We are seeking an experienced Risk Analytics and Underwriting Senior Manager to lead and manage the risk underwriting process, develop and enhance scorecards, optimize the use of external data, and implement fraud triggers for our multi-finance operations. The ideal candidate will be a strategic thinker with a deep understanding of credit risk, fraud management, and risk analytics, capable of developing robust risk models that drive decision-making and mitigate potential risks.
About Flip
Rafi, Luqman, and Anjar, who were college friends in Universitas Indonesia, started Flip as a project in 2015 to transfer payments to each other at a fraction of what banks would charge them. They are pioneers in the Indonesian market, with their technology now helping millions of Indonesians, both individuals and businesses, carry out bank-to-bank money transfers through a reliable and seamless app.
After seven years of operations, Flip has helped Indonesians transfer money worth several trillions of rupiah and has received double-digit funding from respectable investors such as Sequoia India, Insight Partner, and Insignia. Flip’s ultimate mission is to give Indonesians access to one of the most progressive and fairest financial services in the world.
At Flip, we always strive to provide the fairest place for you to work, learn, and grow with talented and fun people in various opportunities to advance your career and get fair rewards. We believe that we have to treat employees, customers, and all stakeholders fairly and respectfully. Fair treatment for employees means we establish clear goals, facilitate our employees to achieve them, and value their contribution to the company with equitable benefits.
What you'll do
Bachelor's degree in Finance, Statistics, Data Science, or related fields; Master's degree preferred.
At least 8-10 years of experience in risk management, underwriting, or related fields in financial services, with a focus on multi-finance operations.
Strong expertise in developing and managing risk scorecards, fraud detection systems, and underwriting frameworks.
In-depth knowledge of external data sources (credit bureaus, alternative data) and their application in risk assessment.
Proficient in data analysis tools (e.g., SQL, Python, R) and experience with risk modeling techniques.
Excellent leadership, communication, and problem-solving skills.
Familiarity with regulatory requirements and best practices in risk management and fraud prevention.