diff --git a/src/main/scala/com/amazon/deequ/VerificationResult.scala b/src/main/scala/com/amazon/deequ/VerificationResult.scala
index b9b450f2..24b68726 100644
--- a/src/main/scala/com/amazon/deequ/VerificationResult.scala
+++ b/src/main/scala/com/amazon/deequ/VerificationResult.scala
@@ -31,6 +31,7 @@ import com.amazon.deequ.repository.SimpleResultSerde
 import org.apache.spark.sql.Column
 import org.apache.spark.sql.DataFrame
 import org.apache.spark.sql.SparkSession
+import org.apache.spark.sql.functions.lit
 import org.apache.spark.sql.functions.{col, monotonically_increasing_id}
 
 import java.util.UUID
@@ -144,7 +145,7 @@ object VerificationResult {
     val constraint = constraintResult.constraint
     constraint match {
       case asserted: RowLevelAssertedConstraint =>
-        constraintResult.metric.flatMap(metricToColumn).map(asserted.assertion(_))
+        constraintResult.metric.flatMap(metricToColumn).map(asserted.assertion(_)).orElse(Some(lit(false)))
       case _: RowLevelConstraint =>
         constraintResult.metric.flatMap(metricToColumn)
       case _: RowLevelGroupedConstraint =>
@@ -160,7 +161,6 @@ object VerificationResult {
     }
   }
 
-
   private[this] def getSimplifiedCheckResultOutput(
       verificationResult: VerificationResult)
     : Seq[SimpleCheckResultOutput] = {
diff --git a/src/test/scala/com/amazon/deequ/VerificationSuiteTest.scala b/src/test/scala/com/amazon/deequ/VerificationSuiteTest.scala
index 146579e8..15c5ca44 100644
--- a/src/test/scala/com/amazon/deequ/VerificationSuiteTest.scala
+++ b/src/test/scala/com/amazon/deequ/VerificationSuiteTest.scala
@@ -1996,6 +1996,29 @@ class VerificationSuiteTest extends WordSpec with Matchers with SparkContextSpec
   }
 
   "Verification Suite's Row Level Results" should {
+    "yield correct results for invalid column type" in withSparkSession { sparkSession =>
+      import sparkSession.implicits._
+      val df = Seq(
+        ("1", 1, "blue"),
+        ("2", 2, "green"),
+        ("3", 3, "blue"),
+        ("4", 4, "red"),
+        ("5", 5, "purple")
+      ).toDF("id", "id2", "color")
+      val invalidColumn = "id"
+      val validColumn = "id2"
+      val checkOnInvalidColumnDescription = s"check on $invalidColumn"
+      val checkOnValidColumnDescription = s"check on $validColumn"
+      val checkOnInvalidColumn = Check(CheckLevel.Error, checkOnInvalidColumnDescription).hasMin(invalidColumn, _ >= 3).isComplete(invalidColumn)
+      val checkOnValidColumn = Check(CheckLevel.Error, checkOnValidColumnDescription).hasMin(validColumn, _ >= 3).isComplete(validColumn)
+      val verificationResult = VerificationSuite().onData(df).addChecks(Seq(checkOnInvalidColumn, checkOnValidColumn)).run()
+      val rowLevelResults = VerificationResult.rowLevelResultsAsDataFrame(sparkSession, verificationResult, df).collect()
+      val invalidColumnCheckRowLevelResults = rowLevelResults.map(_.getAs[Boolean](checkOnInvalidColumnDescription))
+      val validColumnCheckRowLevelResults = rowLevelResults.map(_.getAs[Boolean](checkOnValidColumnDescription))
+      invalidColumnCheckRowLevelResults shouldBe Seq(false, false, false, false, false)
+      validColumnCheckRowLevelResults shouldBe Seq(false, false, true, true, true)
+    }
+
     "yield correct results for satisfies check" in withSparkSession { sparkSession =>
       import sparkSession.implicits._
       val df = Seq(