Why It Exists
The Consensus PD is a simple average — which means it is sensitive to both what banks think and who is contributing. When the contributor pool changes, the average can shift even if no bank has changed its view.
This means the Consensus PD can move for two very different reasons:
- Opinion change — one or more banks changed their PD estimate for this entity
- Depth change — the contributing bank population changed; a bank joined, left, or both
Telling them apart is critical to interpreting the data correctly.
How It Works
The Opinion Change Indicator (OCI) measures the net rating change across banks that contributed in both the current and prior period — holding the population constant to isolate genuine shifts in credit sentiment.
The OCI tracks credit sentiment at the individual contributing bank level — for each same-bank contributor, we calculate whether their view moved toward improvement, deterioration, or held steady month-on-month.
Each is assigned a directional signal (+1, −1, or 0), and those signals are summed to produce a net read on market direction:
OCIt=b∈Bt∩Bt−1∑sign(f(PDb,t−1)−f(PDb,t))
Where:
- Bt = set of contributing banks at time t
- f(PD) = rating scale mapping function returning a notch index
- A positive result indicates net improvement; negative indicates net deterioration
By restricting the sum to Bt∩Bt−1 — banks present in both periods — the OCI strips out any movement caused by banks joining or leaving the contributor pool.
If the CCR or Consensus PD moved but the OCI is Stable, the move reflects a change in who is contributing — not a change in credit opinion. Weight it accordingly.
OCI Values
The OCI is published as a directional indicator. On the single entity page, each contributing bank gets an arrow:
- Improving — net same-bank view moved toward lower PDs (green arrow)
- Stable — no net change among same-bank contributors (no arrow)
- Deteriorating — net same-bank view moved toward higher PDs (red arrow)
Use in PD Aggregates
The OCI feeds into the PD Aggregates methodology, where population-controlled time series are constructed to track genuine credit sentiment over time — stripping out noise from contributor turnover.
