Rita Baviskar

Project - Axis Bank Ltd. Mumbai

1. Fraud Team.

• Card Dashboard: Analyzed credit and debit card data to present fraud numbers and monthly transactions.
• Create the transaction data.
• Segregate credit and debit data.
• Used that data for rule mapping, fraud tagging.
• Also, sorting non-fraud data, secure, and unsecure data.
• Analyzed real-time rule data (RTD rule) for both credit and debit.
• Create a dashboard (PPT) to present monthly credit, debit card fraud, non-fraud, secure, unsecure, and RTD data.
• MAB Dashboard: This dashboard was used to show monthly data of all the merchants. Like PayU, Razorpay, etc. In this dashboard, we present how many frauds occurred, how they happened, and where they happened.
• MORTGAGE DATA: Top-Up Home Loans study identifier for home loan top-up accounts and parent account LTV ratio at the time of sanction, risk weights for top-up loans Rs 30, Rs 60, and Rs 90. Identify the purpose of the loan to be picked from the field.
• Top-Up BScore Analysis: BScore at the time of application for the Top-Up loan, sourcing risk based on the account open month of the customer. After one year, checking the delinquency of Top-Up customers and BScore risk weights for Top-Up loans: Rs 30, Rs 60, and Rs 90.
• Digital vs. Physical view: Portfolio/Vertical delinquency numbers (Rs 30/Rs 60/Rs 90), open accounts/portfolio amount, disbursement numbers, early warning risk (12 MRs 90+ / 6 MRs 30+).
• Other Responsibilities: Create Bullion Report to analyze CA (Current Account) customer data. Create an MLM report to analyze Casa (Current and Savings Account) customer data. Analyzed daily PL data. Create RTD data and summary report. Create a Cash Cross Zone Report to analyze cash deposits from different zones, cash credits from different zones, multiple cash credits, and multiple cash withdrawals.

Project - Axis Bank Ltd. Mumbai

2. Data Engineering Team

• Data engineering involves coordinating with different teams to collect logic and extract the data from tables. Creating workflows on Informatica using SQL language. Uploading SBB month-end data.
• Analyzed business processes to identify areas for improvement and efficiency.
• Collaborated with stakeholders to gather and document business requirements.
• Created detailed reports and presentations for project updates and findings.
• Supported testing efforts by reviewing test cases and results for accuracy.
• Engaged with cross-functional teams to ensure alignment on project goals.
• Utilized data analysis tools to interpret trends and inform decision-making processes.
• Delivered timely support by tracking issues and communicating resolutions to end users.

• Evaluated impact of DC and CC Trigger Campaigns on credit card performance.
• Imported and exported Excel spreadsheets, CSV, and text files into SAS datasets.
• Created datasets according to project requirements.
• Developed and modified macros to streamline data processing.
• Mapped display rates, transactions, and customer details for analysis.
• Identified top performers in credit card campaigns.
• Assessed onboarding impact on customer engagement across various products.
• Prepared data extracts using SAS and SQL for reporting.

• Managed database operations through HDL to ensure accurate record-keeping.
• Created and maintained comprehensive worker profiles, including address and assignment details.
• Generated detailed reports to support project insights and decision-making.