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Date Entry - Loan Payment Sheet
Excel sheet for recording loan payment entries, helping
clients by deducting each payment from the original loan balance. It includes
date, time, amount, and the PIC who received cash for every transaction.
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This portfolio sample shows how I evaluate AI agents and automated workflows to find reliability problems, broken logic, and weak edge-case handling. I review whether the system completes the intended task, uses tools correctly, follows instructions, handles ambiguity, and produces an output that can actually be trusted.
The work focuses on identifying failure points before they become real user problems, including incomplete task execution, incorrect assumptions, workflow dead ends, hallucinations, and verification gaps. This is a portfolio demonstration of my AI agent evaluation and red-teaming work. No confidential client information is included.
Thorough breakdown! Robust edge-case handling and reliability checks are definitely the trickiest part of building reliable AI agents 🤖📊
This is a banking credit dashboard I built from scratch to turn messy loan application records into clear, actionable visuals. The main goal was to analyze what factors actually cause a loan to get approved or rejected.
Here is how I worked on this project manually:
Data Formatting: I cleaned and sorted the raw dataset in Excel, fixing missing rows and organizing the numbers for a flawless setup.
KPI Calculation: I calculated core credit metrics, such as total loan amounts, average annual income, average CIBIL scores (599.9), and the final approval percentage (62%).
Insightful Charts: I created custom visuals to show important comparisons, like loan approval rates based on education levels and a breakdown of residential vs commercial assets.
I designed this entire dashboard on a dark background to make the charts stand out and look clean. Anyone can click the filters on the side to update the whole screen instantly.
Tools used: Advanced Excel (Pivot Tables, Slicers, Data Visualization, Data Analysis)
This is a retail sales and profit dashboard I built from scratch to turn complex spreadsheet data into easy-to-read visuals. The main goal of this project was to make a messy dataset meaningful so a business owner can instantly check how their store is performing.
Here is how I worked on this project:
Data Cleaning: I went through the entire raw file in Excel, filtered out bad entries, and organized the rows to make sure the dashboard numbers are completely accurate.
KPI Tracking: I used Excel formulas to pull out core business metrics, such as total revenue, total orders, and the overall profit margin (12.47%).
Designing Charts: I set up clean visuals to show key trends, like sales by shipping modes, customer segments, and a breakdown of top-performing products.
I also added dynamic slicers, so you can click on any region or year and the whole screen updates automatically. I handled this entire project manually from start to finish.
Tools used: Advanced Excel (Pivot Tables, Slicers, Formulas, Dashboard Design)
