diff --git a/NEWS.md b/NEWS.md
index 1df88197..7d888ef7 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -6,6 +6,7 @@ Minor spelling / mathematical updates to Scoring rule vignette. (#969)
 
 - A bug was fixed where `crps_sample()` could fail in edge cases.
 - Implemented a new forecast class, `forecast_ordinal` with appropriate metrics. Ordinal forecasts are a form of categorical forecasts. The main difference between ordinal and nominal forecasts is that the outcome is ordered, rather than unordered.
+- Refactored the way that columns get internally renamed in `as_forecast_<type>()` functions (#980)
 
 # scoringutils 2.0.0
 
diff --git a/R/class-forecast-binary.R b/R/class-forecast-binary.R
index 2f1b3eb0..09fc1704 100644
--- a/R/class-forecast-binary.R
+++ b/R/class-forecast-binary.R
@@ -34,7 +34,12 @@ as_forecast_binary <- function(data,
                                forecast_unit = NULL,
                                observed = NULL,
                                predicted = NULL) {
-  data <- as_forecast_generic(data, forecast_unit, observed, predicted)
+  data <- as_forecast_generic(
+    data,
+    forecast_unit,
+    observed = observed,
+    predicted = predicted
+  )
   data <- new_forecast(data, "forecast_binary")
   assert_forecast(data)
   return(data)
diff --git a/R/class-forecast-nominal.R b/R/class-forecast-nominal.R
index a457d964..c589b585 100644
--- a/R/class-forecast-nominal.R
+++ b/R/class-forecast-nominal.R
@@ -45,13 +45,13 @@ as_forecast_nominal <- function(data,
                                 observed = NULL,
                                 predicted = NULL,
                                 predicted_label = NULL) {
-  assert_character(predicted_label, len = 1, null.ok = TRUE)
-  assert_subset(predicted_label, names(data), empty.ok = TRUE)
-  if (!is.null(predicted_label)) {
-    setnames(data, old = predicted_label, new = "predicted_label")
-  }
-
-  data <- as_forecast_generic(data, forecast_unit, observed, predicted)
+  data <- as_forecast_generic(
+    data,
+    forecast_unit,
+    observed = observed,
+    predicted = predicted,
+    predicted_label = predicted_label
+  )
   data <- new_forecast(data, "forecast_nominal")
   assert_forecast(data)
   return(data)
diff --git a/R/class-forecast-ordinal.R b/R/class-forecast-ordinal.R
index 0926cd5d..d6dda020 100644
--- a/R/class-forecast-ordinal.R
+++ b/R/class-forecast-ordinal.R
@@ -45,13 +45,13 @@ as_forecast_ordinal <- function(data,
                                 observed = NULL,
                                 predicted = NULL,
                                 predicted_label = NULL) {
-  assert_character(predicted_label, len = 1, null.ok = TRUE)
-  assert_subset(predicted_label, names(data), empty.ok = TRUE)
-  if (!is.null(predicted_label)) {
-    setnames(data, old = predicted_label, new = "predicted_label")
-  }
-
-  data <- as_forecast_generic(data, forecast_unit, observed, predicted)
+  data <- as_forecast_generic(
+    data,
+    forecast_unit,
+    observed = observed,
+    predicted = predicted,
+    predicted_label = predicted_label
+  )
   data <- new_forecast(data, "forecast_ordinal")
   assert_forecast(data)
   return(data)
diff --git a/R/class-forecast-point.R b/R/class-forecast-point.R
index 0dfc87ab..7e2aa9eb 100644
--- a/R/class-forecast-point.R
+++ b/R/class-forecast-point.R
@@ -30,7 +30,12 @@ as_forecast_point.default <- function(data,
                                       observed = NULL,
                                       predicted = NULL,
                                       ...) {
-  data <- as_forecast_generic(data, forecast_unit, observed, predicted)
+  data <- as_forecast_generic(
+    data,
+    forecast_unit,
+    observed = observed,
+    predicted = predicted
