No Economies of Scale in Banking
Judge an institution's crisis response by its org shape, not its balance sheet
- Difficulty
- Easy
- Time to result
- ~weeks to results
- Steps
- 5
- Confidence
- 58%
Whalen's model holds that banking has essentially no economies of scale when the work is non-standard. Large banks are built as pyramids on purpose: layers of approval exist to stop staff from causing trouble, which is a sound control objective and a crippling constraint the moment something unprecedented arrives. The mechanism runs from org shape to decision latency to throughput. A flat institution lets branch-level staff make decisions and increase capacity locally, so it absorbs a surge quickly. A pyramid must route every unfamiliar case upward, so its effective capacity is set by a narrow band of decision-makers, not by headcount. Non-bank lenders, being flat, move fastest of all. The practical use is diagnostic: to predict who executes a new programme well, count approval layers rather than assets.
Origin
Extracted from Masters in Business, where Christopher Whalen explained why small community banks processed emergency Paycheck Protection Program loans faster than the money-centre banks.
Core principles
- 01Size buys balance sheet, not operational speed.
- 02Hierarchy is deliberately installed to prevent unauthorised action, and it works both ways.
- 03Decision authority sitting close to the customer is what makes a firm nimble.
- 04Non-standard work is where scale advantages invert into disadvantages.
- 05Bottlenecks show up first in the channels that require a human decision.
How to run it
- 1
Classify the task
Separate routine, high-volume processing from work that is out of the ordinary. The model only inverts on the second kind.
Pro tip Anything created by legislation in the last month is out of the ordinary by definition.
- 2
Map the decision path
Trace how a single request travels from the customer to the person authorised to approve it, counting every layer it passes through.
Watch out Published org charts understate the real number of sign-offs.
- 3
Find the human bottleneck
Identify the channel that requires an actual conversation. That channel, not the website, sets the institution's real throughput on novel work.
Pro tip Phone-queue capacity is a surprisingly good proxy for a pyramid's width at the decision layer.
- 4
Score flatness
Rank each institution by how far decision authority sits from the customer. Community banks and non-bank lenders typically score flattest.
Watch out Do not confuse a flat brand with a flat approval process.
- 5
Predict, then check
Use the flatness ranking to predict who delivers the new programme fastest, then compare against observed results to calibrate the model.
Pro tip Where the prediction fails, look for a small unit inside the large firm that was given unusual autonomy.
In the wild
When emergency small-business loans were legislated with no implementation guidance, the largest banks had to stand up an entire process in days. Their pyramids routed every unusual case upward and their phone channels bottlenecked, because applicants had to speak to someone to get a loan approved. Community banks and regionals, with decision authority at branch level, simply flexed local capacity and processed applications. Non-bank lenders, flatter still, moved fastest.
→ Institutional speed tracked flatness almost inversely to asset size.
Common mistakes
Reading size as capability
A trillion dollars of deposits says nothing about how quickly a firm can approve an unfamiliar request. The two are almost independent.
Judging by the digital front end
A slick online application form does not remove the human approval step behind it, which is where the real queue forms.
Applying the model to routine volume
For standardised, repetitive processing, scale genuinely helps. Using the flatness ranking there will give the wrong answer.
Is it for you?
Best for
Anyone comparing large and small institutions on their ability to deliver something novel under time pressure.
Not ideal for
Assessing capacity for high-volume routine processing or balance-sheet strength, where size genuinely helps.
From the transcript
“they have a flatter organization the big banks or pyramids,”
“So essentially, the largest banks are very inefficient by design,”
“they move very quickly, and smaller banks tend to be”
From the episode
Chris Whalen on PPP Loans (Podcast)
Chris Whalen