Chakravarthi Manepalli
FinCrime, Risk & Data Analytics Professional
Professional Summary
FinCrime, Risk & Data Analytics professional with experience across AML, KYC and CDD reviews, fraud and financial crime risk analysis, and transaction risk investigation. Combines a financial-services risk foundation with hands-on analytics — SQL, Python (Pandas, NumPy), advanced Excel, Power BI and Tableau — to analyse transaction and customer data, detect anomalies, segment risk, visualise trends and support data-driven decisions. Targeting Risk Analyst, Fraud & Risk Analytics, Data Analyst and Business Analyst roles.
Core Competencies
Professional Experience
FinCrime Analyst · Revolut
April 2026 – Present- Conduct customer due diligence (CDD) and AML/KYC reviews
- Investigate financial crime and fraud risk indicators
- Assess and document risk using structured analytical methods
- Apply data-driven reasoning to support compliance decisions
- Escalate and report findings clearly to relevant stakeholders
MHLS Advisor · Amazon
September 2025 – February 2026- Resolved employee and customer queries within defined processes
- Maintained process compliance and accurate case documentation
- Identified recurring issue patterns and recommended improvements
Transaction Risk Investigator · Amazon
July 2024 – January 2025- Investigated suspicious transactions and account activity
- Analysed transaction patterns to detect anomalies and fraud risk
- Evaluated risk signals to support accurate decisioning
- Documented investigation outcomes and risk rationale
Data Analyst Intern · Ai Variant
May 2023 – November 2023- Built interactive dashboards for business reporting
- Wrote SQL queries to extract and aggregate datasets
- Cleaned and prepared data using Python and Excel
- Derived insights and visualised trends for stakeholders
Independent Personal Projects
Credit Card Transaction Analysis & Fraud Insights — Fraud Analytics
Analysed credit card transaction data to identify fraud patterns — built a Power BI dashboard covering transaction volume, fraud-rate trends, high-risk transactions, merchant-level risk and category-wise fraud distribution with KPI cards, slicers and time-based analysis.
Tools: Power BI, SQL, DAX, Data Modeling · Data: Publicly available / synthetic transaction dataset
Loan Evaluation & Risk Assessment System — Credit Risk
Built an interactive credit-risk evaluation tool that scores applicants, segments risk levels and recommends loan decisions — includes credit scoring, geographic risk factors and a live demo running the full rules engine in the browser.
Tools: Python, Pandas, NumPy, TypeScript, REST API · Data: Synthetic applicant data
Ecommerce Sales Dashboard — Business Intelligence
Developed a business dashboard analysing sales performance, customer behaviour and revenue trends — visualised KPIs and segment-level performance to support commercial decision making.
Tools: Power BI, Excel, DAX · Data: Publicly available sales dataset
Combined Cycle Power Plant Energy Prediction — Machine Learning
Developed and evaluated an XGBoost regression model predicting net hourly energy output (R² 0.963) — includes outlier handling, train/test evaluation, feature importance and a live demo running the trained model in the browser.
Tools: Python, XGBoost, Pandas, Scikit-learn · Data: Public UCI dataset
NLP Sentiment Analysis — Python Analytics
Built an end-to-end text analysis pipeline — preprocessing, sentiment classification and visualisation of results using Python.
Tools: Python, NLTK, Matplotlib · Data: Publicly available text dataset
Automation Medicine Dispenser Machine — Engineering
Final engineering project focused on automating medicine dispensing to improve efficiency and accuracy.
Tools: Mechatronics, Automation, Prototyping · Data: Academic project
Technical Skills
Data & Technical: SQL, Python, Pandas, NumPy, Microsoft Excel (Advanced), Power BI, Tableau, DAX, Data Modeling
Analytics & Business Intelligence: Data Analysis, Data Visualization, Dashboard Development, Business Intelligence, Statistics, Trend Analysis, Anomaly Detection, Segmentation, Reporting
Risk & Financial Crime: Risk Analytics, Fraud Analysis, Transaction Monitoring Concepts, AML, KYC, CDD, Financial Crime Compliance, Risk Assessment, Credit Risk Analysis
Analytical & Professional: Investigation, Analytical Thinking, Root-Cause Analysis, Problem Solving, Data-Driven Decision Making, Stakeholder Communication, Attention to Detail
Education
MBA in Finance — Andhra University
Expected: 2026B.Tech in Mechanical Engineering — Avanthi Institute of Engineering & Technology
Graduated: 2023Diploma in Mechanical Engineering — Government Polytechnic College, Narsipatnam
Graduated: 2019Certifications
- IBM Data Analyst Professional Certificate
- IBM Data Science Professional Certificate
- ExcelR Data Analyst Certification
- Google Analytics Certification
- KPMG Data Analytics Virtual Internship
- PwC Power BI Virtual Experience
This is a personal portfolio and does not represent or speak on behalf of Revolut or any other employer. All projects shown are personal or independently completed work using publicly available, synthetic, or independently sourced data. No confidential, proprietary, customer, internal, or non-public employer information is included.