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The Responsible Investors

Alygne and Finastra

Scoring Finastra ESG Funds (Environmental Social Governance criteria) using Fintech AI and Natural Language Processing.
Scoring Finastra ESG Funds (Environmental Social Governance criteria) using Fintech AI and Natural Language Processing.


>> watch the video (3 min) <<

The investors mindset is changing, they request the need to integrate social criteria in their investments.
Financial investment funds aligned with ESG (Environmental Social Governance) criteria have a direct and positive impact on the society and the environment.

But retail and institutional investors are hindered by the lack of transparent, easy-to-access, easy-to-understand and comprehensive information. And the data should be available for all companies, not just the largest public corporations.


#How does the Responsible Investors app work?
1. The Fintech (Alygne) consumes an OpenAPI (GA) on FusionFabric.cloud to load the issuers (companies, assets) of a fund from Finatra product’s Fusion Invest.
2. The Fintech AI is able to collect data from the www, related to ESG-criteria of a given issuer/company. Using Natural Language Processing, the AI gathers relevant press releases, social networks, tweets, and corporate announcements of the Internet. Note: the Fintech is able to split the company's self-assessments (their own communication) vs the market's perception (press, social networks).
The Fintech algorithm computes quantitative ESG scores, for each issuer and for several dimensions.
3. The Finastra user retrieves the ESG score of his issuers and aggregates them at the fund level.
4. This is fully integrated in the core product (Fusion Invest), where the asset manager can use all existing functionalities: for example, increase the allocation of good companies (regards to ESG-criteria and scoring), and reduce the exposure to those that underperform. He can also share this transparency towards his own customers.


#How we built it?
- We first drafted a Use Case based on persona who have an interest in ESG: a retail investor, an asset manager and an AI. Step by step, the user stories became a real scenario.

- For a very fast reactivity, we created micro-teams working on the different functionalities described in the workflow, and across different time zones (San Francisco, Paris, London, Singapore).


#What did we learn?
- How to build integrated functionalities on top of innovation.

- ESG awareness, especially social criteria applied to retail and institutional investors.

- "Natural Language Processing" capabilities.

 - How easy it is to co-innovate between Finastra and a fintech through FFDC.

>> For more info, visit our devpost <<


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