Pandemic Impact Evaluator by Oxyml

Despite a plethora of evidence, many countries and communities ignored scientific advice in responding to the COVID-19 pandemic because of concerns about the economy. These concerns were often well warranted, as hundreds of millions of people across the globe found themselves facing arduous economic hardships.

Oxyml's proposed solutions are designed to provide clarity and insight regarding the true financial and economic costs of pandemics, letting policymakers adjust governmental policies to reflect the true price of pandemic risks and exposures.

Policy-making for uncertain events is a difficult, challenging process that impacts almost every major country across the globe. Our technology has the potential to improve the lives of billions of people struggling with the economic impacts of pandemics through better government policy, more insights into investments, and guidance on best practices for a robust and sustainable economic recovery.

Prevent the spread of misinformation and inspire people to protect themselves and their communities, including through information campaigns and behavioral nudges.

Without adoption and support the best scientific research and opportunities to combat a pandemic can be squandered. Our solution aims to provide an online software-as-a-service platform for government agencies and individuals to assess the economic risk of a pandemic across economic sectors using Oxyml’s database of over 80,000 companies and thousands of economic indicators over time. Using this data, we can provide policymakers with guidance on advice regarding reopening economies and enhancing compliance with pandemic response best practices, serving the goal of creating nudges designed to better protect communities.

This problem impacts people across the globe, as both developed and developing countries have made serious errors in their pandemic response ranging from holding campaign rallies to reopening parts of the economy too early. Our solution aligns with MIT Solve’s goal of promoting best practice responses in communities to the pandemic. This problem impacts billions of people across the globe as every country’s leadership struggles with balancing the financial and health impacts of a pandemic and is especially pronounced in developing economies with less fiscal slack.

Our solution is a software-as-a-service platform for government agencies and individuals that allows them to forecast and understand the economic and financial impact of a pandemic. Users are able to understand potential financial hardships that may occur and the financial impact on individual publicly traded companies, sectors of the economy, and economic regions. Users can also see how different pandemic responses would impact financial recovery. For example, one could see how many companies in the travel and leisure industry would become insolvent in a 3-month lockdown versus a 6-month lockdown, and see which regions would be most impacted. Users can vary criteria such as lockdown periods, virus severity, spread rates, and economic factors to understand granular impact analysis.

Our program is built on a database of over 80,000 companies across the globe and incorporates up to hundreds of thousands of data points on each company. Our system is built using proprietary artificial intelligence technology developed in collaboration with the London Stock Exchange Group and is part of our mission of deploying artificial intelligence solutions to the most at-risk communities across the globe.

Our proposed solution is targeted at government agencies, think tanks, and individuals that are at the highest risk of financial hardship from pandemics. The primary government agencies targeted are disease preparedness groups, economic development councils, and budgetary agencies. In the United States, this would include groups like the Congressional Budget Office, the Centers for Disease Control, and various regional economic development groups. Similar agencies exist in most countries. While the United States has funds to fully staff these agencies, many governments from developing countries face many hardships including inconsistent and or limited funding, a shortage of talent, and fierce competition from corporations for experts in analytics and artificial intelligence. Because of this, when a pandemic occurs many agencies are left without a proper understanding of the full economic impacts of a pandemic.

This lack of analytics and concrete research on financial impacts leads to conflicting reports and disagreements regarding best practices to pandemic responses. This can lead to infighting and resistance to implementing pandemic response plans. A well-thought-out pandemic research plan with a coherent analysis of the financial impact on economic sectors can improve both the economic and health-based response to a pandemic, which makes the issues resulting from the global COVID-19 response all the more tragic.

These tools will also be available to individuals and think tanks as part of our commitment to transparency. This will allow individuals in certain sectors such as hospitality to understand the potential impact of a pandemic. This can have real-world implications that change the everyday lives of stakeholders making difficult decisions every day about pandemic responses. For example, many restaurants are small local businesses that struggled with determining whether or not to order inventory and engage in layoffs during the COVID-19 pandemic. This is also true for larger companies such as cruise lines and airlines which struggled to balance public good with a need to sustain ongoing operations.

