Case Studies

Case Study: AI Enhances Leading Financial Platform

Fidra Analytics integrates AI into leading financial platform, Finbridge Global - supercharging their competitive edge and customer value.

Problem Statement

Finbridge Global is a portal for technology companies, providing services to Financial Institutions and Financial Investors to help them find each other and collaborate. Their platform simplifies the lengthy and restrictive typical RFI (request for information) process.

They identified ways AI could enhance their platform:

Hundreds of fintechs have signed up to the platform but many are yet to register with Finbridge Global. Previously, search results within the platform were limited to only those registered. Thousands of fintechs were missing out on connections with Financial Institutions and potential investors.
Relevant fintechs could only be found with keywords or assigned categories. In particular, the system lacked the ability to understand the inputs and so many compatible matches were not identified.
Other competitor fintech directories give unexciting results. Relevant fintechs are often listed plainly, with no other information. Moreover, the data relentlessly risks going stale, for fintechs are constantly evolving their capabilities. Finbridge also has a key focus on product assessment.

Finbridge Global wanted to improve the user experience and add value to the industry.
Fidra Analytics were brought in to enhance their software platform into something even more competitive, through the power of AI.

Our Approach

Fidra Analytics worked in two-week Agile Sprints to quickly produce a Proof of Concept and MVP; encompassing customer feedback to improve content personalisation, matching capabilities and insights.

Technical Overview

This AI implementation works in three stages.

Step 1 – information retrieval
The system scans three knowledge sources:
a) Finbridge Global’s data
b) The wider web; to catch all the fintechs not yet registered
c) Investopedia; to train the AI engine with the level of knowledge needed to understand the domain

The AI framework leverages vector search to identify what information is relevant to the user’s question.

Step 2- prompt generation
The system pairs the relevant information (found in Step 1) with the initial question and some company context- these form the prompt for the Large Language Model.

Step 3- the Large Language Model
The LLM generates a clear response for the user. Results utilise technical financial terms, accurately matching fintechs to institutions based on capabilities, needs, and intent.

This AI capability integrates seamlessly within their existing platform, and, following some front end development, will become part of the Production release.

Adding Value with AI

With the help of Fidra Analytics, Finbridge Global have transformed their platform. The AI-powered changes add several new features and impactful value to their users.

Refined results in less time. The framework produces a short summary of each fintech, their key features, and contact information. Users can then chat with them directly from the platform.
Widened search scope. Finbridge Global’s search results now include all fintechs across the web, increasing compatible matches.
Invite to join. Users can invite those unregistered fintechs appearing in the search results to join – thus organically increasing the size and reach of the Finbridge Global platform.
Still stuck? No problem. The AI enabled search understands the context of user requirements, and produces some related questions to help them delve further.

Customer Feedback

“We listened to our customers and Innovation Board and wanted to bring AI into our platform. Fidra Analytics have brought this to life. The opportunity for us and our users is both exciting and hugely valuable.”
Barbara Gottardi, CEO Finbridge Global

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