+  )
   data <- new_forecast(data, "forecast_point")
   assert_forecast(data)
   return(data)
diff --git a/R/class-forecast-quantile.R b/R/class-forecast-quantile.R
index caf301fa..ac341ee2 100644
--- a/R/class-forecast-quantile.R
+++ b/R/class-forecast-quantile.R
@@ -46,13 +46,13 @@ as_forecast_quantile.default <- function(data,
                                          predicted = NULL,
                                          quantile_level = NULL,
                                          ...) {
-  assert_character(quantile_level, len = 1, null.ok = TRUE)
-  assert_subset(quantile_level, names(data), empty.ok = TRUE)
-  if (!is.null(quantile_level)) {
-    setnames(data, old = quantile_level, new = "quantile_level")
-  }
-
-  data <- as_forecast_generic(data, forecast_unit, observed, predicted)
+  data <- as_forecast_generic(
+    data,
+    forecast_unit,
+    observed = observed,
+    predicted = predicted,
+    quantile_level = quantile_level
+  )
   data <- new_forecast(data, "forecast_quantile")
   assert_forecast(data)
   return(data)
diff --git a/R/class-forecast-sample.R b/R/class-forecast-sample.R
index 352c139c..8252ca4d 100644
--- a/R/class-forecast-sample.R
+++ b/R/class-forecast-sample.R
@@ -29,13 +29,13 @@ as_forecast_sample <- function(data,
                                observed = NULL,
                                predicted = NULL,
                                sample_id = NULL) {
-  assert_character(sample_id, len = 1, null.ok = TRUE)
-  assert_subset(sample_id, names(data), empty.ok = TRUE)
-  if (!is.null(sample_id)) {
-    setnames(data, old = sample_id, new = "sample_id")
-  }
-
-  data <- as_forecast_generic(data, forecast_unit, observed, predicted)
+  data <- as_forecast_generic(
+    data,
+    forecast_unit,
+    observed = observed,
+    predicted = predicted,
+    sample_id = sample_id
+  )
   data <- new_forecast(data, "forecast_sample")
   assert_forecast(data)
   return(data)
diff --git a/R/class-forecast.R b/R/class-forecast.R
index 09a279df..697e94fa 100644
--- a/R/class-forecast.R
+++ b/R/class-forecast.R
@@ -4,25 +4,29 @@
 #' It renames the required columns, where appropriate, and sets the forecast
 #' unit.
 #' @inheritParams as_forecast_doc_template
+#' @param ... Named arguments that are used to rename columns. The names of the
+#'  arguments are the names of the columns that should be renamed. The values
+#'  are the new names.
 #' @keywords as_forecast
 as_forecast_generic <- function(data,
                                 forecast_unit = NULL,
-                                observed = NULL,
-                                predicted = NULL) {
-  # check inputs - general
+                                ...) {
   data <- ensure_data.table(data)
-  assert_character(observed, len = 1, null.ok = TRUE)
-  assert_subset(observed, names(data), empty.ok = TRUE)
-
-  assert_character(predicted, len = 1, null.ok = TRUE)
-  assert_subset(predicted, names(data), empty.ok = TRUE)
-
-  # rename columns - general
-  if (!is.null(observed)) {
-    setnames(data, old = observed, new = "observed")
-  }
-  if (!is.null(predicted)) {
-    setnames(data, old = predicted, new = "predicted")
+  oldnames <- list(...)
+  newnames <- names(oldnames)
+  provided <- !sapply(oldnames, is.null)
+
+  lapply(seq_along(oldnames), function(i) {
+    var <- oldnames[[i]]
+    varname <- names(oldnames)[i]
+    assert_character(var, len = 1, null.ok = TRUE, .var.name = varname)
+    assert_subset(var, names(data), empty.ok = TRUE, .var.name = varname)
+  })
+
+  oldnames <- unlist(oldnames[provided])
+  newnames <- unlist(newnames[provided])
+  if (!is.null(oldnames) && length(oldnames) > 0) {
+    setnames(data, old = oldnames, new = newnames)
   }
 
