Overview

The Loan Markets Association (LMA) is an organisation "up my alley" as I am from an economics background and previously worked at the British Bankers' Association (BBA), which covered some of the things within the remit of the LMA and also set the world's London Interbank Offered Rate (LIBOR) until the infamous controversy led to investigations and prosecutions surrounding the rate and reforms about it. The BBA no longer exists and its successor is now UK Finance. As someone from London, perhaps humorously, there is no need for the LMA to fund an airfare ticket in the event of winning since I'm based in London and I am well aware of The Brewery, where LMA Edge 2026 is expected to take place 😉 .

Economic importance of loans

It's practically universally accepted among economists that access to credit is one of the key ingredients of economic growth. The economic historian Niall Ferguson remarked that credit was humanity's greatest invention. Relatedly, the availability of loans determines how successful an economy is: when an economy contracts, there is less availability for loans, and when an economy expands, there is more availability for loans. At my age, I have lived through both kinds of periods, such as the infamous "credit crunch" in 2008 in the United Kingdom and the dotcom bubble of the late 1990s. In extreme situations, a lack of availability for loans can cause a depression, such as that seen during the Great Depression.

Motivation for program

I have developed a strong interest in network theory. Network theory studies the relationship between different entities, such as the connection between friends, political parties and universities. One concept in network theory is how quickly something spreads throughout a given network. This is usually called an "epidemic" or "contagion", and there are a number of models used within network theory to represent this. Something I am personally interested in is financial contagion and what causes systemic risks to the economy.

There are many theoretical/mathematical concepts behind the level of exposure one takes when lending out money to a different entity such as "correlated defaults", etc, but this is far beyond the scope of Devpost.

Description of program

This program utilises graph technology to represent and visualise the level of exposure a financial institution has when they provide a loan to a different institution. It utilises the API provided by Companies House, which is the official register for all companies and other organisations in the United Kingdom and to which all must be registered to. The program also has a "demo version" for those who do not have an API key for Companies House.

The nodes or "circles" represent the institutions themselves and the lines or "edges" between the nodes represent the relationship. The greater the width of the line or edge, the more exposed a given financial institution is.

Artificial intelligence declaration

The code to create this program was "vibe-coded" in Amazon Web Services Bedrock, using the Claude Opus 4 model provided by Anthropic. This particular project description has been written entirely by a human.

Built With

• neo4j