Credit Risk Analyst

07 set - Milano
American Express

Job Description

Credit and Fraud Risk (CFR) is a global function, responsible for making the right credit and fraud risk decisions that uphold operational excellence, drive growth, and accelerate innovation across American Express. CFR combines technology and infrastructure with new computing techniques to make better risk decisions and provide real-time customer communications and fraud servicing.

How will you make an impact in this role?

You will join a team responsible for supporting and collaborating in the definition of credit strategies and models, credit risk monitoring and governance for the acquisition of individuals and small companies.

Thanks to your strong analytical mindset and data manipulation skills you will work on projects to implement automated monitoring systems while deep-diving on identifying opportunities of growth. You will be involved with the CFR International Centre of Excellence teams on defining and implement the best-in-class modelling solutions and strategies dedicated to acquisition for individuals and small companies.

Responsibilities





In particular, you will be requested the following activities:

Credit Risk Data and Processes: Identify new and innovative data points and sources to enhance our models and strategies, then support the integration of the new data in our systems. Identify opportunities for process efficiencies and contribute to work flow/process change redesign, forming a good understanding of the specific product or process.

Credit Risk Analysis: analyse, assess, and quantify the impact and probability of various risk scenarios and select the most appropriate course of action for the given situation.

Insights and Reporting: Develop, create and maintain credit risk reporting. Lead execution of complex reports, identifying and interpreting complex patterns and trends, and translating those insights into actionable recommendations. Applies comprehensive knowledge and skills to create relevant, lucid and effective

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