Wealthdoor
Smart Wealth Management & Goal-Based Investing Platform
Problem Statement
Key Pain Points
- Generic investing apps lacked personalized investment planning for USA investors.
- Users were confused by complex risk assessment models and unclear portfolio suggestions.
- Manual paperwork during onboarding and KYC reduced conversion rates.
- Lack of real-time data visualization (charts, indicators) limited awareness.
- Fragmented systems created inefficiencies and caused early drop-offs during onboarding.
- Traditional apps failed to align portfolio recommendations with personal risk profiles.
Key Metrics
Investors were unable to complete journeys confidently, revealing gaps in onboarding, risk mapping, portfolio intelligence and user engagement.
The Solution
Intelligent Risk Profiling Engine
A custom-built assessment framework that evaluates users’ financial behaviour, investment experience, liquidity needs and emotional risk tolerance. This algorithm classifies users into: Conservative, Moderate, Aggressive. This personalisation dramatically improves portfolio accuracy and investor confidence.
Automated Goal-Based Portfolio Builder
Users can create financial goals such as: Retirement, Education, Emergency Fund ,Custom Goals. The system recommends: Monthly Investment Amount, Portfolio builder, Asset allocation mix. The portfolio dynamically distributes funds into stocks, bonds, ETFs, based on the user’s risk class.
Fully Digital KYC & Onboarding
Paperless onboarding flow: ID verification, Bank linking via Plaid, Personal and Address Details, This eliminated manual intervention and improved onboarding success
Real-Time Trading with Candle Charts
A trading UI inspired by modern platforms like Groww: Candlestick charts, Live ticks, Volume indicators, Buy/sell flows, Watchlist management. Users can make informed decisions based on real-time trends.
A unified wealth management ecosystem that delivers personalized portfolios, automated investing, robust trading tools and a frictionless mobile-first experience.
Our Approach
Discovery Phase
- Industry research on USA investing flows
- Competitor analysis
- Risk-profiling framework study
Deliverable:
Research Insights Document
Design and Planning Phase
- User personas created
- Risk-to-portfolio mapping
- Flow design
- KYC journey mapping
Deliverable:
Functional Specs & User Stories
Development and Integration Phase
- Investment goal workflows
- Dashboard wireframes
- Charting interface prototypes
Deliverable:
Wireframes, UX Task Flows
Testing and Deployment Phase
- Modern mobile-first design
- Clean API orchestration
- Scalable microservice architecture
Deliverable:
Final Product Release
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OneClick Expertise in Various Full-Stack Combinations
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FastAPI + PostgreSQL
Purpose: Reliable transactional data layer. How it works: FastAPI exposes APIs, PostgreSQL stores user accounts, portfolios, goals, transactions, SIP histories. Use case: All financial data, orders, investments, audit logs.
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Next.js + PayloadCMS
Purpose: Flexible admin and CMS system. How it works: PayloadCMS provides content models; Next.js provides the UI. Use case: Education content, risk guides, FAQs, onboarding steps, banners.
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PayloadCMS + MongoDB
Purpose: High-speed content management. How it works: PayloadCMS uses MongoDB for storing dynamic content and admin metadata. Use case: Articles, disclaimers, notifications, investment education.
Team Structure
| Role | Responsibility |
|---|---|
| Business Analyst | Requirement gathering, mapping financial flows |
| Project Manager | Delivery management & client coordination |
| Solution Architect | System architecture and technology strategy |
| UX/UI Designer | App design & goal-based journeys |
| Flutter Developer | Mobile app development |
| Backend Developer | Python/FastAPI microservices |
| CMS Developer | Next.js/PayloadCMS |
| QA Engineer | Testing & validation |
| DevOps Engineer | AWS deployment & CI/CD |
Technology Used
Technology Used
Core Languages & Runtime
- Python
- Dart
Frameworks & Servers
- FastAPI
- Uvicorn
- Flutter
Databases
- PostgreSQL
ORM & Data Access
- SQLAlchemy
- Psycopg2
State Management
- GetX
UI & Styling
- Material Design
- Cupertino Widgets
- Custom Themes
Networking & API
- HTTP
- Swagger (OpenAPI)
Authentication & Security
- JWT
- Social Login
- Authentication handled at BFF service level (Java)
Scheduling & Background Jobs
- APScheduler
Data Validation
- Pydantic
- Local Storage
- Shared Preferences
Push Notifications
- Firebase Cloud Messaging (FCM)
Animations & Media
- Flutter Animations (Implicit & Explicit)
- Lottie for Flutter
Payments & Subscriptions
- Stripe Flutter
- Plaid
- In-App Purchases
Cloud & DevOps
- Docker
- AWS EKS
- AWS ECR
Testing & Quality Assurance
- Widget Testing
- Integration Testing
Design Samples
Comprehensive design system and development samples demonstrating the technical excellence and visual appeal of the Outfitter platform.
Competitor Analysis
| Parameter | Competitor | Our Solution | Opportunity |
|---|---|---|---|
| Core Offering | Generic investment apps with limited personalization | Risk-based portfolio creation + goal mapping | Introduce AI-driven advisory, and rebalancing |
| Customer Experience | Basic Goal Investment and trading UI | Personalized dashboards, real-time charts, curated recommendations | Build smart nudges & insights based on user behavior |
| Communication | Generic push/SMS alerts | Richer KYC notifications | Expand to email automation |
| Admin Controls | Standard data dashboards | CMS + admin tools with portfolio & KYC oversight | Add advanced analytics & customer lifecycle tracking |
| Mobile Responsiveness | Good UI but not goal-focused journeys | Mobile-first UX tailored for investing and risk capture | Build micro-interactions improving conversion |
| Risk Profiling | Basic questions | Advanced scoring logic with custom portfolio allocation | Risk drift detection |
Project Outcomes
Reduced Manual Intervention
Automated risk scoring and goal planning to streamline processes.
Eliminated Portfolio Misallocation
Achieved high accuracy with algorithmic risk-based investment suggestions.
Accelerated Onboarding
Optimized KYC and risk assessment processes, reducing drop-offs by 40%.
Boosted Repeat Investment
Enhanced engagement by 33% through personalized portfolio nudges
Improved Financial Clarity
Provided real-time portfolio analytics and optimized allocations for better decision-making.
Key Outcomes Metrics
| Key Outcomes Metrics | Before Implementation | After Implementation |
|---|---|---|
| Manual Data Handling | 85% | 5% |
| Risk Profiling Accuracy | 45% | 92% |
| Repeat Investments | 30% | 63% |
| Portfolio Recommendation Accuracy | 50% | 88% |
| Server Reliability | 70% uptime | 99.5% uptime |