The solution will be housed under Oxyml’s Voltsail (™) product line and will be part of our Voltsail charitable initiatives, making the vast majority of our product’s features free of charge to those in the direst need. 

As part of our Voltsail charitable initiative, we are constantly in contact with think tanks, researchers, and major conglomerates that share our values and are dedicated to expanding access to artificial intelligence tools to communities most in need. Our engagement takes many forms ranging from public-private partnerships to research consortiums and collaborations based on our commitment to deploying our technology in the most efficient and scalable manner to create long-lasting impacts.

Our solution is designed to ensure that scientific research aimed at combating pandemics is funneled into solutions that are practical and have a broad support by limiting the financial and economic damage from policy implementations. This will create the correct nudges and incentives to allow for support not only from scientific agencies but also from local communities, business leaders, and industry groups. The result is that the divide between local businesses, governments, and scientists will become narrower and as a result community stakeholders will work together on solutions with broad support.

We are currently testing parts of our solution internally and with select partner firms and collaborators. Our management team anticipates rolling out our technology to a larger group of select beta testers within the next several months and hopes for a commercial roll-out of select parts of our platform to a wider commercial audience by the end of Q3 20201.

Our technology will be released in various stages to different groups, agencies, and global regions over time based on regulatory requirements, feedback from stakeholders, and results from our internal tests and proprietary analytics.

Oxyml is dedicated to tackling some of the world’s most challenging quantitative problems, with a specialty in research and development into previously unsolved problems related to artificial intelligence and data analytics. Our approach is based on patented technology that creates artificial intelligence solutions using a mix of machine learning, decision theory, optimization theory, quantitative finance, econometrics, and other diverse quantitative fields.

Each of these fields is nuanced, complex, and takes many years to truly master. Combining them together in unified frameworks that are both theoretically sound and commercially deployable at scale is an arduous task. Our proposed solution is only now viable due to advances in cloud computing, hardware advancements, and theoretical advancements across multiple disciplines and represents our dedication to pursuing innovation by pushing the limits of what is theoretically possible.

Our technology aims to serve as a catalyst for global change by democratizing artificial intelligence tooling and making it available to those who have been left out by the technological revolution. By sharing our insights with universities, think tanks, and other firms we hope to lay the groundwork for others to follow in our footsteps and use both our platform and our expertise for advancing our mission of promoting AI accessibility. 

Our solution is currently in the pilot stage and is being used internally and with a select number of partners. As such, our deployment is currently only serving around a dozen organizations. In the next year, we are engaging in a planned roll-out with our partners at LSEG and anticipate launching to around 100 organizations and agencies on a gradual basis.

Over the next five years, we anticipate pursuing an aggressive international expansion via a network of collaborators and partner firms across the globe, reaching tens of thousands of agencies and millions of individuals directly, and many more through the indirect benefits gained from better government policies and community buy-in. We anticipate well-planned policies and data-driven decisions to make an impact on the lives of billions of people across the globe over the next five years.

There are four primary indicators we will be using to track our progress towards our impact goals: adoption by government agencies, integration into government plans, qualitative feedback from our partners, and results from focus groups.

Our adoption rate metric will analyze how our platform is used and by government agencies and groups. This will track usage metrics such as login activity, session times, new account creation rates at agencies, and individual tool adoption as well as second-order metrics such as the change in these metrics over time. This will allow us to see if our toolkit matches the needs of specific agencies.

While usage is important, implementation is critical. This metric will track agency reports to see if our tools have been used in pandemic preparedness plans at different agencies. Analyzing linkages between usage and implementation is a critical component of maximizing impact.

