This project demonstrates Business Analysis skills applied to a real compliance automation problem at NovaPay Financial Services β a fictional fintech onboarding 500+ business entities monthly for their payment gateway.
The project reframes a technical ML implementation (KYC/KYB Entity Risk Scoring Engine) as a comprehensive BA deliverable, showcasing the ability to:
- Define clear problem statements and business cases
- Create detailed BRDs with proper requirements management
- Map and analyze business processes (As-Is vs To-Be)
- Write Agile user stories with real acceptance criteria
- Quantify and communicate business impact
KYC-KYB-Entity-Risk-Scoring-Engine/
βββ docs/
β βββ 01_executive_summary.md # Business case & ROI
β βββ 02_brd.md # Business Requirements Document
β βββ 03_process_mapping.md # As-Is vs To-Be analysis
β βββ 04_user_stories.md # Agile user stories (12 stories)
β βββ 05_business_impact.md # Quantified business impact
βββ kyb_process_dashboard.html # Visual dashboard
βββ src/
β βββ generate_entities.py # Data generation
β βββ train_model_kyb.py # ML model training
βββ data/
β βββ entities.csv
β βββ entities_scored.csv
β βββ model_results.json
βββ README.md # This file
βββ README_KYB.md # Technical documentation
1. Executive Summary (docs/01_executive_summary.md)
- Problem Statement: Manual KYB takes 5-7 days, costs βΉ2,800/entity
- Business Case: Cost savings, risk reduction, efficiency gains
- ROI Calculation: βΉ6.65L/month savings (53% reduction)
2. Business Requirements Document (docs/02_brd.md)
- Stakeholder Register: MLRO, Compliance Head, Tech Lead, Business Head
- RACI Matrix: Clear accountability mapping
- Functional Requirements: FR-01 to FR-12 with MoSCoW prioritization
- Non-Functional Requirements: Performance, security, RBI compliance
3. Process Mapping (docs/03_process_mapping.md)
- As-Is Process: 12-step manual KYB with pain points
- To-Be Process: Automated risk scoring with decision gates
- Time Comparison: 70% TAT reduction by risk tier
4. User Stories (docs/04_user_stories.md)
- 12 User Stories across 4 Epics
- Roles: Compliance Analyst, MLRO, Technology Lead, Business Relationship Manager
- Each Story: Acceptance Criteria (3-4 points), Priority, Story Points
5. Business Impact (docs/05_business_impact.md)
- 12 Metrics before vs after comparison
- Monthly Savings: βΉ7,47,500
- Annual Savings: βΉ90 Lakhs
- Payback Period: 4 months
| Metric | Before | After | Improvement |
|---|---|---|---|
| Average TAT | 5-7 days | 1-2 days | 70% faster |
| Cost per Onboarding | βΉ2,800 | βΉ900 | 68% reduction |
| High-Risk Detection | 40% | 92% | 130% improvement |
| Rework Rate | 35% | 8% | 77% reduction |
| Monthly Savings | - | βΉ7.5 Lakhs | βΉ90L/year |
| Category | Technology |
|---|---|
| ML Backend | Python, Scikit-learn, Gradient Boosting |
| Data | SQL, CSV, JSON |
| Visualization | Chart.js, HTML/CSS |
| Documentation | Markdown |
When discussing this project in BA interviews:
-
Problem Identification: "I identified a 5-7 day manual process with 35% rework rate as the core problem"
-
Requirements Management: "I created a BRD with 12 functional requirements, using MoSCoW prioritization to focus on Must-Haves"
-
Stakeholder Management: "I worked with 6 stakeholders including MLRO, Compliance Head, and Technology Lead, using RACI to clarify roles"
-
Process Analysis: "I mapped the As-Is process (12 manual steps) to To-Be (automated with decision gates), achieving 70% TAT reduction"
-
User Story Writing: "I wrote 12 user stories in standard format with specific acceptance criteria β not generic ones"
-
Business Impact: "I quantified the ROI as βΉ90L/year with 4-month payback, using internally consistent metrics"
-
Agile Delivery: "I planned 4 sprints with 53 story points, organized by Epic"
Author: Kishore U.
- GitHub: github.com/ukishore33
- LinkedIn: linkedin.com/in/kishore-techie
- Phone: 6303308133
This project is for demonstration purposes as part of a BA portfolio.
Built as a Business Analyst Portfolio Project | April 2026