Based on the given feature "existing_credits", we can analyze its relationship with the target variable "Does this person receive a credit?". 

Here is the analysis:

Yes (Target class 'yes'):
- People with no existing credits at this bank are more likely to receive credit.
- People with 1 existing credit at this bank have a decent chance of receiving credit.
- People with 2 or more existing credits at this bank may have a lower chance of receiving credit.
- We don't have any information on the ranges of values for existing_credits, so we cannot provide further details at this point.

No (Target class 'no'):
- People with no existing credits at this bank may have a higher chance of not receiving credit.
- People with 1 or more existing credits at this bank might have a lower chance of not receiving credit.
- We don't have any information on the ranges of values for existing_credits, so we cannot provide further details at this point.

Based on this analysis, we can generate the dictionary:

```json
{
	"yes": [0.0, 0.0, 0.0, 1.0, 2.0],
	"no": [0.0, 1.0, 1.0, 2.0, 2.0]
}
```

Please note that the values in the dictionary are just examples and may vary depending on the dataset and specific analysis.