SAS Hackathon winners decode real-world dilemmas with data

International teams awarded for innovative AI and analytics solutions to humanitarian and business challenges

SAS, the leader in analytics, today announced the winners of its 2022 SAS Hackathon. From 70 qualifying teams from around the world and 50 business case submissions, SAS recognized 13 teams for innovation using cloud-native SAS^® Viya^® artificial intelligence, Microsoft Azure and other technology. Tasked with tackling a real-world business or humanitarian problem, the winning teams’ projects ranged from optimizing disaster response to reducing food waste.

More than 100 judges from diverse backgrounds recognized international winners across eight industries, six technologies and three regions. The awards ceremony was broadcast live on LinkedIn and YouTube.

Unique SAS Hackathon format boosts innovation

Rather than a traditional in-person hackathon that gathers coders for a few days, SAS Hackathon participants collaborated online for a month, enhancing their data science skills under the guidance of a SAS mentor through a variety of industry tracks. Each team had access to a learning portal and the ability to try SAS techniques such as machine learning, natural language processing, computer vision, data visualization and IoT on SAS Viya, powered by Microsoft Azure. Participants were encouraged to network while solving real-world issues that affected their communities.

“There’s a stereotype that hackathons are just a bunch of coders hunched over computers tackling fluff challenges for the sake of it — and it isn’t true,” said Einar Halvorsen, Global Hackathon Lead at SAS. 

“The end goal of the SAS Hackathon is to bring together sharp minds from many backgrounds to create a commercially viable solution for real-world problems. It’s a learning experience, an incubator and a trial for taking world-changing ideas to market.”

2022 SAS Hackathon Winners by category

Global Industries

·       Banking: Green Swedbank (Sweden): Record-breaking rain and flooding spurred by climate change battered Sweden last year. Team members from Swedbank and KPMG created a dashboard in SAS Visual Analytics to assess flood risk to properties — and price potential losses — for 100-, 200- and 1,000- year flooding scenarios.

·       Energy: Innova Data Hub (Spain): As the European city with the most deaths linked to traffic emissions, Madrid wants to prioritize green transportation. To improve BiciMAD, Madrid’s bike service, Innova Data Hub from Innova-tsn compiled datasets on bike usage, then used predictive modeling to design an optimization solution that can be implemented in less than six minutes and reduce impossibilities by more than 90 percent.

·       Health and Life Science: The Chart Chasers! (U.S.): While value-based care ties doctors’ paychecks to the efficiency of their care, doctors can be underpaid when mistakes are made in the medical coding process. Team members from InformedHC and Pinnacle Solutions built an automated system to uncover lost revenue for medical providers due to mistakes in the use of the International Classification of Diseases codes.

·       Insurance: LiveEO #2 (Germany/Mixed): Dennis Schmargon, head of business development at LiveEO, used SAS analytics, LiveEO and open-source public and commercial satellite data to create a model that monitors and predicts flooding events, empowering insurers to make informed decisions about risk potential.

·       Public Sector: Jakstat (Indonesia): Team Jakstat from StarCore applied SAS and Python to map and optimize the disbursement of COVID financial aid for the micro-, small and medium-sized businesses that make up 97 percent of Jakarta’s economy.

·       Telecom & Media: Funka (Sweden) To improve the accessibility of web forms for people with and without disabilities, team members from company Funka Nu AB used computer vision, optical character recognition, machine learning, and test automation to create a solution for website owners to evaluate the accessibility of their forms — and apply solutions to any indicated problems — by inputting their site’s URL.

·       Retail: TrendsPro (U.S.): Team TrendsPro from Maypro Group LLC used search engine trend analysis to forecast consumer demand for products to optimize ad campaigns. Their solution allows business owners to allocate inventory, discover the most appropriate advertising channels, and decide how many and what kind of ads to deploy.

·       Mixed/Manufacturing: Notilyze (Netherlands): Notilyze created an insight tool for a food manufacturer that monitors processing and quality control. This allows the food manufacturer to optimize the manufacturing process for maximum profit while reducing energy consumption and food waste.

Technologies

·       IoT: Oges (Singapore/India): Accurate reservoir modeling is crucial for oil and gas companies to drill effectively, protect personnel and prevent oil spills. Team members from Oges Solutions incorporated SAS Visual Data Mining and Machine Learning and Python Libraries to create a hyper-accurate AI-based oil reservoir model, ready to be incorporated by any oil and gas company.

·       Machine Learning: The Positive Thinking Company (Germany/Belgium): As climate change intensifies, farmers most vulnerable to its impacts can benefit from protective, inexpensive microinsurance. Using SAS Viya and machine learning technology, The Positive Thinking Company analyzed climate risk in various states in India, then built a tool for at-risk farmers to explore how climate change can affect their livelihoods — and how microinsurance can help. 

·       Computer Vision: Funka [See above.]

·       Decisioning: Linktera4Insurance (Türkiye): Digitalizing the customer journey in insurance would reduce paper usage and automate workflow and decision making for faster and easier underwriting and claims management. Linktera4Insurance from Link Tera Bilgi Teknolojileri employed SAS Viya on Azure to render complex insurance data into easily navigable dashboards and graphs, and used Neula Low Code Platform to automate workflow.

·       Visual Analytics: Disaster Response AI (Canada): Globally, natural disasters cause more than 15,000 deaths and cost $173 billion per year. On SAS Viya, Team Disaster Response AI from Deloitte built an interactive map visualization rich with disaster insights and predictions to advise the Canadian government on how best to allocate relief funds.

·       Forecasting: Team 4-kasting (Norway): To keep its ranking as the fastest mobile network in the world, Telenor Norway requires enough network capacity to stay speedy without tipping into expensive and unsustainable overcapacity. Team 4-kasting deployed machine learning/visual forecasting to create a system that forecasts expected usage at any given site, potentially saving the telecommunications company millions.

·       Natural Language Processing: The Chart Chasers! [See above.]

Regions

·       Asia: Jakstat

·       EMEA: Funka

·       Americas: The Chart Chasers!

SAS Viya on Microsoft Azure key to scalability around the globe

Microsoft — the hackathon’s sponsor — and SAS offer integrated technology that fueled innovation among the international cohort at SAS Hackathon. SAS Hackathon participants implemented SAS Viya on Microsoft Azure’s cloud-native, integrated technology to build insight tools, automated systems and models and more.

Analytics and AI answer real-world problems at SAS Hackathon 

“Whether it’s ensuring doctors are paid for the quality of their care, optimizing sustainable transportation, or rendering hyper-accurate AI models for the world’s largest companies, our 2022 Hackathon winners applied SAS, Microsoft and open-source technologies in ways that inspired our judges,” said Peter Lundqvist, Global Hackathon Program Manager.

“Competition is fun, but collaboration and curiosity are what truly power the SAS Hackathon.”

For more information on the winners and what sets the SAS Hackathon apart, please visit sas.com/sas/events/hackathon.html and follow #SAShackathon on LinkedIn, Twitter and Instagram.