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  Your loan document, checked !

Inspiration

When I first registered for the LMA Edge Hackathon, I didn’t immediately know what to build. Instead of forcing an idea, I started by reading — the LMA website, LinkedIn posts, and shared resources. Even when I wasn’t actively brainstorming, the themes around loan documentation, efficiency, and transparency stayed with me as I went about my daily routine.

I spend a lot of time studying and reading, and in my leisure time I enjoy watching movies. During this period, I was watching a legal movie focused on pro bono work. A key part of the story involved a loan dispute, and what stood out was how lawyers had to go through hundreds of pages of loan documents just to find what mattered. That moment sparked a simple but powerful question: why is understanding loan documents still this hard?

When I study, I use highlighters to mark important details so I can quickly revisit why something matters. That led to the idea: what if loan documents could be digitally highlighted, with each highlight explaining why it was flagged? That was the moment Chequeck was born.

What it does

Chequeck cross-checks loan documents against predefined rules and standards to surface risk, inconsistencies, and missing information.

Instead of treating loan agreements as static PDFs, Chequeck highlights important clauses digitally and explains why they matter — whether a clause is missing, inconsistent, non-standard, or potentially risky. Each highlight is tied to a clear rule, making complex documents faster to review and easier to understand.

How we built it

Chequeck was designed as a rule-driven system. Loan documents are ingested and broken down into clauses, which are then checked against a set of predefined rules inspired by market standards and best practices.

Rather than attempting to interpret legal meaning, the focus stayed on deterministic checks: presence of required clauses, consistency of definitions, conflicts introduced by amendments, and deviations from expected structure. The interface was intentionally kept simple — highlighting clauses and attaching clear explanations to each flag.

Challenges we ran into

One major challenge was scope. It was tempting to over-automate or promise full legal interpretation, but that would introduce risk and complexity. Keeping the solution focused on clarity, consistency, and explainability was a deliberate and necessary constraint.

Another challenge was user experience. Loan documents are already dense, so the system had to reduce cognitive load rather than add to it. Designing highlights that inform without overwhelming took careful thought.

Accomplishments that we're proud of

Turning a vague frustration into a clear, focused product idea

Designing a solution that aligns with existing loan market workflows

Creating a system that emphasizes explainability and auditability

Translating complex documentation problems into simple visual signals

What we learned

This project highlighted how manual and fragmented loan documentation still is, despite the size of the market. It also reinforced the importance of standards — technology is most effective when it amplifies agreed rules rather than trying to replace human judgment.

We also learned that in regulated markets, trust comes from predictability and transparency, not just automation.

What's next for Chequeck

The immediate next milestone is, hopefully, winning the LMA Edge Hackathon. Beyond that, the goal is to evolve Chequeck into a full‑fledged product and bring it to market.

This would involve hardening the rule engine, expanding coverage across more loan types, and refining the user experience for real‑world legal and banking workflows. Longer term, Chequeck could become a trusted layer that sits alongside existing loan processes, helping institutions review documents faster, reduce risk, and operate with greater confidence.

Features

1. Document Check Automatically reviews loan documents against predefined rules to flag missing clauses, risky terms, and inconsistencies—reducing oversight before signing.
2. Document Compare Compares two versions of a document to instantly surface edits, additions, or removals—so no “small change” slips through unnoticed.
3. Manual Check Allows users to upload a document and prompt specific checks they care about, enabling flexible, context-driven reviews beyond preset rules.

Target Users

1. Individuals & Borrowers People reviewing personal or business loan documents who want clarity before committing.

2. Startups & SMEs Founders and operators who deal with financing agreements but lack in-house legal teams.

3. Legal & Compliance Teams Professionals who need faster first-pass reviews and document comparisons without replacing human judgment.

4. Financial Institutions & Lenders Teams seeking consistent document checks and reduced risk from overlooked clauses.

Built With

• javascript
• mammoth
• nextjs
• pdfjs-dist
• react
• shadcn/ui
• tailwindcss
• typescript