Features Progress

Features Completed Since Launch

Since the first deployment, the platform has evolved. Key capabilities now include a structured analyst → approver process, multi-cycle review handling, and a complete audit trail that records every action with timestamps and user identity.

Role-based access ensures that analysts and approvers operate within clearly defined permissions. Reviews can be submitted, commented on, approved, or closed with full transparency. A dedicated dashboard gives approvers a clear view of all pending and active reviews.

Financial data can now be uploaded directly from Excel, allowing analysts to import key ratios and borrower information without manual entry. Key financials are stored in the central database for further use such as peer comparisons or portfolio overviews.

Future Features

🖼️ Drag & Drop from Snipping Tool: While image uploads and drag-and-drop from file explorer are already supported, future updates may allow direct paste or drag from tools like Windows Snipping Tool, streamlining workflows for users.

🔐 Role-Based Access & Audit Trail: A granular permission system will ensure that reviewers, approvers, and administrators have appropriate access levels. Every action will be logged with timestamps and user identity, supporting internal controls and external audits. Escalation paths for flagged reviews are also being explored.

📊 Portfolio Dashboard: A centralized dashboard will provide real-time visibility into all loan exposures, including metrics like Loss Given Default (LGD), rating distributions, and sectoral breakdowns. This will support portfolio-level risk monitoring and regulatory reporting.

📄 Centralised File Storage: Borrower-specific documents — such as annual reports, due-diligence files, and other relevant materials — should be stored using a standardized file-naming convention to ensure consistency across uploads.

📄 Automated Document Parsing: Personal R&D on NLP tools will explore extracting key financial metrics and qualitative insights from uploaded PDFs or borrower documents. This aims to reduce manual data entry and improve consistency across reviews.

📄 Risk and Industry Classifications: Each borrower review should include classifications such as performing, watchlist, default, and industry‑specific risk categories.

📄 Default, Recovery, LGD Enhancements: Current LGD and recovery estimates are based on a simulated one-year payment default. Future enhancements may include two-year and three-year simulations, including Expected Loss calculations.

🔑 User Authentication & Sign-Up: While the platform currently focuses on showcasing credit-review functionality, a full authentication cycle (registration confirmation, password reset, session management) may be added. As modern authentication flows are already familiar territory, the emphasis remains on features that deepen coding expertise and demonstrate hybrid skills in credit risk and software development.

🌐 Automatic Market Data Feeds: Future updates may allow the platform to pull key market references — such as EURIBOR and SOFR — directly from external sources. Instead of typing these values manually, the system would fetch them automatically.

🔄 Sharing Data Through APIs: The platform may expose borrower and review data through a simple API, allowing other tools or systems to connect, retrieve information, and process it further. In other words, the app will not only store data — it will be able to “talk” to other software.

☁️ Exploring Cloud Service Concepts: Longer-term experimentation will focus on scalable, multi-tenant architecture. The idea is similar to offering the app as a cloud service where each party has its own secure environment within the same system. This is primarily a learning journey to deepen understanding of modern cloud approaches rather than a commercial objective.