diff --git a/doc/source/whatsnew/v0.24.2.rst b/doc/source/whatsnew/v0.24.2.rst
index 8e59c2300e7ca..f528c058d2868 100644
--- a/doc/source/whatsnew/v0.24.2.rst
+++ b/doc/source/whatsnew/v0.24.2.rst
@@ -26,6 +26,7 @@ Fixed Regressions
 
 - Fixed regression in :meth:`DataFrame.duplicated()`, where empty dataframe was not returning a boolean dtyped Series. (:issue:`25184`)
 - Fixed regression in :meth:`Series.min` and :meth:`Series.max` where ``numeric_only=True`` was ignored when the ``Series`` contained ```Categorical`` data (:issue:`25299`)
+- Fixed regression in ``IntervalDtype`` construction where passing an incorrect string with 'Interval' as a prefix could result in a ``RecursionError``. (:issue:`25338`)
 
 .. _whatsnew_0242.enhancements:
 
diff --git a/pandas/core/dtypes/dtypes.py b/pandas/core/dtypes/dtypes.py
index f84471c3b04e8..b73f55329e25b 100644
--- a/pandas/core/dtypes/dtypes.py
+++ b/pandas/core/dtypes/dtypes.py
@@ -932,13 +932,18 @@ def construct_from_string(cls, string):
         attempt to construct this type from a string, raise a TypeError
         if its not possible
         """
-        if (isinstance(string, compat.string_types) and
-            (string.startswith('interval') or
-             string.startswith('Interval'))):
-            return cls(string)
+        if not isinstance(string, compat.string_types):
+            msg = "a string needs to be passed, got type {typ}"
+            raise TypeError(msg.format(typ=type(string)))
+
+        if (string.lower() == 'interval' or
+           cls._match.search(string) is not None):
+                return cls(string)
 
-        msg = "a string needs to be passed, got type {typ}"
-        raise TypeError(msg.format(typ=type(string)))
+        msg = ('Incorrectly formatted string passed to constructor. '
+               'Valid formats include Interval or Interval[dtype] '
+               'where dtype is numeric, datetime, or timedelta')
+        raise TypeError(msg)
 
     @property
     def type(self):
@@ -979,7 +984,7 @@ def is_dtype(cls, dtype):
                         return True
                     else:
                         return False
-                except ValueError:
+                except (ValueError, TypeError):
                     return False
             else:
                 return False
diff --git a/pandas/tests/dtypes/test_dtypes.py b/pandas/tests/dtypes/test_dtypes.py
index 0fe0a845f5129..71eaf504bdc46 100644
--- a/pandas/tests/dtypes/test_dtypes.py
+++ b/pandas/tests/dtypes/test_dtypes.py
@@ -501,10 +501,11 @@ def test_construction_not_supported(self, subtype):
         with pytest.raises(TypeError, match=msg):
             IntervalDtype(subtype)
 
-    def test_construction_errors(self):
+    @pytest.mark.parametrize('subtype', ['xx', 'IntervalA', 'Interval[foo]'])
+    def test_construction_errors(self, subtype):
         msg = 'could not construct IntervalDtype'
         with pytest.raises(TypeError, match=msg):
-            IntervalDtype('xx')
+            IntervalDtype(subtype)
 
     def test_construction_from_string(self):
         result = IntervalDtype('interval[int64]')
@@ -513,7 +514,7 @@ def test_construction_from_string(self):
         assert is_dtype_equal(self.dtype, result)
 
     @pytest.mark.parametrize('string', [
-        'foo', 'foo[int64]', 0, 3.14, ('a', 'b'), None])
+        0, 3.14, ('a', 'b'), None])
     def test_construction_from_string_errors(self, string):
         # these are invalid entirely
         msg = 'a string needs to be passed, got type'
@@ -522,10 +523,12 @@ def test_construction_from_string_errors(self, string):
             IntervalDtype.construct_from_string(string)
 
     @pytest.mark.parametrize('string', [
-        'interval[foo]'])
+        'foo', 'foo[int64]', 'IntervalA'])
     def test_construction_from_string_error_subtype(self, string):
         # this is an invalid subtype
-        msg = 'could not construct IntervalDtype'
+        msg = ("Incorrectly formatted string passed to constructor. "
+               r"Valid formats include Interval or Interval\[dtype\] "
+               "where dtype is numeric, datetime, or timedelta")
 
         with pytest.raises(TypeError, match=msg):
             IntervalDtype.construct_from_string(string)
@@ -549,6 +552,7 @@ def test_is_dtype(self):
         assert not IntervalDtype.is_dtype('U')
         assert not IntervalDtype.is_dtype('S')
         assert not IntervalDtype.is_dtype('foo')
+        assert not IntervalDtype.is_dtype('IntervalA')
         assert not IntervalDtype.is_dtype(np.object_)
         assert not IntervalDtype.is_dtype(np.int64)
         assert not IntervalDtype.is_dtype(np.float64)
diff --git a/pandas/tests/series/test_operators.py b/pandas/tests/series/test_operators.py
index 4d3c9926fc5ae..b2aac441db195 100644
--- a/pandas/tests/series/test_operators.py
+++ b/pandas/tests/series/test_operators.py
@@ -563,6 +563,13 @@ def test_comp_ops_df_compat(self):
             with pytest.raises(ValueError, match=msg):
                 left.to_frame() < right.to_frame()
 
+    def test_compare_series_interval_keyword(self):
+        # GH 25338
+        s = Series(['IntervalA', 'IntervalB', 'IntervalC'])
+        result = s == 'IntervalA'
+        expected = Series([True, False, False])
+        assert_series_equal(result, expected)
+
 
 class TestSeriesFlexComparisonOps(object):