Using [Miller][1] (`mlr`) to first (left-)join the data from `fileA` with the data in `fileB` on the following named fields:

```none
account,code,date,type,pc,vol,bs
```

... and then rename the `account1` field `account` (for the records that have an `account1` field, which will only be the ones that were joined).

We then reorder the fields and remove the ones we don't want in the output.


```sh
mlr --csv \
    join -f fileA -j account,code,date,type,pc,vol,bs --ul then \
    rename account1,account then \
    cut -o -f account,temp1,code,type,date,subtask,pc,toy,vol,bs,sub fileB
```

The output, given the data in the question:

```csv
account,temp1,code,type,date,subtask,pc,toy,vol,bs,sub
CCCCC,GFHD,ASDF,BS,21122022,STOP,C,CAT,1000,S,MATH
6576,WEQR,TYRE,BS,54122022,OBCD,K,BAT,5000,F,SCSC
7654,GHAD,LOPI,CV,9089022,KGAD,G,BSEE,5908,J,IOYU
```

Note that the order of the fields in the two input files is irrelevant.

If you don't know what fields you may use to join on, you may calculate the common field names separately (unfortunately, Miller can't do a "natural join" operation but must be given an explicit list of field names to join on):

```sh
mlr --csv put -q '
    if (NR == 1) {
        for (k in $*) { @f[k] = 1 }
    } else {
       for (k in @f) {
           is_null($[k]) { unset @f[k] }
       }
    }
   end {
       common_fieldnames = joink(@f,",");
       emit common_fieldnames
   }' fileA fileB
```

For the given data, this outputs the following CSV data set
```csv
common_fieldnames
"account,code,type,date,pc,vol,bs"
```

To _only_ get the comma-delimited list, use options that would generate header-less unquoted CSV output, e.g. `--csv` in combination with `--headerless-csv-output` and `--quote-none`.

  [1]: https://miller.readthedocs.io/en/latest/