Based on the given feature "savings_status" and the task of determining whether a person receives a credit or not, we can analyze the relationship between the feature and the target variable.

To do this, we need access to a dataset that contains the "savings_status" feature and the corresponding information on whether the person received a credit or not. With this dataset, we can calculate the distribution of different savings status categories for both the "yes" and "no" target classes.

Let's assume we have access to a dataset and analyze the relationship based on that data. After the analysis, we will create the required dictionary in the given format.

```json
{
    "yes": ["no known savings", "<100"],
    "no": [">=1000", "100<=X<500"]
}
```

Please note that the values in the dictionary above are hypothetical and may vary depending on the actual data analysis. Also, we have included only a subset of possible values in the dictionary, as mentioned in the task.