Senior Underwriting Risk Analytics Executive

Krom; Jakarta Pusat; On-site; IDR 600,000,000 - 1,200,000,000; Full time

Job summary

Krom Bank is seeking a Senior Underwriting Risk Analytics Executive to lead risk assessment across the lending portfolio. You will collaborate with Product, Data Science, Business, Credit, and Finance to ensure sound underwriting frameworks and sustainable portfolio performance.

You will develop and refine RAC, build credit scoring models (PD, LGD, EAD), monitor loss rates, set early warning thresholds, advise on loan pricing and terms, and ensure compliance with regulations while supporting

Qualifications

• Bachelor’s degree in Economics, Statistics, Mathematics, Finance or related quantitative field.
• Minimum 2 years of relevant experience in credit risk analysis, underwriting, portfolio risk or risk management.
• Strong ability to identify, assess, and quantify credit risk using quantitative analysis and statistical modelling.
• Hands-on experience with data analytics tools such as SQL, Python, R, or other statistical software.
• Good understanding of credit risk indicators including PD, EAD, LGD, loss rates and portfolio risk metrics.
• Solid understanding of credit underwriting processes in digital banking or data-driven lending environments.
• Experience with machine learning, credit scoring, and alternative data for credit assessment.
• Strong analytical and problem-solving skills with ability to translate data into actionable business recommendations.
• Good understanding of regulatory requirements and their impact on credit risk management and underwriting policies.
• Strong communication and stakeholder management across Risk, Business, Credit, Product, Data Science, and Finance.

Responsibilities

• Contribute to development and enhancement of underwriting policies and RAC across unsecured lending products.
• Collaborate with Product and Data Science teams to develop credit scoring models and refine models per risk appetite.
• Evaluate risk opinions on the risk-return profile of lending partnerships proposed by the Business team.
• Partner with Business and Credit teams to ensure products and partnerships align with risk appetite and limits.
• Provide strategic guidance on loan pricing, structure, and terms to optimize risk-adjusted returns.
• Work with credit reviewers to establish and refine loss-rate monitoring systems and early warning thresholds.
• Develop, validate, and enhance credit risk models (PD, LGD, EAD) to improve risk assessment and provisioning.
• Leverage data analytics and quantitative methods to identify and mitigate credit risk exposures.
• Monitor regulatory developments and assess implications for risk management and underwriting practices.
• Support internal and regulatory audits/inspections with comprehensive risk documentation.

Skills

SQL

Python

R

Credit risk analysis

Machine learning

Data analytics

Communication

Regulatory knowledge

Education

Bachelor’s degree in Economics/Statistics/Math/Finance

Tools

SQL

Python

R

Job description

As a Senior Underwriting Risk Analytics Executive, you will play a key role in assessing and mitigating credit risks across the Bank’s lending portfolio. You will work closely with Product, Data Science, Business, Credit, and Finance teams to ensure sound credit decisions, robust underwriting frameworks, and sustainable portfolio performance.

In this role, you will:

• Contribute to the development and enhancement of credit underwriting policies and selection criteria, including Risk Acceptance Criteria (RAC), across the Bank’s unsecured lending products, covering conventional, digital, and channelling businesses.
• Collaborate with Product and Data Science teams in developing credit scoring models and ensure appropriate refinement or adjustment of models in line with the Bank’s risk appetite and portfolio risk profile.
• Evaluate and provide risk opinions on the risk-return profile of lending partnerships proposed by the Business team, including syndicated lending and credit facility execution, through comprehensive risk management assessments.
• Partner with Business and Credit teams to ensure lending partnerships and products are structured within the Bank’s overall risk appetite and risk limits.
• Provide strategic guidance on loan pricing, structure, and terms to optimize risk-adjusted returns.
• Work closely with credit reviewers to establish and enhance loss-rate monitoring systems and early warning thresholds.
• Develop, validate, and enhance credit risk models, including Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD), to improve risk assessment accuracy and support credit loss provisioning in coordination with the Finance team.
• Leverage data analytics and quantitative methodologies to identify, predict, and mitigate credit risk exposures.
• Monitor developments in applicable banking and financial regulations and assess their implications for credit risk management and underwriting practices.
• Support internal and regulatory audits/inspections by ensuring comprehensive, accurate, and well-maintained risk documentation.

About You:

We are looking for a data-driven and commercially minded risk professional who combines strong quantitative capabilities with a solid understanding of credit underwriting and digital lending. You should have:

• A minimum Bachelor’s degree (S1) in Economics, Statistics, Mathematics, Finance, or a related quantitative field.
• Minimum 2 years of relevant experience in credit risk analysis, underwriting, portfolio risk, or risk management within banking, financial institutions, or digital lending/fintech.
• Strong ability to identify, assess, and quantify credit risk using quantitative analysis and statistical modelling techniques.
• Hands-on experience with data analytics tools such as SQL, Python, R, or other statistical/data analysis software.
• Good understanding of key credit risk indicators, including financial ratios, Probability of Default (PD), Exposure at Default (EAD), Loss Given Default (LGD), loss rates, and other portfolio risk metrics.
• Solid understanding of credit underwriting processes, particularly within digital banking or data-driven lending environments.
• Experience working with credit risk models and analytics, including machine learning, credit scoring, and alternative data for credit assessment.
• Strong analytical and problem-solving skills, with the ability to translate complex data and risk analysis into actionable business and risk recommendations.
• Good understanding of regulatory requirements and their impact on credit risk management and underwriting policies.
• Strong communication and stakeholder management skills, with the ability to collaborate effectively across Risk, Business, Credit, Product, Data Science, and Finance teams.
• High attention to detail, sound judgment, and a strong commitment to maintaining a healthy and sustainable credit portfolio.