Alumna Geeta Sankappanavar founded Akira Impact, an investment firm that directs capital to support the UN Sustainable Development Goals, reports Cheryl Robinson for Forbes. “The firm invests in companies that support gender equality, clean water and sanitation, clean energy and responsible consumption and production,” writes Robinson.
Prof. Diana Henderson, Prof. Daniel Jackson, Prof. David Kaiser, Prof. S.P Kothari, and Prof. Sanjay Sarma have released a new white paper “summarizing their ideas for a new type of undergraduate institution,” writes David Rosowsky for Forbes. “The authors have done a commendable job identifying and assembling some of the proven high-impact practices each of these types of higher educational institutions can offer,” writes Rosowsky.
At MIT’s AI Policy Forum Summit, which was focused on exploring the challenges facing the implementation of AI technologies across a variety of sectors, SEC Chair Gary Gensler and MIT Schwarzman College of Computing Dean Daniel Huttenlocher discussed the impact of AI on the world of finance. “If someone is relying on open-AI, that's a concentrated risk and a lot of fintech companies can build on top of it,” Gensler said. “Then you have a node that's every bit as systemically relevant as maybe a stock exchange."
Prof. Jonathan Parker and other researchers have found that Covid-19 relief payments have served as a form of insurance for families, reports Howard Schneider for Reuters. Although, “’the small short-term spending response and its pattern suggest that the (economic-impact payments) went to many people who did not need the additional funds,’” writes Schneider.
Prof. Andrew Lo speaks with Forbes contributor Russell Flannery about his work using finance to help lower the cost of drug development for cancer treatment and therapies. “I started thinking about how we could use finance pro-actively to lower the cost of drug development, increase success rates, and make it more attractive for investors,” says Lo. “Because that's really what the issue is: you need investors to come into the space to spend their billions of dollars in order to get these drugs developed.”
Francis Plaza ’13 co-founded PayMongo, a fintech firm designed to digitalize the Philippine’s cash-based economy, reports Catherine Wang for Forbes. “PayMongo now not only plans to expand beyond the Philippines to other Southeast Asian countries, but also to broaden its remit by becoming a platform for scaling small business in the region,” writes Wang.
Prof. Silvio Micali speaks with Los Angeles Times reporter Laurence Darmiento about his predictions for the future of crypto. “The moment the blockchain starts to be used for transactions, the few blockchains that are really capable of transacting at a very low cost, they’re going to emerge, in my opinion,” says Micali. “When traditional finance starts getting on the blockchain, you’re going to see the blockchains that are really used in a massive and transactional way are going to accelerate.”
In an article for the Financial Times, Prof. Robert Merton underscores the importance of providing workers with financial security in retirement and explains Selfies (Standard-of-living indexed, forward-starting, income-only securities), a pension-like bond innovation he helped create. “More such innovative instruments from academics, politicians and others are needed if we are to ensure more people can retire with resources that can withstand inflation and provide the security they need,” Merton writes.
Wall Street Journal reporter Luis Garcia spotlights how Prof. Antoinette Schoar and University of Chicago Prof. Steven Kaplan developed a public-market-equivalent (PME) method known as the Kaplan-Schoar approach that serves as an alternative advantage in comparing fund performance with stock market benchmarks. “The thing that PME allows you to do better is compare across fund vintages,” says Kaplan.
Writing for The Los Angeles Times, Prof. Simon Johnson makes the case for imposing more stringent sanctions on Russia. “The war crimes committed by Russian forces at Bucha in Ukraine have brought greater clarity to economic sanctions,” writes Johnson. “What is in place now is insufficient and needs to be expanded.”
MIT researchers and two high school seniors have developed DualFair, a new technique for removing bias from a mortgage lending dataset, reports Hiawatha Bray for The Boston Globe. “When a mortgage-lending AI was trained using DualFair and tested on real-world mortgage data from seven US states,” writes Bray, “the system was less likely to reject applications of otherwise qualified borrowers because of their race, sex, or ethnicity.”
Educators from the Asia School of Business and MIT have developed a course aimed at teaching central bankers how the market is impacted by bottlenecks and how monetary policy can help, reports Enda Curran for Bloomberg. “The curriculum covers topics that include crisis prevention, behavioral finance, cybersecurity, digital currencies, and ethics,” writes Curran.
TechCrunch reporters Christine Hall, Anita Ramaswamy, Connie Loizos and Mary Ann Azevedo spotlight Sribuu, an AI-powered personal financial advisor in Indonesia, co-founded by Nadia Amalia ’20. The company is aimed at helping “users make better money decisions with our wealth management tools and give personalized saving advice based on their financial habits,” they write.
Forbes contributor Rick Miller spotlights “In Pursuit of the Perfect Portfolio: The Stories, Voices, and Key Insights of the Pioneers Who Shaped the Way We Invest,” a new book by Prof. Andrew Lo and Prof. Stephen Foerster of the University of Western Ontario. The book “provides historical perspective on the development of modern investment theory and practice,” writes Miller.
Fortune reporter Jeremy Kahn spotlights a study co-authored by Prof. Marzyeh Ghassemi exploring issues associated with “explainable” AI systems that are being applied in fields such as healthcare, finance and government. The researchers explain that those using such systems “might have misunderstood the capabilities of contemporary explainability techniques—they can produce broad descriptions of how the AI system works in a general sense but, for individual decisions, the explanations are unreliable or, in some instances, only offer superficial levels of explanation.”