In recent years, financial and insurance organization are producing large volumes of digital data from a variety of sources including traditional enterprise systems, e-banking and mobile-banking transaction processing systems, social media platforms, as well as emerging blockchain systems based on distributed ledger technologies. The availability of these data has given rise to the development and deployment of a host of novel banking, finance and insurance applications in areas such as credit scoring, customer risk assessment, personal finance management, asset management, roboadvisors, fraud detection, customer centric analytics, intelligent customer service and regulatory reporting. Most of these applications rely on big data and Artificial Intelligence (AI) technologies, which enable the persistence, the management and the intelligent analysis of these datasets.
AI applications in financial and insurance are already delivering a positive Return on Investment (ROI) for financial organizations.
This ROI stems from:
- Tagible improvements in the efficiency of existing digital finance business processes (e.g., risk assessment, regulatory reporting), which enhance productivity and drives reductions in operational costs. Therefore, these improvements increase the profitability of finance and insurance organizations.
- The development of novel personalized customer-centric products that increase the customers’ engagement with the organization and their overall lifetime value for the financial or insurance company.
This is the reason why there is a surge of market interest on AI applications in digital finance and insurance. According to Grandview research, the goal AI in Fintech (Financial Technology) market was valued at USD 9.45 billion in 2021 and is expected to grow at a Compound Annual Growth Rate (CAGR) of 16.5% in the period from 2022 to 2030. This growing market value will be produced in the scope of growing ecosystem that comprises multiple stakeholders, including traditional banks and insurance firms, emerging Fintech and Insurtech companies, digital finance/insurance vendors and integrators, as well as consultants and regulators.
To accelerate the adoption and deployment of Big Data and AI solutions for digital finance, all stakeholders need easy access to a variety of technical and technological resources. The latter range from data infrastructure components and Machine Learning (ML) algorithms to training and learning resources. Along with access to these resources, most stakeholders need also support in development, deployment and innovation management processes, notably support that will help them learn, gain experience and gradual overcome development and deployment barriers. Nevertheless, most of the resources that are nowadays available to financial organizations, insurance companies and other relevant stakeholders tend to be fragmented and propriety rather than structured, integrated, and openly accessible from a single-entry point. This can become a serious setback to testing AI solutions and deploying relevant AI-based innovations.
State of the Art Catalogues and Repositories of AI and BigData Resources
To address the need for accessing Artificial Intelligence and Digital Finance related resources from a single-entry point, several European Research and Innovation (R&I) projects have developed on-line catalogues and repositories of such resources.
Some of the most prominent examples of catalogues and repositories with relevance to the digital finance sector include:
- The AI4EU Catalogue of AI resources. AI4EU is the first European Artificial Intelligence On-Demand Platform and Ecosystem, which has been recently built with the support of the European Commission under the H2020 R&I program. AI4EU has developed a searchable catalogue of AI assets, which includes already 100s of AI resources. These resources are classified based on different criteria, including the business domain they address. Nevertheless, the catalogue does not include any resources in the digital finance and insurance category. Moreover, even though some of the AI resources of the catalogue have been used in finance use cases, the catalogue is far from providing a critical mass of digital finance resources that could be useful for the BigData and AI in finance and insurance communities.
- The Internet of Things (IoT) Catalogue is a one-stop-source for IoT knowledge, innovations and technologies. It aims at helping IoT stakeholders (e.g., developers, integrators, advisors, end-users, etc.) to access IoT resources and use them to improve the competitiveness and business results of their organizations. The catalogue comprises use cases, technologies, components and other IoT-related resources, which in several cases include analytics, ML and AI algorithms. Several EU projects have leveraged the IoT catalogue infrastructure in order to provide repositories of components in the form of new segments of the catalogue. However, the catalogue is not primarily focused on AI and does not include digital finance resources.
- The Finsecurity portal is an on-line catalogue and community of security experts and stakeholders of the finance sector, which was created by the H2020 FINSEC project. It presents, promotes and offers solutions and services for the security of the critical infrastructures of the Finance Sector. Hence, while being focused on the digital finance sector, its scope is quite limited to security and critical infrastructure protection and does not cover the broader scope of AI-based Fintech and Insurtech applications.
Beyond these EU projects initiatives, there are also commercial initiatives and open source ecosystems that provide single-entry point access to AI resources. Two of the most prominent examples include:
- The KNIME Hub offers public and private spaces for organizing and sharing AI/ML resources developed in the scope of the ecosystems of the KNIME platform for data science. It includes many solutions, yet very few of them are directly related to finance sector use cases.
