Security tools for AI Investments platform

Coordinated by

Secured AI Investments platform using the outcome of the BIECO project.


Describe the innovation content of the result:
The key innovation products will be:
Security tools for AI Investments platform using the outcome of the BIECO project.
Who will be the customer?
The customers are hedge funds, proprietary trading companies, mutual funds.
What benefit will it bring to the customers?
The AI Investments platform will be secured using the outcome of the BIECO project.
When is the expected date of achievement in the project (Mth/yr)?
At the end of the project.
When is the time to market (Mth/yr)?
At the end of the project.
What are the costs to be incurred after the project and before exploitation?
It is estimated at 10 – 20 kEUR.
What is the approximate price range of this result/price of licences?
AI Investments it depends on AuM of the investments fund, it is 1% of management fee of AuM and 10% of success fee.
What are the market size in Millions € for this result and relevant trend?
It is assumed that in the 1st year of implementation the value of funds will amount to EUR 20M and within 5 years – EUR 100M.
How will this result rank against competing products in terms of price/performance?
To our knowledge, there is no similar platform on the European market. Almost all of the successful quant funds are based outside of Europe, so our solution will be very innovative in Europe.
Who are the competitors for this result?
Advanced quant funds that use complex investing methods.
How fast and in what ways will the competition respond to this result?
Unknown at the moment
Who are the partners involved in the result?

AI Investments platform – partnership with AI Investments company.

Who are the industrial partners interested in the result (partners, sponsors, etc.)?
Hedge funds, investments funds, mutual funds, proprietary trading companies.
Have you protected or will you protect this result? How? When?
IP rights for source code are reserved. The AI Investments source code will not be available publically.

Other results

Data Collection Tool

Data Collection Tool (DCT) stores information from relevant vulnerability related datasets, providing a single access point to information required by the vulnerability detection and forecasting tools developed in T3.3, as well as for the failure prediction tools developed in T4.2.

Vulnerability Detection Tool

Vulnerability Detection Tool will detect existing vulnerabilities within the source code which may lead to the successful execution of an attack.

Fuzzing Tool

Fuzzing Tool will test System Under Test (SUT) security vulnerabilities or inputs not contemplated that could compromise the system; as a black-box process, by using unintended or incorrect inputs and monitoring their corresponding outputs.

BIECO Project

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