BI Analyst

We are seeking a highly analytical and detail-oriented Business Intelligence (BI) Analyst to support data-driven decision-making across our consumer finance and installment lending business. The role is responsible for generating actionable insights related to loan performance, customer behavior, risk trends, collections efficiency, fraud detection, and sales conversion optimization.

The ideal candidate has strong experience in fintech, digital lending, or consumer finance environments and possesses advanced analytical skills with a solid understanding of lending operations and portfolio performance metrics. This role will work closely with Risk, Credit, Sales, Collections, Product, and Operations teams to improve portfolio quality, operational efficiency, and business growth.

• Analyze the end-to-end lending funnel including:
  • Customer applications
  • Credit approvals
  • Loan disbursements
  • Repayment behavior
  • Delinquency trends
  • Collections performance
• Monitor and track key lending KPIs such as:
  • Approval Rate
  • Conversion Rate
  • Disbursement Rate
  • Portfolio-at-Risk (PAR)
  • M1/M2+ Delinquency
  • Roll Rate
  • Vintage Analysis
  • DPD (Days Past Due)
  • Recovery Rate
• Conduct deep-dive analyses to identify portfolio trends, customer behavior patterns, and operational inefficiencies.

• Develop and maintain automated dashboards and reports using BI tools such as Power BI or Tableau.
• Create real-time monitoring dashboards for:
  • Credit Risk
  • Collections Performance
  • Merchant/Channel Performance
  • Fraud Monitoring
  • Operational KPIs
• Ensure data accuracy, consistency, and timely reporting for management and business stakeholders.

• Support Risk and Collections teams through portfolio analysis, segmentation, and predictive insights.
• Analyze delinquency movement, roll-forward behavior, and collection effectiveness.
• Assist in evaluating and improving credit policies, scorecards, and underwriting strategies.
• Identify early warning indicators and emerging risk trends within the lending portfolio.

• Conduct fraud pattern analysis and identify suspicious customer or merchant activities.
• Support fraud prevention initiatives through anomaly detection and behavioral analytics.
• Collaborate with Fraud and Risk teams to improve controls, monitoring frameworks, and decision models.

• Analyze merchant, sales channel, and product performance to identify growth opportunities and operational gaps.
• Support pricing analysis, campaign evaluation, and profitability studies.
• Provide recommendations to improve conversion rates, loan quality, and customer acquisition efficiency.

• Work closely with Risk, Sales, Collections, Operations, Product, and Technology teams to support strategic initiatives.
• Translate complex data into actionable business insights and management presentations.
• Assist in ad hoc analysis and business case preparation for new projects or process improvements.

• Bachelor’s Degree in Statistics, Mathematics, Economics, Computer Science, Business Analytics, Finance, or related field.
• Minimum of 2–5 years of experience in Business Intelligence, Data Analytics, Risk Analytics, or Collections Analytics within the fintech, digital lending, or consumer finance industry.
• Must have experience from consumer finance or installment lending companies such as:
  • Home Credit
  • Salmon
  • BillEase
  • Tonik
  • or similar lending/fintech organizations.
• Strong SQL skills are mandatory.
• Proficient in BI and visualization tools such as:
  • Power BI
  • Tableau
  • Google Data Studio or similar platforms
• Strong understanding of lending and collections KPIs including:
  • DPD
  • Vintage Analysis
  • Roll Rate
  • PAR
  • Recovery Metrics
• Experience in risk analytics, collections analytics, or fraud analytics is highly preferred.
• Advanced proficiency in Excel and data analysis techniques.
• Knowledge of Python, R, or statistical modeling tools is an advantage.
• Strong analytical thinking, problem-solving, and presentation skills.
• Ability to work in a fast-paced fintech environment and manage multiple priorities.

• Experience in digital lending, BNPL, credit cards, or unsecured lending products.
• Familiarity with data warehousing and ETL processes.
• Exposure to machine learning or predictive analytics is an advantage.
• Experience handling large datasets and creating automated reporting solutions.

• Business Intelligence & Data Analytics
• SQL & Data Querying
• Dashboard Development
• Credit Risk Analytics
• Collections Analytics
• Fraud Detection & Monitoring
• Portfolio Performance Analysis
• Data Visualization
• Problem Solving & Critical Thinking
• Stakeholder Management
• Process Improvement & Automation