Risk

Transform risk management

Our Risk Practice is at the forefront of the movement to transform risk management through advanced analytics. We help clients optimize their risk exposure, improve performance, increase profits, and accelerate growth by combining analytics tools and techniques with our strategy and organizational-transformation expertise.

Why McKinsey Analytics?

Work alongside and learn from the best people in the field—more than 130 industry and functional experts, as well as advanced-analytics and modeling specialists. In this role, you’ll apply your skills across areas such as credit-risk modeling and analytics, stress testing and balance-sheet analytics, operational-risk and fraud analytics, and insurance analytics. Throughout, you’ll drive our clients’ transformations from the ground up.

What we are looking for

We’d love to hear from you if you have excellent academic qualifications or experience building risk-management strategies or proprietary tools, such as credit assessments, sentiment analyses, or quantitative commodity-price scenario analyses.

Project Snapshot

A leading bank uses machine learning to detect more than 85 percent of all invoice fraud

To help a leading bank detect rare fraudulent transactions (one in 50 million instances), a team of analytics experts and data engineers built one of the largest payment data sets in the bank’s country. The team developed a machine-learning model that uses more than 200 features and ensures computational performance for live scoring, database best practices, and legal compliance. Within the first few weeks of operation, the model flagged some ~$130,000 USD in fraudulent transactions.