Credit Risk Analyst - Loan against Property

We are seeking a detail-oriented and analytical Data Analyst to support the Strategy team for the Loan Against Property (LAP) business. The role involves analyzing customer data, underwriting patterns, portfolio performance, and market trends to support strategic decision-making and business planning.

Key Responsibilities:

• Analyse borrower profiles, bank statements, credit bureau data, and other financial information to support credit assessment and strategic decision-making.
• Prepare and maintain daily, weekly, and monthly MIS reports covering sanctions, disbursements, TAT, delinquency trends, bounce rates, and overall portfolio performance.
• Identify growth opportunities, process improvements, and support the development of credit scorecards, projection models, policy triggers, and other credit strategy frameworks.
• Conduct competitor and market analysis to support business initiatives and strengthen risk and credit decision processes.
• Monitor portfolio performance, identify early warning signals, and perform deep-dive analysis on NPAs, PD/LGD trends, customer cohorts, losses, and underwriting deviations.
• Build and manage dashboards using Excel, Power BI, or Tableau for portfolio tracking, segment-wise performance, and risk monitoring.
• Clean, structure, validate, and manage data from LOS, LMS, CRM, CBS, and bureau sources while ensuring data integrity, accuracy, and audit readiness.
• Use SQL/Python/R for data extraction, transformation, modelling, projections, and advanced analytics to support business and credit functions.

What were looking for:

• 02 years of experience in credit, risk, strategy, or analytics within NBFCs/Banks/HFCs.
• Bachelors degree in engineering, Finance, Economics, Statistics, Mathematics, or a related field.
• Strong analytical and quantitative skills with understanding of credit fundamentals, lending, and exposure to LAP underwriting or portfolio analytics.
• Advanced Excel capability with proficiency in SQL and foundational Python for data analysis and modelling.
• Ability to build financial and credit projections along with experience working on credit bureau data (CIBIL/CRIF/Experian).
• Strong attention to detail, data accuracy, problem-solving, and clear communication of insights and recommendations.
• High ownership, ability to manage multiple tasks/timelines, and a proactive, collaborative mindset.

About Kissht:

Kissht, a Great Place to Work certified organization, is a consumer-first credit app that is transforming the landscape of consumer credit. As one of the fastest-growing and most respected FinTech companies, Kissht is a pioneer in data and machine-based lending. With over 15 million customers, including 40% from tier 2 cities and beyond, we offer both short and long-term loans for personal consumption, business needs, and recurring expenses.

Founded by Ranvir and Krishnan, alumni of IIT and IIM, and backed by renowned investors like Endiya Partners, the Brunei Investment Authority, and the Singapore Government, Kissht is synonymous with excellence in the industry. Join us and be a part of a dynamic, innovative company that is changing the future of financial technology.