Abstract: A machine-learning tool evaluates an acquirer's current portfolio and then develops a model portfolio that mathematically redistributes the effect of the current portfolio by suggesting business categories that would better serve the acquirer from a risk/reward perspective. The machine-learning tool is trained with model portfolios and then generates a suggested portfolio that incorporates the acquirer's current partners and supplements them with additional business categories that would improve the risk/reward metric. The machine-learning tool may also select specific businesses from within the suggested business categories for the acquirer to use in achieving the suggested improvement.

Abstract: A machine-learning tool evaluates an acquirer's current portfolio and then develops a model portfolio that mathematically redistributes the effect of the current portfolio by suggesting business categories that would better serve the acquirer from a risk/reward perspective. The machine-learning tool is trained with model portfolios and then generates a suggested portfolio that incorporates the acquirer's current partners and supplements them with additional business categories that would improve the risk/reward metric. The machine-learning tool may also select specific businesses from within the suggested business categories for the acquirer to use in achieving the suggested improvement.

Abstract: A machine-learning tool evaluates an acquirer's current portfolio and then develops a model portfolio that mathematically redistributes the effect of the current portfolio by suggesting business categories that would better serve the acquirer from a risk/reward perspective. The machine-learning tool is trained with model portfolios and then generates a suggested portfolio that incorporates the acquirer's current partners and supplements them with additional business categories that would improve the risk/reward metric. The machine-learning tool may also select specific businesses from within the suggested business categories for the acquirer to use in achieving the suggested improvement.

Abstract: A machine-learning tool evaluates an acquirer's current portfolio and then develops a model portfolio that mathematically redistributes the effect of the current portfolio by suggesting business categories that would better serve the acquirer from a risk/reward perspective. The machine-learning tool is trained with model portfolios and then generates a suggested portfolio that incorporates the acquirer's current partners and supplements them with additional business categories that would improve the risk/reward metric. The machine-learning tool may also select specific businesses from within the suggested business categories for the acquirer to use in achieving the suggested improvement.