Priyasha Harjani

1. Tech Transformation Analysis – Fee Leakage (SQL, SAS):

• Spearheaded the analysis for identifying fee leakages in different loan disbursal stages.
• Devised and delivered an analysis model to pinpoint discrepancies in fees collection and presented findings to stakeholders which resulted in mitigating 5% revenue loss.

2. Aavas Plus – Strategic Data Support (SAS, SQL):

• Developed data-driven models to identify high-performing loan customers eligible for top-up offers, based on repayment behavior and performance metrics.
• Collaborated with business stakeholders and telecalling teams to drive targeted outreach campaigns.
• Enabled lead generation efforts that contributed to a 5–10% increase in profits through additional top-up loans.
• Improved campaign targeting accuracy by 40%, increasing efficiency and conversion rates.

3. Login File Quality Monitoring (SAS, SQL):

• Designed and developed a data mart and automated MIS reports to monitor the quality of login files submitted by RO branches.
• Tracked and analyzed turnaround times to identify process bottlenecks at the draft stage, reducing delays and improving overall file processing speed.
• Achieved a 5% increase in login case volumes, directly enhancing loan pipeline efficiency and branch-level profitability.
• Utilized SQL and SAS extensively for large-scale data querying, statistical analysis, and performance monitoring.

Tools & Technologies: SAS, SQL, DBeaver, Excel

• Implemented an enterprise-grade Azure Data Lake to store raw data from multiple sources (databases, APIs), improving data accessibility and reducing manual data handling by 80%.
• Built ETL pipelines using Azure Data Factory for automated, scalable data ingestion and transformation, enhancing data migration efficiency and reliability.
• Performed data transformation and unification using Azure Databricks and PySpark, migrating cleaned data to Azure SQL Data Warehouse for advanced reporting use cases.
• Automated Daily and MTD MIS reports for collections and disbursements, improving reporting turnaround time by 60% and enabling faster decision-making.
• Developed and managed Power BI dashboards and KPI scorecards, creating custom visualizations for executive and operational stakeholders.
• Independently designed Risk Analysis Reports, identifying high-risk customers using factors such as age, bureau scores, payment behavior (bouncing), and existing loan exposure, aiding in proactive risk mitigation strategies.

Tools & Technologies: Azure Data Factory, Azure Databricks, Power BI, Python, PySpark, MS SQL Server, Jira