We present the results of a business solution on how to measure credit and counterparty risk, with the main focus on over-the-counter derivatives. Moreover, we use this approach to include the measurement of liquidity risk exposure. While there are very sophisticated approaches to credit/counterparty risk, these have many disadvantages (eg, cost, implementation time, model risk, complexity). On the other hand, the "current exposure method" approach suggested by the regulator is quite simplistic and has been widely criticized since it does not model the risk "properly". Instead, we present a working model that lies in the middle (ie, it is simple without being simplistic, not very expensive/time-consuming to implement, able to solve the shortfalls that the add-on approach has, etc) and is able to capture the liquidity risk from collateral requirements. In particular, we explain how we measure the exposure for each counterparty with netting arrangements and collaterals. We introduce the concept of potential future exposure and explain why we opted for a parametric approach. We then develop the concepts of credit loss and default probability as a result of a Poisson process and we use the concept of unexpected loss in order to derive the economic capital as the difference between the unexpected loss and the credit loss. Finally, we show how this approach can be applied as a refinement of liquidity risk measurement by considering collateral requirements, so as to enhance the monitoring of liquidity congruence between funds' assets and liabilities, particularly under stressed market conditions.