For investment bank sales desks
Every salesperson, client and product, from Japan to Australia or New York to London, rolled up to the numbers you already report. Ask where wallet share is below benchmark and get the clients, the products and the figure, with nothing invented.
Regions, products and sub-products are configuration, not code. The roll-up is asserted on every refresh: desk equals regions equals salespeople equals clients, to the penny.
Your revenue against the client's estimated wallet, by product line, ranked by the gap.
Who covers what, who is thin, and what the thin patch is worth against benchmark.
"Which clients grew in rates but not credit?" Answered from your rows, with the rows shown.
Three steps, in this order.
Revenue by client ID, product and salesperson, plus your benchmark file.
We assert every level against the reported total before anything is shown.
Each salesperson sees their book. The desk head sees the ranked gaps.
Short answers. The Help centre has the long ones.
No. Covirage works on client IDs and figures. The name mapping stays in your systems, and the platform can run inside your own tenant.
Any benchmark you hold as a file: Coalition Greenwich, McLagan, Tricumen or an internal one. It is reconciled to the same client IDs.
Your CRM shows activity. Covirage shows share: revenue against wallet, by client and product, with an assistant that answers follow-ups from the same figures.
Analytics software for investment banking, compared · Alternatives to named products
Written for this desk: the measures, the data you already hold, and the arithmetic.
How an investment bank's coverage group manages a banker's departure or move from the coverage file and the contact log: the clients whose last contact was with the departing banker, the days since any other banker touched them, the fee wallet at risk, the handover list ranked by it, and the ninety-day check that says which clients the new officer has actually met.
16 Sept 20262 min readHow an investment bank's coverage group estimates each client's total fee wallet across products from deal data and its own fee ledger, computes the bank's share per client per product, sets the expected share from clients where the bank is a lead relationship, and ranks the clients whose wallet is largest and whose share is lowest, with the product where the gap sits.
16 Sept 20263 min readWhy a bank's league table position by product describes the market and not its clients, how to compute the bank's rank within each covered client's own fee wallet from public deal data and the fee ledger, the clients where the bank is top-three in the market and fifth at the client, the sector teams whose client ranks lag their market ranks, and the list of clients where one product mandate would move the bank from fifth to second.
16 Sept 20263 min readHow an investment bank's coverage and product groups measure pitch-to-mandate conversion from the pitch log and the mandate register: pitches made per sector team and product, mandates won, conversion by count and by estimated fee, the senior hours per pitch from time or calendar records, fees won per senior hour by cell, and the sectors and products where the bank pitches most and wins least.
16 Sept 20263 min readA checklist for the quarter-end reconciliation between an investment bank's sales desk roll-up and the revenue it submits to its benchmark provider: product mapping, client mapping, period cut, joint coverage and the variance report that turns three weeks of email into one page.
16 Sept 20263 min readHow an investment bank's institutional sales desk measures coverage from its own revenue and contact data: which clients each salesperson reaches, which products each client trades with the desk, and the roll-up that reconciles to the benchmark submission.
16 Sept 20264 min read