Blog · Wallet share and penetration · Investment banking
How 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.
A coverage banker knows the fees the bank earned from a client. What they estimate in their head is the fees the client paid everyone. Deal data makes that estimate explicit, per product, and the difference between the two is the wallet the bank is not in. This guide sets out the fee wallet, the share, the expected share from the bank's own lead relationships, and the list.
Per client, per product, per period:
Fee wallet = Σ deals × fee assumption for the product and size band Share = the bank's fees ÷ fee wallet Gap = expected share × fee wallet − the bank's fees
Across products:
client fee wallet = Σ products
Client identifiers only.
Among clients in the same sector and size band where the bank is a lead relationship: the median share per product. That is what the bank achieves with clients it covers well, and it is the norm for the ones it does not.
One sector, this year.
| Client | Fee wallet | The bank's fees | Share | Expected | Gap | Largest gap product |
|---|---|---|---|---|---|---|
| 2207 | $48m | $19m | 40% | 38% | none | |
| 4471 | $62m | $6m | 10% | 38% | $17.6m | Debt capital markets |
| 9034 | $21m | $8m | 38% | 38% | none | |
| 1187 | $35m | $2m | 6% | 38% | $11.3m | M&A advisory |
Client 4471 paid sixty-two million dollars in fees this year and the bank earned six of it, almost all in equity. The debt wallet is the gap and the banker knows which deals, from the public data, went to whom. Client 1187 is a lending client that pays eleven million dollars of advisory fees elsewhere.
Per coverage banker, per sector: the fee wallet covered, the share, and the gap. And the identity:
Σ the bank's fees per client = fee ledger total
A client in the ledger with no wallet estimate is listed; it is usually a private client with no public deal data, and it is reported as unestimated rather than as a zero wallet.
Wallet from league tables. Market share is not client share. Estimate per client.
Fee assumptions unstated. The wallet is a guess nobody can check. Version the assumptions and show them.
Private clients scored at zero. No public data is not no wallet. List them as unestimated.
Share read without the wallet. A 40 percent share of a small wallet ranks above a 10 percent share of a large one. Rank by gap in dollars.
Mapped once, the deal data, the fee ledger and the assumptions produce the wallets, the shares, the expected shares and the gap list every quarter. Covirage builds this from the exports as they are. The investment banking page describes the setup, and the coverage by salesperson guide covers the contact-level measure that sits under the wallet.
Good enough to rank, not to bill. Public deal data gives the transactions and their sizes; fee assumptions per product and size band, stated on the report, give the wallet. The report shows the method and the range, and the ranking is stable even when the level is approximate.
The bank's own share with clients of the same sector and size where it holds a lead relationship: the median across those. Not the league table position, which is about the market, not the client.
The join between public deal data and the bank's ledger needs a common identifier, which can be the bank's own client code applied to the public data once. After that, the client code is enough, and names stay in the coverage team's own lookup.