Our final two metrics are qualitative in nature. This includes feedback from our partner firms and data from focus groups. This set of feedback will be used to see how users interact with our platform and services and can provide added context to the quantitative data generated by our first two impact metrics. For example, focus groups can provide insight into why tool usage may not be translating into implementation.

By using these primary impact metrics as well as additional data we collect as we expand we plan to tailor our offering to maximize impact and deliver sustainable progress on our UN initiative goals.

Full-Time: 2

Part-Time: 1

Contractual basis: 6

Dr. Tracy has previous experience working with Los Alamos National Lab on government projects for the department of energy. He has a proven track record of incorporating advanced scientific computing and hardware optimization techniques into complex systems.

Mr. D’Souza has experience from his time at Alphabet in every phase of a product’s life cycle development through his expertise and leadership as part of the Android team.

Dr. Kotarinos is an expert in the intersection of quantitative finance, statistics, and compliance. He is the author of numerous publications and patents and coordinates intellectual property development with research institutes across the globe.

Oxyml also has eight utility patent disclosures that will support approximately 75 to 80 patent allowances in addition to five trademark filings and anticipates filing additional patents later this year.

We believe that our team’s experience, expertise, and research-driven approach allow us to implement, de-risk, and deploy world-class tools that assess the true cost of pandemics. Our team is diverse and comes from different backgrounds, countries, and walks of life.

At Oxyml, our company’s culture and diversity are key to our continued success as a leader in artificial intelligence innovation. We believe a company’s culture is best represented by who a company’s management chooses to hire and who it chooses to promote. We are committed to hiring and promoting people from diverse backgrounds and have as our partners, collaborators, and employees people from all walks of life.

Oxyml LLC is a diverse company and an equal opportunity employer. Each applicant to Oxyml is given consideration for employment and is not discriminated against on the basis of race, color, marital status, socio-economic level, sex, sexual orientation, gender identity, religion, religious beliefs, age, political ideology, disability, genetic information, veteran status, ancestry, or national or ethnic origin.

Our team has three primary objectives in becoming a Solver: pursuing partnerships with MIT and its research affiliates, establishing a groundwork for recruitment at Oxyml, and collaborating with MIT’s global network of partners and institutions.

MIT’s vast network of scientists, researchers, and professionals across the globe will help us deploy our technology and solutions across diverse and highly regional economies and systems, helping us address the issues in scaling our technological solutions and systems.

This can further be augmented by access to MIT’s highly talented pool of students and alumni. MIT’s training and preparation is an excellent foundation for future leadership and talent across Oxyml’s many product lines, and in particular in our Solver solution. Finally, as a research and development firm, we wish to pursue public-private partnerships with research institutes and groups across MIT’s campus to allow for mutually beneficial collaborations between Oxyml’s management team and MIT’s research faculty and staff.

There is a dire shortage of talented researchers with experience in developing new and innovative artificial intelligence technologies. Companies are in constant recruiting battles for talent and at Oxyml we strive to hire, train, and develop the best AI researchers in the world. Access to MIT’s pipeline of the world’s best and brightest researchers will help us grow and expand both in our proposed solution line and across Oxyml’s family of products. We seek to recruit MIT graduates and students for internships, externships, and full-time positions.

MIT’s pipeline of researchers is also enhanced by their global and diverse pool of talent with connections and knowledge of different countries, customs, and systems. This globally diverse pool of talent will help us better serve our communities by building a diverse workforce that reflects the communities we service by recruiting from an academic institution that shares our values.

Finally, we hope to establish public-private partnerships with research institutions and faculty groups at MIT. We hope to share our unique insights into AI with MIT faculty and researchers, and in turn, pursue collaborations with researchers across the university. This serves Oxyml’s initiative to pursue public-private partnerships with research institutes that share our same goals and objectives of solving the world’s most challenging problems.

We are already partnered with Microsoft, one of MIT’s solver members.

MIT Laboratory for Financial Engineering-The MIT Laboratory for Financial Engineering shares many similar research interests with our research teams. We hope to partner with the lab on public-private research partnerships to promote the lab’s goal of promoting research partnerships between academia and industry in computational finance.

