Using data from the Frankfurt Stock Exchange we analyze price formation and liquidity in a non-anonymous environment with similarities to the floor of the NYSE. Our main hypothesis is that the non-anonymity allows the specialist to assess the probability that a trader trades on the basis of private information. He uses this knowledge to price discriminate. This can be achieved by quoting a large spread and granting price improvement to traders deemed uninformed. Consistent with our hypothesis we find that price improvement reflects lower adverse selection costs but does not lead to a reduction in the specialist's profit. Further, the quote adjustment following transactions at the quoted bid or ask price is more pronounced than the quote adjustment after transactions at prices inside the spread. Our results indicate that anonymity comes at the cost of higher adverse selection risk.