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WMBT Team Pitch: Sustainability Management Platform
- 1. WMBT S u s t a i n a b i l i t y M a n a g e m e n t P l a t f o r m F10 Hackathon Challenge #4: SME Health Check Zurich, March 2020 WMBT
- 2. WMBT What is an SME Health? Sustainability!
- 3. WMBTWMBT Focused on larger public companies How to assess sustainability? Expensive for small businesses Way to go! ESG Rating Companies Specialized Consultants Data Driven Solutions V
- 4. WMBT Sustainability Management Platform powered by Machine Learning
- 5. WMBTWMBT How does it work? Collect Analyze Suggest Open Banking Invoices, CRS Reports, Tax Returns Manual input Neural Network Current Positioning Potential Improvements
- 6. WMBTWMBT Data Input A user inputs information about her company: • Manually; • Uploading invoices, tax returns or CRS reports; • Connecting to her bank via open banking. The more information we get, the better suggestions we can make. Currently we support 42 metrics and only manual input. Mock-up, not a real website
- 7. WMBTWMBT Data Input A user inputs information about her company: • Manually; • Uploading invoices, tax returns or CRS reports; • Connecting to her bank via open banking. The more information we get, the better suggestions we can make. Currently we support 42 metrics and only manual input. Mock-up, not a real website
- 8. WMBTWMBT ESG Score The user gets information about her company current positioning against the peers… Mock-up, not a real website
- 9. WMBTWMBT ESG Score The user gets information about her company current positioning against the peers and how it could be improved. Mock-up, not a real website
- 10. WMBTWMBT Detailed Analytics The user gets detailed information per each metric… Mock-up, not a real website
- 11. WMBTWMBT Detailed Analytics The user gets detailed information per each metric and how it could be optimized to improve the overall score. The user can set up constraints for the optimization, e.g. that CO2 emissions cannot be reduced; otherwise we imply constraints from the data. Currently we support optimization by 6 metrics. Mock-up, not a real website
- 12. WMBTWMBT Referrals The platform suggests to the client our partners who could help to improve a particular metric. Mock-up, not a real websiteNot real companies
- 13. WMBTWMBT But make it fair! The platform shows the positioning of the peer companies, which are using the suggested partner. Mock-up, not a real website
- 14. WMBTWMBT Completely Free For Users How must does it cost? Monetized via Partnership Program Users can use all the features of the service with no fee. Paid partnership programs for the companies helping our clients to become better, e.g.: • Water management solutions; • Energy saving equipment; • HR consultancy; • And many more.
- 15. WMBTWMBT How does it evolve? Work with Governments Engage with policy makers to guide environmental policy ●direct financial help / subsidies; ●institutionalize new sustainable technology. Cater to the Real Economy Connect users of sustainable technologies to ●sustainability-driven tech sector; ●consultancy sector; ●various contractors. The platform gathers high quality data that could be used to: ●enhance large data agglomerates: Amazon, Google; ●reduce economic friction: adapt investment process. Make Data Work
- 16. WMBTWMBT How did we make the prototype? Data Preprocessing Model Visualization ≈ 400 metrics for > 40,000 companies Public Sources ESG assessments for ≈ 500 companies Collected data via APIs and web scrapping (partially) using a Natural Language Processing. https://wikirate.org
- 17. WMBTWMBT How did we make the prototype? Treated missing data. Identified incorrect data. Adjusted for outliers. Data Preprocessing Model Visualization
- 18. WMBTWMBT How did we make the prototype? Trained a state of the art neural network: a multi layers perceptron Please see Math Supplement for more details. Data Preprocessing Model Visualization
