the inquiry export as the denominator and match executions back to it. Public market activity alone cannot establish the desk's conversion rate.
No. Contact recency shows whether the agreed coverage cadence was met. Revenue also depends on client demand, product activity, pricing, and execution outcomes. Review contact exceptions alongside flow, then investigate changes without assuming that a recorded contact caused a trade.