Projects / AI Innovation Challenge

Building Climate and Credit Risk Scoring for African SMEs With AI

Application Deadline: March 7


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Developing an AI-driven solution to integrate climate and credit risk scoring for African SMEs, enhancing financial decision-making, and supporting green transitions by combining environmental impact assessments with financial stability evaluations. In this 8-week challenge, you will join a collaborative team of 50 AI engineers from all around the world.

The problem

In Africa, SMEs often face significant hurdles in securing financing, especially when seeking to transition towards greener operations or reduce their carbon footprint. Traditional credit scoring mechanisms employed by financial institutions do not account for the climate risks or the environmental impact of these enterprises. This oversight not only hampers the ability of SMEs to contribute to the fight against climate change but also exposes lenders to potential climate-related financial risks. As the continent grapples with the adverse effects of climate change, including extreme weather events and resource scarcity, the need for a comprehensive understanding of both climate and credit risks has never been more critical.

Impact of the Problem

On Financial Institutions:

  • Limited Risk Assessment Tools: The absence of integrated climate and credit risk assessments can lead to inadequate evaluation of loan applications, potentially resulting in financial losses.
  • Missed Opportunities: Financial institutions miss out on fostering green investments and supporting SMEs in their transition to sustainable practices, a growing market with significant potential.

On SMEs:

  • Access to Finance: SMEs looking to invest in green technologies or practices often struggle to secure financing due to the lack of tailored financial products that recognize their unique challenges and contributions to sustainability.
  • Operational Risks: Without a clear understanding of their climate impact, SMEs may face operational and reputational risks, hindering their growth and sustainability efforts.

On the Environment:

  • Increased Carbon Footprint: The failure to integrate climate considerations into financial decision-making processes contributes to the continued support of high-carbon projects, exacerbating environmental degradation.
  • Slow Progress Towards Sustainability Goals: The lack of financial incentives and support for green transitions among SMEs slows down the overall progress towards national and global sustainability targets.

This project aims to develop an AI-driven solution that accurately measures the climate risks and carbon footprint of SMEs, beginning with supporting transition projects in Renewable Energies (RE) and Energy Efficiency (EE) in East Africa. It integrates these evaluations with credit reports, enhancing the green loan application process. By collecting real-time data on extreme weather events, financial and operational details from the SMEs, the project provides lenders with a comprehensive tool evaluating the green loan applications, incorporating climate risk appraisal reports. This initiative not only aids financial institutions in making informed lending decisions but also supports SMEs in managing their climate impact, aligning financial growth with sustainable development trajectories.

Thus, this project addresses the urgent need for innovative tools that recognize and mitigate climate risks while supporting sustainable business practices among African SME’s. By doing so, it contributes to a more resilient and environmentally conscious economic landscape in Africa.

The goals

The ultimate objective of creating an AI-driven solution to integrate climate and credit risk scoring for African SMEs is to enhance the decision-making processes of financial institutions, enabling them to provide green loans to SMEs committed to reducing their carbon footprint and transitioning towards sustainable practices. This tool aims to support Africa’s emerging voluntary carbon credit market by offering a comprehensive assessment tool that combines climate impact evaluations with financial stability assessments for SMEs, facilitating sustainable business growth and environmental stewardship.

The main goals of this challenge are:

  • Comprehensive Data Collection Framework Development: Establish a robust framework using IoT devices and APIs to collect real-time operational and environmental data from schools and other SMEs, ensuring data privacy through anonymization techniques.
  • AI Model Development for Climate Risk Scoring: Utilize advanced machine learning algorithms and natural language processing (NLP) to analyze collected data, focusing on developing a model that accurately assesses climate risks and carbon footprints. This involves leveraging Python and libraries like TensorFlow and PyTorch for deep learning model development.
  • Integration of Climate Risk Scores with Credit Reports: Seamlessly integrate the developed climate risk scoring system with credit reports to provide financial institutions with a holistic view of an SME’s creditworthiness and environmental impact, facilitating informed decision-making for green loan applications.
  • Deployment of the Solution as an API Endpoint: Develop APIs for easy integration of the AI model with financial institutions’ systems, ensuring the solution’s accessibility and usability.
  • User Interface Development: Create a basic yet intuitive user interface, possibly using tools like Streamlit, to demo the solution’s capabilities in displaying climate risk scores and carbon footprint analyses for SMEs.
  • Documentation and Reporting: Produce comprehensive documentation that details the development process, methodologies, and results, providing a transparent account of the project’s outcomes.

Why join? The uniqueness of Omdena AI Innovation Challenges

A collaborative experience you never had in your working life! For the next eight weeks, you will build AI solutions to make a real-world impact and go through an entire data science project lifecycle. This covers problem scoping, data collection, and preparation, as well as modeling for deployment.

And the best part is that you will join a global and collaborative team of changemakers. Omdena AI Challenges are not a competition or hackathon but a real-world project that will take your experience of what is possible through collaboration to a new level.

 Find more information on how an Omdena project works

First Omdena Project?

Join the Omdena community to make a real-world impact and develop your career

Build a global network and get mentoring support

Earn money through paid gigs and access many more opportunities



Your Benefits

Address a significant real-world problem with your skills

Get hired at top companies by building your Omdena project portfolio (via certificates, references, etc.)

Access paid projects, speaking gigs, and writing opportunities



Requirements

Good English

A very good grasp in computer science and/or mathematics

(Senior) ML engineer, data engineer, or domain expert (no need for AI expertise)

Programming experience with Python

Understanding of Machine Learning and/or NLP



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Application Form
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