- The Acumos AI platform which is an open source framework that eases the development, and sharing of AI applications. Acumos had started a marketplace of standardized AI solutions, which did not however created a lot of traction around the platform.
There are many other initiatives that have developed similar repositories of solutions, while a lot of code for software solutions can be found in lower level repositories such as gtihub. However, there is generally a lack of single access points to a critical mass of AI/ML based solutions for digital finance and insurance. Motivated by this gap, the H2020 INFINITECH project has developed and established the INFINITECH marketplace, an on-line repository of AI-based solutions for digital finance.
Introducing the INFINITECH Marketplace
The INFINITECH marketplace is a repository and a catalogue of on-line resources about Big Data and AI solutions in digital finance and insurance, which has been established by the H2020 INFINITECH project. It supports the innovation efforts of the INFINITECH community and of other EU projects, including the efforts of banks, insurance companies, Fintechs, Insurtechs, AI/BigData vendors, as well as of universities and research organizations. The marketplace is already used by the INFINITECH partners and other related organizations from their business networks, including other EU projects (e.g., H2020 Triple-A), researchers, banks and digital finance innovation associations.
- 40 technical assets for AI and Big Data in digital finance that were developed by the INFINITECH project.
- 73 third party technical assets and tools for AI and Big Data in digital finance, including solutions developed by the INFINITECH business partners and other third party organizations.
- 212 courses and 77 innovation services (including resources developed in INFINITECH), structured and organized in searchable catalogues.
- Over 10 workshops and thematic Webinars addressing many different technical and technological areas of AI/BigData solutions for digital finance and insurance.
The contents of the marketplace form already a critical mass of technical, training and innovation support resources, which can be of interest to various stakeholders. Furthermore, the number of resources that are integrated in the INFINITECH marketplace is constantly growing in an attempt to keep up with the evolution of the state of the art and to continually provide value to the community.
INFINITECH Marketplace Assets and Tools
The technological assets and tools of the marketplace are of different types and are offered based on different formats. They include:
- Datasets for data science testing and experimentation.
- Software components in terms of docker images for easy packaging and distribution.
- Source software libraries and applications available in Github.
- Data science components (including machine learning code) in the form of data science notebooks (e.g., Jupyter Notebooks).
- Open-source components with links to software repositories.
- Textual and multimedia documentation of software components and solutions, including PDF documents and Youtube videos.
From a business perspective the various assets and tools cover many data intensive digital finance use cases, including risk assessments of investment portfolios, customer profiling solutions, Know Your Customer (KYC) solutions, financial recommendation solutions, usage-based insurance solutions, energy efficient and ESG investments, regulatory compliance and data protection solutions, as well as a variety of blockchain solutions. INFINITECH’s ambition is to populate the marketplace with Big Data & AI assets and resources spanning the entire digital finance sector.
INFINITECH Marketplace Resources and Services
The marketplace integrates a rich set of training and innovation management resources and services, including:
- A searchable catalogue of training resources for AI and Big Data in Digital Finance. including courses in major training platforms like Udemy and Coursera, course and trainings developed by INFINITECH, as well as a rich set of relevant webinars that were organized by INFINITECH project and organizations of the INFINITECH partners’ business network. Moreover, the catalogue includes training resources in the form of how-to videos, which drive their viewers to complete a concrete programming or data science task.
- A searchable catalogue of accelerator programs for AI/BigData and financial technology in Europe. The catalogue provides comprehensive information about each program, including its technology or business focus, as well as the location where the acceleration services are provided.
These resources complement the assets and tools of the marketplace. They are destined to help potential users of the marketplace’s assets and tools to develop the skills and obtain the innovation support needed to use and fully leverage the available technical and technological resources of the repository.
How to Get Started with the INFINITECH Marketplace
- Register to the marketplace at: https://marketplace.infinitech-h2020.eu/login
- Browse through assets at: https://marketplace.infinitech-h2020.eu/assets and download the asset of your interest.
- Access INFINITECH trainings, how-to-videos and other training resources through the training catalogue at: https://marketplace.infinitech-h2020.eu/vdih/training/courses
- Add a new asset after viewing a short tutorial on how to add your own resource to the marketplace at: https://marketplace.infinitech-h2020.eu/new-information/new-asset
INNOV-ACTS is proud to have contributed to the design of the marketplace and to the production of several of its contents. INNOV-ACTS has contributed training resources (courses, how-to videos), assets and tools (e.g., risk assessment tools), as well as ML algorithms and blockchain solutions. We are committed to continuing the INFINITECH project journey towards empowering the Digital Finance Community through a unique Repository of Big Data and AI Resources.