Nidhi Jha

Unified Loan & Security Mapping System

• Helped build a system that links all loans and securities to one unique customer ID.
• Previously, customers with multiple loans using the same security would get separate IDs — now resolved by adding a dropdown to select from existing securities.
• This solution ensures cleaner data and enables teams to view full customer loan portfolios clearly, supporting better analysis and reporting.

Automated Error Reporting & Dashboard Development

• Created a Python script that automatically pulls monthly loan processing data from Excel sheets and generates PowerPoint reports, highlighting error types and volumes.
• This automation saves time, improves accuracy, and supports monthly performance reviews.
• Currently building an interactive dashboard to visualize trends and help teams identify and resolve issues faster.

Data Remediation & Quality Checks

• Regularly review, clean, and fix errors in loan data — including correcting missing fields, resolving duplication, and validating customer-security relationships.
• Ensure data consistency and compliance with internal standards and external regulatory requirements.

Strong Understanding of Banking & Loan Operations

• Well-versed in banking terms and processes such as:
  Loan Origination (customer onboarding, KYC)
  Collateral Management (securities linked to loans)
  Credit Risk Assessment (eligibility, scoring)
  Loan Disbursement & Repayment Cycles
  Regulatory Compliance (AML, OFAC, audit readiness)
• This knowledge helps me communicate effectively across teams and ensure our data aligns with how banking systems actually operate.

Automated Compliance Screening (OFAC)

• Improved the OFAC (Office of Foreign Assets Control) screening process by automating key steps using Python scripts.
• This led to a 30% increase in screening efficiency, helping the client stay compliant with regulatory checks faster and more accurately.

Model Validation & Accuracy Enhancement

• Worked on validating and fine-tuning financial risk models used by banking clients.
• Improved model accuracy by 15% through structured testing and careful parameter tuning, which led to more reliable risk predictions.

AML Risk Detection Improvement

• Helped detect suspicious transactions more effectively in Anti-Money Laundering (AML) systems.
• Increased detection accuracy by 20%, contributing to stronger compliance and fraud prevention.

Sales & Profit Optimization through EDA

• Conducted detailed Exploratory Data Analysis (EDA) for a retail client.
• Identified trends in sales data and customer behavior that led to a 25% increase in profits through improved decision-making.

Data Cleaning & Interface Development

• Cleaned, merged, and restructured large datasets to improve data quality and reduce errors.
• Built simple and user-friendly interfaces for Relationship Managers (RMs), making it easier for them to access customer insights and interact with clients.

CI/CD Pipeline Development

• Created Continuous Integration and Continuous Deployment (CI/CD) pipelines using Jenkins, which helped speed up software deployment and improved reliability across environments.

Infrastructure Automation with Terraform & GCP

• Automated cloud infrastructure setup for a credit agency client using Terraform and Google Cloud Platform (GCP).
• This reduced manual tasks and made it easier to manage scalable environments for storage and virtual machines.

Java-GCP Integration

• Integrated Java-based applications with GCP services, allowing smoother data flow and more efficient backend operations.
• Reduced manual work by 20% through better system design and integration.

Python Deployment & Automation Enhancements

• Improved the deployment process for Python projects by introducing continuous integration techniques.
• Automated builds and deployments using Jenkins, increasing stability and delivery speed for development teams.