BI Analyst

PALMPAY LIMITED; Taguig; On-site; PHP 446,400 - 781,200; Full time

Job summary

PALMPAY LIMITED is seeking a highly analytical BI Analyst for their office in Taguig. This role focuses on generating actionable insights related to loan performance, customer behavior, and risk trends. The ideal candidate will have experience in fintech, specifically in consumer finance, with strong skills in SQL and BI tools.

The BI Analyst will work closely with multiple teams to enhance portfolio quality and facilitate data-driven decision-making. Key responsibilities include analytics, dashboard development, and supporting risk and collections strategies.

Qualifications

• Minimum of 2–5 years of experience in Business Intelligence, Data Analytics, or Risk Analytics.
• Strong analytical skills with a deep understanding of lending and collections KPIs.
• Proficient in BI and visualization tools.

Responsibilities

• Analyze the end-to-end lending funnel including customer applications and credit approvals.
• Develop and maintain automated dashboards using BI tools.
• Support Risk and Collections teams through portfolio analysis and predictive insights.

Skills

SQL

Business Intelligence & Data Analytics

Dashboard Development

Credit Risk Analytics

Collections Analytics

Fraud Detection & Monitoring

Data Visualization

Analytical Thinking

Problem Solving

Stakeholder Management

Education

Bachelor’s Degree in Statistics, Mathematics, Economics, Computer Science, Business Analytics, or Finance

Tools

Power BI

Tableau

Google Data Studio

Excel

Python

R

Job description

Job Title: BI Analyst
Location: BGC, Taguig (Full Time, Onsite)

Job Summary

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.

Key Responsibilities

Business & Portfolio Analytics

• 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.

Dashboard & Reporting Management

• 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.

Risk & Collections Analytics

• 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.

Fraud & Credit Risk Monitoring

• 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.

Channel & Business Performance Analysis

• 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.

Cross-Functional Collaboration

• 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.

Qualifications

• 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.

Preferred Qualifications

• 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.

Key Competencies

• 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