I have been working with beta-bernoulli posteriors recently. Is it true that if $X,Y$ are independent rvs with $X \sim Beta(a_1+1,b_1+1)$ and $Y \sim Beta(a_2+1,b_2+1)$ then $\mathbb{P}(X>Y)>0.5$ iff $\frac{a_1}{a_1+b_1}>\frac{a_2}{a_2+b_2}$? $a_1,a_2,b_1,b_2$ are assumed to be whole numbers.
This makes intuitive sense as the estimated bernoulli parameter is greater in $X$ than in $Y$. I have observed this for all parameters within the range $0 \leq a_1,b_1,a_2,b_2\leq 6$. However, it does not seem to immediately follow from the definitions.
I have tried writing $\mathbb{P}(X>Y)=\frac{\int_{0}^{1}\int_{0}^{x}y^{a_2}(1-y)^{b_2}x^{a_1}(1-x)^{b_1}dy dx}{B(a_1+1,b_1+1)B(a_2+1,b_2+1)}$, but the numerator doesn't seem that easy to work with. I don't see a similar question on stackexchange. Can this be proved or can a counter example be produced for this?
Update1: It seems the result is false if $a_1,b_1,a_2,b_2$ are just positive real numbers as initially posed. See Henrys answer below. Can a counterexample be produced for whole numbers?
Update2: Henry has produced a whole number counterexample. This answers the question in the negative conclusively.