About LenDenClub
LenDenClub is India s largest RBI-registered (NBFC-P2P) Peer-to-Peer (P2P) lending platform. We are a platform for lenders seeking high interest with creditworthy borrowers, bridging the gap left by traditional credit institutions. With over 3 crore users and 16,000 crore+ in loans disbursed, we command more than 98% of India s P2P lending market. Our 4.4+ rating on the App Store reflects our commitment to offering a trustworthy and secure lending experience. Powered by cutting-edge technology and a user-first approach, we are setting new benchmarks in India s evolving fintech ecosystem. The progressive approach towards employee benefits has been acknowledged and appreciated and as a result, LenDenClub has been certified as a Great Place to Work successively for four years by the Great Place to Work Institute, Inc.
About InstaMoney
InstaMoney is our cutting-edge Loan Service Provider (LSP) platform, built to make borrowing fast, flexible, and fully digital for users across India. With over 30 million downloads, InstaMoney offers seamless credit access through a simple and intuitive mobile app. From Personal Loans and Merchant Loans, InstaMoney provides short- to mid-tenure credit solutions.
Role Overview
The Portfolio Analyst/Associate will join the Credit and Risk team to analyze loan portfolio performance, identify trends, and provide data-driven insights to shape credit risk strategy. Key responsibilities include transforming complex data into actionable recommendations to drive growth while mitigating risk. This role requires exceptional critical thinking and data management abilities.
Key Responsibilities
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Portfolio Monitoring:
Continuously monitor and analyze the performance of the lending portfolio, tracking key metrics such as delinquency, default rates, roll rates, and loss provisions. -
Data Analysis & Reporting:
Develop, maintain, and enhance comprehensive dashboards and reports in Excel and other BI tools to provide clear insights into portfolio health. -
Trend Identification:
Conduct deep-dive analyses on specific segments of the portfolio to identify emerging risk trends, performance drivers, and opportunities for optimization. -
Policy & Strategy:
Collaborate closely with the Credit Risk and Policy teams to assess the impact of new and existing policies, providing data-backed recommendations for adjustments. -
Data Management:
Manage and query large datasets, ensuring the integrity, accuracy, and consistency of data used for all analyses and reporting. -
Cross-functional Collaboration:
Work with various teams, including Collections, Product, and Technology, to understand performance drivers and contribute to strategic initiatives. -
Presentation:
Clearly and concisely present findings, insights, and recommendations to senior management and other key stakeholders.
Required Skills & Qualifications
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Experience:
1-3 years of experience in a data analysis, business analysis, or portfolio management role. -
Primary Skillset:
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Critical Thinking:
Demonstrated ability to analyze complex problems, challenge assumptions, and draw logical, data-driven conclusions. -
Data Management:
Proven ability to handle, manipulate, and analyze large, complex datasets with precision. -
Technical Skills:
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Advanced Microsoft Excel:
Exceptional proficiency is a must. Expertise in pivot tables, advanced formulas, data modeling, and scenario analysis is required. -
Domain Experience:
- Solid experience and understanding of
credit risk
and credit policy
. -
Education:
Graduate or MBA from Tier 2-3 colleges. A bachelors degree in Finance, Economics, Statistics, Engineering, or a related quantitative field.
Preferred Qualifications
-
Industry Experience:
Prior experience in the Digital Lending
or Fintech sector is highly preferred. -
Risk & Collections:
A good understanding of the end-to-end credit lifecycle, particularly risk and collections
strategies. -
Coding Skills:
Experience with SQL for data extraction and/or a programming language like Python or R for data analysis and automation will be a significant advantage. -
BI Tools:
Familiarity with data visualization tools.