   # set forecast unit (error handling is done in `set_forecast_unit()`)
diff --git a/man/as_forecast_generic.Rd b/man/as_forecast_generic.Rd
index 9cb52e5b..cfbba7c2 100644
--- a/man/as_forecast_generic.Rd
+++ b/man/as_forecast_generic.Rd
@@ -4,12 +4,7 @@
 \alias{as_forecast_generic}
 \title{Common functionality for \verb{as_forecast_<type>} functions}
 \usage{
-as_forecast_generic(
-  data,
-  forecast_unit = NULL,
-  observed = NULL,
-  predicted = NULL
-)
+as_forecast_generic(data, forecast_unit = NULL, ...)
 }
 \arguments{
 \item{data}{A data.frame (or similar) with predicted and observed values.
@@ -23,11 +18,9 @@ If \code{NULL} (the default), all columns that are not required columns are
 assumed to form the unit of a single forecast. If specified, all columns
 that are not part of the forecast unit (or required columns) will be removed.}
 
-\item{observed}{(optional) Name of the column in \code{data} that contains the
-observed values. This column will be renamed to "observed".}
-
-\item{predicted}{(optional) Name of the column in \code{data} that contains the
-predicted values. This column will be renamed to "predicted".}
+\item{...}{Named arguments that are used to rename columns. The names of the
+arguments are the names of the columns that should be renamed. The values
+are the new names.}
 }
 \description{
 Common functionality for \verb{as_forecast_<type>} functions
diff --git a/man/assert_input_categorical.Rd b/man/assert_input_categorical.Rd
new file mode 100644
index 00000000..cc203e8f
--- /dev/null
+++ b/man/assert_input_categorical.Rd
@@ -0,0 +1,39 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/metrics-nominal.R
+\name{assert_input_categorical}
+\alias{assert_input_categorical}
+\title{Assert that inputs are correct for categorical forecasts}
+\usage{
+assert_input_categorical(observed, predicted, predicted_label, ordered = NA)
+}
+\arguments{
+\item{observed}{Input to be checked. Should be a factor of length n with
+N levels holding the observed values. n is the number of observations and
+N is the number of possible outcomes the observed values can assume.}
+
+\item{predicted}{Input to be checked. Should be nxN matrix of predicted
+probabilities, n (number of rows) being the number of data points and N
+(number of columns) the number of possible outcomes the observed values
+can assume.
+If \code{observed} is just a single number, then predicted can just be a
+vector of size N.
+Values represent the probability that the corresponding value
+in \code{observed} will be equal to the factor level referenced in
+\code{predicted_label}.}
+
+\item{predicted_label}{Factor of length N with N levels, where N is the
+number of possible outcomes the observed values can assume.}
+
+\item{ordered}{Value indicating whether factors have to be ordered or not.
+Defaults to \code{NA}, which means that the check is not performed.}
+}
+\value{
+Returns NULL invisibly if the assertion was successful and throws an
+error otherwise.
+}
+\description{
+Function assesses whether the inputs correspond to the
+requirements for scoring categorical, i.e. either nominal or ordinal
+forecasts.
+}
+\keyword{internal_input_check}
diff --git a/scoringutils.Rproj b/scoringutils.Rproj
index a96991f9..bb245469 100644
--- a/scoringutils.Rproj
+++ b/scoringutils.Rproj
@@ -1,4 +1,5 @@
 Version: 1.0
+ProjectId: 008f911e-df6e-4218-825c-db1095ac43c4
 
 RestoreWorkspace: No
 SaveWorkspace: No
diff --git a/tests/testthat/test-class-forecast-quantile.R b/tests/testthat/test-class-forecast-quantile.R
index 3711cf05..fda26428 100644
--- a/tests/testthat/test-class-forecast-quantile.R
+++ b/tests/testthat/test-class-forecast-quantile.R
@@ -157,6 +157,25 @@ test_that("as_forecast_quantiles issue 557 fix", {
   expect_equal(any(is.na(out$interval_coverage_deviation)), FALSE)
 })
 
+test_that("as_forecast_quantile doesn't modify column names in place", {
+  quantile_data <- data.table(
+    my_quantile = c(0.25, 0.5),
+    forecast_value = c(1, 2),
+    observed_value = c(5, 5)
+  )
+  pre <- names(quantile_data)
+
+  quantile_forecast <- quantile_data %>%
+    as_forecast_quantile(
+      predicted = "forecast_value",
+      observed = "observed_value",
+      quantile_level = "my_quantile"
+    )
+
+  post <- names(quantile_data)
+  expect_equal(pre, post)
+})
+
 
 # ==============================================================================
 # is_forecast_quantile()