Martin Trust Center for MIT Entrepreneurship-We aim to share our insights into the commercialization of artificial intelligence solutions with the Martin Trust Center. By doing so, we hope to empower the next generation of entrepreneurs to use AI in responsible and sustainable frameworks.

MIT Computer Science & Artificial Intelligence Lab-At Oxyml, every day we work on solving some of the world’s toughest problems using our own proprietary algorithms. We believe that CSAIL would be an ideal academic partner for future collaborations on developing new innovations in AI algorithms and architecture.

MIT Quest for Intelligence-The MIT quest for intelligence aims to solve big and fundamental questions about the implications of automated decision-making. We at Oxyml want to be part of the conversation about what the future of AI holds and share our insights through the MIT quest corporate initiative.

At Oxyml, we believe that the best scientific solutions and ideas to combat health challenges will be ignored if community stakeholders are left out of the decision process. However, empowering communities is a challenging task, as the United States is a large and diverse country with unique challenges in each region.

Our solution makes data and analytics accessible to community leaders throughout the country in an easy-to-navigate platform that allows local businesses and employees to understand the impact a pandemic will have on their financial well-being. By exploring what the financial impact will be on local companies and communities of different pandemic responses at a granular firm and industry-specific level, we can depoliticize pandemic response plans.

Our technological solution utilizes billions of data points from almost 10,000 companies across the United States to draw our conclusions and presents these analytics in an easy-to-understand platform that does not require any technical expertise. By improving the financial security and well-being of everyday Americans during pandemics we can better serve the most vulnerable communities that have to struggle with difficult health challenges and economic hardship during pandemics.

Scientific agencies across the globe tend to be relatively well equipped to analyze and collate health and disease-related data. However, these agencies have also been tasked with generating guidance on re-opening plans to minimize financial damage to the economy. This is a problem: these agencies don’t have the data and insights they need and are asked during a pandemic to rapidly draw these plans without time to collect the right data, hire analysts familiar with this kind of data, and draw conclusions.

Traditionally, artificial intelligence solutions for financial data have only been available to large hedge funds and institutional investors. At Oxyml, we are dedicated to expanding access to artificial intelligence systems based on market and financial data to make the gains from AI advancements available to everyone regardless of income. Our MIT Solve application leverages our expertise in data analytics and the tooling we are building for our platform to help communities, governments, and people across the globe understand the financial impact of pandemics on company bottom lines so the right conclusions about when to reopen the economy can be drawn at both national and local levels.

Our proprietary solution utilizes billions of data points that have been amassed from over 47,000 unique companies across the globe. Our system uses machine learning, time series analysis, game theory, and our own proprietary systems to deliver these solutions to communities most at risk of financial hardship.

One of the biggest challenges in analyzing and understanding supply chains is having the right data at the right time. Supply chains are increasingly becoming more complex. For example, an increase in Bitcoin prices can cause a surge in demand for semiconductor components, which can cause shortages in the automotive industry due to issues in securing automobile chips. In a pandemic, it can be even more difficult to predict supply chain issues due to behavior such as hoarding.

We at Oxyml have experience analyzing complex supply chains and we have the data to generate the insights health care workers and communities need to detect issues in real-time. We collect, analyze, and process data on over 47,000 companies across the globe and can detect complex linkages across supply chains that are not immediately obvious through our proprietary algorithms and time series techniques. This enables us to not only track and detect known supply chain issues such as delivering personal protective equipment but also identify future supply constraints before bottlenecks occur. 

With the right data and our experienced team our MIT solve solution is uniquely positioned to deliver analytics and insights to communities and frontline healthcare workers across the globe. By providing these analytical solutions in real-time on our platform we can help ensure the most isolated communities can anticipate and react to commodity constraints in real-time, saving lives and protecting frontline workers who face the greatest danger during the early stages of a pandemic.