Project description
Improved financial security during investments
Economic growth, innovation, and competitiveness are dependent on private investment in companies. But a majority of investment deals end up failing and destroying value. This is in part because proper analysis is not carried out, leading to unsound, non data-driven decisions. The current solution to this problem is manual analysis, which takes a lot of time, money, and is fundamentally unscalable. The EU-funded Plural AI project aims to change this by researching and developing a platform capable of automated financial analysis. This would help ensure better investment decisions, and in turn will help increase capital flowing to companies, by making investment a much more profitable course of action.
Objective
Economic growth and competitiveness are dependent on the investment in companies in order for them to innovate and
advance. But the majority of merger and acquisitions deals end up failing and depleting the value of the companies involved.
This in part because proper analysis and data driven decision are not being made during these deals. The current solution to
this problem is human analysis, which takes a lot of time and effort and is very cost intensive. Using natural language
processing, machine learning, and knowledge graph technology, Plural AI has developed a beta version of a data science
platform for financial analysis capable of generating data driven reports on financial markets and potential acquisition
targets. Plural AI is a gamechanger as it provides answers to complex questions and allows humans to focus on decisionmaking
and strategy. Corporate finance is still behind technologically, meaning that a lot of their financial analysis continues
to be unsophisticated and inaccurate. Plural AI is on the forefront of AI powered financial analysis technology. Plural AI can
help to bring corporate finance to the future, helping companies to make better financial decisions. This will position us to
gain a share within the €5 billion global AI fintech market. To reach our goal of changing the market and reaching a market
share of 5-20% with €89 million revenues by 2024, we plan to follow a SaaS model based on an annual licence fee. Our
customers are investors focused on private companies (private equity / venture capital (PE/VC)), strategic investors (internal
M&A/corporate development arms of large firms), investment banks and other corporate finance advisors/consultancies.
Plural AI’s technology has the potential to reduce instances of fraud in the investment process. It can also help to maximize
Europe’s investments and build strong long-lasting relationships between companies.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- social sciencessociologygovernance
- natural sciencescomputer and information sciencesdata sciencenatural language processing
- natural sciencescomputer and information sciencesknowledge engineering
- social scienceseconomics and businesseconomicsproduction economicsproductivity
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
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Programme(s)
Funding Scheme
SME-1 - SME instrument phase 1Coordinator
NR6 6BB NORFOLK
United Kingdom
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.