- 19. WMBTWMBT How did we make the prototype? Built visualization for the model output Data Preprocessing Model Visualization
- 20. WMBTWMBT How can we improve? More Clients More Data Better Model
- 21. WMBTWMBT The Team Valentina Lapteva Data Analyst Google Dr. Valery Vishnevskiy Senior Scientific Assistant ETH Zurich Kirill Zimin Senior Business Analyst SIX Victor Kochemirovskiy VP Sales and Trading Morgan Stanley
- 22. WMBTWMBT The Team Valentina Lapteva Data Preprocessing and Visualization, Team Leader Dr. Valery Vishnevskiy Mathematical Modeling and Machine Learning Kirill Zimin Data Scraping and Pitch Preparation, Team Cook Victor Kochemirovskiy Financial Modelling
- 23. WMBT Thank you Please contact us at wmbtteam@gmail.com
- 25. WMBTWMBT Learning ESG score • We aim at predicting the score value from SME feature description , where is the number of features • We can solve it it with a neural network by optimizing for network parameters over the training dataset : 𝑦 𝐱 ∈ ℝ 𝑛 𝑛 𝒱𝜃(𝐱) 𝜃 (𝐱𝑖, 𝑦𝑖) min 𝜃 ∑ 𝑖=1,…,𝑁 ( 𝒱𝜃( 𝐱𝑖) − 𝑦𝑖) 2
- 26. WMBTWMBT Structure of the network • For every company, we can evaluate information bottleneck layer, which is just the vector of activations at the bottleneck layer • Then we can measure company similarities as an Euclidean distance 𝐯 …Inputfeatures𝑛𝐱 Layer1 Bottleneck layer latent representation v Layer 𝑀 Prediction ^𝑦
- 27. WMBTWMBT Prediction and Distribution • We can evaluate prediction for a company • And use latent representation of training data to illustrate the distribution of ESG scores for similar companies 𝑦 Your predicted score Distribution of similar companies
- 28. WMBTWMBT Suggestion for ESG improvement • What would be the minimal effort to improve your ESG score? • Formulated as an optimization problem, wrt fixed neural network max 𝐱 𝒱𝜃(𝐱) − 𝜆 𝐱 − 𝐱0 1 , s . t . 𝑥𝑗 − 𝑥0 𝑗 < 𝜀𝑗 How to change company parameters to maximize ESG With minimal amount of changes to the current company state 𝐱0 Specify feasibility range of changes
- 29. WMBT Mock-ups
- 30. WMBT Sustainability Management Platform Please enter information about your company Or let us do it for you! Connect Your Online Banking Drag & Drop your CRS Report, invoices and tax returns here General⌄ Company Name Financial ⌃ Environmental⌄ Energy (renewable) Energy (non-renewable) Water withdrawals CO2 Emissions Human Resources ⌃ Governance ⌃ kWh per annum kWh per annum m3 per annum metric tons per annum Rainwater used ANALYSE
- 31. WMBT Sustainability Management Platform Please enter information about your company Or let us do it for you! Connect Your Online Banking Drag & Drop your CRS Report, invoices and tax returns here General⌄ Company Name XYZ Company Financial ⌃ Environmental⌄ Energy (renewable) 23,230 Energy (non-renewable) 0 Water withdrawals 852600 CO2 Emissions 580 Human Resources ⌃ Governance ⌃ kWh per annum kWh per annum m3 per annum metric tons per annum Rainwater used ANALYSE
- 32. WMBT Sustainability Management Platform NumebrofCompanies ESG Score 0 25 50 75 100 Your ESG Score is 63 How do you compare to peers: Your Score
- 33. WMBT Sustainability Management Platform NumebrofCompanies ESG Score 0 25 50 75 100 Your ESG Score is 63, could be improved to 78 How do you compare to peers: Your Score Improved Score
- 34. WMBT Sustainability Management Platform Your current metrics: Energy (renewable) Energy (non-renewable) Water withdrawals CO2 Emissions Rainwater used 8345 767340 23540 12345 852600 580 27540 580 TRUE FALSE
- 35. WMBT Sustainability Management Platform Your current metrics and proposed improvements: Energy (renewable) Energy (non-renewable) Water withdrawals CO2 Emissions Rainwater used 8345 767340 23540 12345 852600 580 27540 580 TRUE FALSE
- 36. WMBT Sustainability Management Platform Detailed Information 23540 27540 You might be interested: ABC Water: water recirculation equipment XYZ Wasser: drainage filtering systems
- 37. WMBT Sustainability Management Platform NumebrofCompanies ESG Score 0 25 50 75 100 Companies using Your Score A A A A