Credit risk and lending professional turning underwriting experience into analytics projects across fintech, forecasting, customer behaviour, Power BI dashboards, and decision-support models.
I bring hands-on experience in credit underwriting, affordability assessment, KYC/compliance checks, financial documentation review, lending decision support, and research analytics. I am currently completing a Master of Business Analytics at the University of Auckland, with a focus on applying analytics, dashboards, automation, and machine learning to real business and financial problems.
- Credit risk analysis, lending decision support, and financial statement interpretation
- Business analytics for fintech, customer behaviour, operations, and strategic decision-making
- Data cleaning, modelling, reporting, dashboarding, and communicating insights for business users
- Building a practical portfolio across Python, SQL/SQLite, Power BI, R, Excel, and project analytics
Research Analyst Intern | Technology Investment Network (TIN)
Apr 2026 - Present | Auckland, New Zealand
Supporting technology-sector research, data validation, reporting, and Python-based automation for Power BI-ready workflows.
Assistant Manager Credit | Leap Finance
Nov 2021 - Mar 2025 | Bengaluru, India
Assessed international education loan applications through credit analysis, affordability assessment, customer discussions, KYC, and underwriting support.
Credit Manager | The Muthoot Group
Sep 2019 - May 2021 | India
Evaluated personal loan applications, conducted customer discussions and field verification, and supported responsible lending decisions.
- Built fintech lending models using borrower attributes to analyse loan interest rate drivers.
- Designed Power BI and R-based analytics workflows for Netflix content clustering and customer behaviour analysis.
- Developing Python and one-click batch-file automation that supports data processing, reporting graphs, and Power BI dashboard visualisation workflows.
- Created SQL/SQLite, Excel, Python, and project analytics portfolio work across finance, tourism, retirement planning, and scheduling risk.
| Area | Tools and methods |
|---|---|
| Data analysis | Python, pandas, NumPy, R, Excel, data cleaning, feature engineering |
| Databases | SQL, SQLite, star schema design, fact/dimension modelling, joins, aggregation |
| Visualisation | Power BI, DAX, Power Query, Matplotlib, Seaborn, ggplot2, dashboard storytelling |
| Automation | Python scripting, batch files, workflow automation, Power BI process support |
| Machine learning | Regression, decision trees, random forests, LightGBM, clustering, model evaluation |
| Finance analytics | Credit assessment, affordability, repayment capacity, FOIR, DTI, LTV, Fama-French modelling |
| Project management | Project Libre, critical path analysis, crashing analysis, risk-aware delivery planning |
These are academic and applied analytics projects prepared as public portfolio repositories with cleaned notebooks, reports, datasets, and documentation.
| Project | Summary | Tools |
|---|---|---|
| LendingClub Loan Interest Rate Modelling | Used borrower and loan attributes to explore loan grade distribution, feature engineering, and tree-based regression for fintech lending analysis. | Python, scikit-learn, decision trees |
| Macroeconomic Data Warehouse | Designed a SQLite star schema for macroeconomic indicators, including country, time, measure, activity dimensions and fact tables for GDP growth, PPP expenditure, and productivity. | SQLite, SQL, data warehousing |
| House Price Prediction | Prepared imperfect housing data, handled missing values, selected regression models with cross-validation, evaluated performance, and interpreted feature importance. | Python, scikit-learn, GridSearchCV |
| Global Tourism Recovery Analysis | Analysed post-COVID tourism recovery using UN Tourism arrivals, World Bank GDP data, country-code integration, COVID phase labels, and visitor sentiment context. | Python, pandas, NumPy, Seaborn, Matplotlib, NLTK |
| PlatefulNZ Customer Churn Prediction | Built churn analysis for a NZ meal-kit provider, comparing logistic regression, random forest, and LightGBM to identify retention drivers and at-risk customer segments. | R, predictive analytics, classification, feature engineering |
| Netflix Content Clustering and Power BI Dashboard | Applied k-means clustering to Netflix/movie data using genre, duration, country, and critic score features, with dashboard pages for ratings, country trends, and content strategy. | R, Power BI, k-means, PCA, ggplot2 |
| Superannuation Retirement Planning Sensitivity Analysis | Modelled retirement readiness using annuity logic, Monte Carlo-style scenario analysis, and sensitivity testing across contribution, return, inflation, and allocation assumptions. | Excel, financial modelling, sensitivity analysis |
| Portfolio and Risk Factor Modelling | Simulated stochastic processes and estimated a Fama-French three-factor model for a buy-and-hold technology portfolio. | Python, NumPy, pandas, statsmodels, yfinance |
| Conference Project Scheduling Analysis | Evaluated project completion risk using critical path analysis, scenario crashing, cost trade-offs, and confidence-based delivery planning. | Project Libre, Excel, project analytics |
- Assessed customer creditworthiness using income, liabilities, repayment behaviour, and financial documentation.
- Supported consumer and SME lending decisions using internal policy, risk indicators, and structured credit frameworks.
- Evaluated affordability, repayment capacity, exposure levels, and early signs of repayment stress.
- Worked with KYC, responsible lending principles, compliance checks, stakeholder communication, and credit record accuracy.
- Experienced with credit appraisal, underwriting, risk assessment, audit support, Excel-based analysis, MYOB, CRM, and loan origination systems.
- Additional public GitHub versions of my university analytics projects with reproducible notebooks and clear READMEs
- Power BI dashboards and workflow automation for research, portfolio, customer, and risk analysis
- A fintech analytics portfolio connecting credit risk experience with Python, SQL, R, and business intelligence
- GitHub: Sree0-0-9
- LinkedIn: linkedin.com/in/sreenathsuman
- Email: sreenathsuman1@gmail.com
I am building my portfolio around the intersection of credit risk, fintech, business analytics, and practical decision-support systems.