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2021 planning: New business models, big opportunity

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2021 planning: New business models, big opportunity


Certainly, corporate execs and finance professionals have to focus on the future and take advantage of emerging technology. “You have to evolve to succeed,” explains Scott Brown, senior vice president of finance at tech distributor Mouser Electronics. “Whether it’s software, hardware or automation, we are investing in state-of-the-art solutions and systems to help us work smarter across all areas of the company.” 

The good news: Nearly everyone is feeling optimistic. A worldwide survey of 297 business executives conducted by MIT Technology Review Insights, in association with Oracle, shows that organizations are ready to invest in innovative ideas to reinvigorate their organizations. And they’re getting the work underway. 

The journey from survive to thrive 

The pandemic challenged every business in 2020. It tested every element of organizations’ workflows and utterly changed their planning processes. But by autumn, most executives had a handle on the situation. When they spoke with MIT Technology Review Insights, they were busy designing strategic business plans for 2021. Among them: major business model and technology adjustments to help them achieve success. 

Most execs are upbeat about their companies’ future. Few are are postponing any sort of changes for the next 18 months or putting everything on hold until things shake out. 

Overall, 47% expect their business to thrive in 2021, 36% expect their organizations to transform, and only 12% are hunkering down for a bleak year of survival. Herein, “thrive” is distinguished as a successful continuation of an existing business model. Take a manufacturer of standing desks—there’s a good chance it’s selling a lot more with the influx of employees now working from home. Compare that to “transform,” or making significant changes. That might include rethinking how a company sells to customers or adding a new product line. 

The 2021 objectives vary by company size to some degree. Large companies—which in this report are organizations with more than $1 billion in revenue—are more open to transforming; in contrast, small and midsize companies aim to thrive. 

Making big moves 

Perhaps it’s possible to cope in the short term by making modest adjustments, such as renegotiating supply chain contracts or reskilling displaced workers. But many companies have used the pandemic as an opportunity to reassess their business. Which parts can succeed mostly as-is? Which need redirection? Which should be eliminated? Where are the untapped growth areas? Whatever their conclusions, corporate executives are taking action. 

These are rarely small changes. For instance, some in the retail industry quickly found ways to keep business buoyant while stores were closed—bolstering their e-commerce setups and making it easier for customers to shop online or arrange for contactless pickup at a store. The coffee industry made changes across its entire supply chain, from harvest to the local coffee shop, despite the uncertainty of demand. 

In 2021, 80% of businesses surveyed are planning strategic big moves, such as acquisitions, divestitures, new business models, and widespread automation. In fact, 39% have already made a “big move” in 2020. Just over a quarter of businesses, 27%, are contemplating such plans in 2021. In some cases—14% overall—the major plans are underway but are not scheduled for deployment in the next 36 months. 

Big moves are more likely to be undertaken by larger organizations; 87% of businesses with more than $1 billion in revenue have plans, compared with 76% of smaller businesses. These large-scale changes are also more common in the Americas—84%, compared with roughly three quarters with such plans in Europe, the Middle East, and Africa (EMEA), and Asia-Pacific. 

Download the full report.

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Banks need to strike the right balance for digital transformation

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Banks need to strike the right balance for digital transformation


Every financial institution is looking to digital transformation to meet rising customer expectations for speed and convenience, lower its operating cost, and fend off competition, including from tech companies moving into financial services. Some are spending over 10% of yearly revenue on technology investments, according to Bloomberg. “This is a huge investment and most financial institutions cannot support this for the long term,” says Michael Fei, SME banking CEO at OneConnect Financial Technology, an associate of Ping An Insurance.

The covid-19 pandemic has revealed how even financial institutions that considered themselves digitally advanced are, in reality, still wedded to analog processes along the chain of processing.

“For many financial institutions, this has been a wake-up call,” says Fei. “In the past, many had thought that if they have an online portal and a mobile application then that’s enough. But now they’ve realized it’s not. Some banks have online portals and mobile apps where you can apply for loans, but they still need to send items to the customer and carry out on-site inspection before they can process the loans, which hasn’t been possible during covid. Banks have had to reshape and redesign the whole process of their lending products.”

Banks have also realized their lack of truly deep customer knowledge, which is crucial to inform responsible and flexible decisions during an economic downturn as customer needs rapidly change.  

“Now that everything is digital, financial institutions are realizing how little they knew their customers,” says Tan Bin Ru, chief executive officer for Southeast Asia at OneConnect Financial Technology. “Customer hyper-personalization tools, to understand what products to offer, have been acknowledged conceptually for a long time but not implemented—now banks are moving towards it and really getting tools to do it.” Traditional banks that were not previously utilizing alternative datasets now want to integrate them more into secure lending, Tan says.

The power of partnerships

Banks have increasingly understood they need outside help to execute their digital transformation agenda. “Banks usually have very rigid systems and procedures,” says Fei. “For instance, if you want to launch a new product you have to follow the process, and it takes at least six months. In the age of digitalization, this doesn’t work, as customers want things immediately. This has put huge pressure on these financial institutions to build agile operations and systems to be able to respond to the needs of their customers.”

But the number of tech companies pushing into financial services can be overwhelming and not all of them have domain expertise, which can lead to misguided attempts to apply new technologies everywhere. Without experience of financial services, tech companies may also underestimate the trade-offs involved in deploying certain digital tools. 

OneConnect combines expertise in digital technology with deep knowledge of banking. Fei, who has past experience working at HSBC China and Bank of Langfang, a Chinese commercial bank, describes one partnership with a Chinese national bank to reimagine its customer service center as an illustration of why banking experience matters in digital reform. The lender was looking to transform a 6,000-person call center toward a more intelligent, AI-enabled approach with greater use of automation. But automating customer services must be done carefully; customers will not appreciate being handed off to a robot for certain sensitive or urgent inquiries where a human counterpart is desired.  

OneConnect built a knowledge map with the bank, to understand and anticipate what problem a customer is trying to solve with a given query, and then understanding when and where to apply automation versus human support. “This required extensive understanding of the business and the industry, which many technology companies do not have,” he says. “You need that, to know when to intervene, what should be done by robotics and what should be a human being. Many tech companies cannot offer this.”

Rather than advocating digital transformation across the board, OneConnect works to get the right balance between customization and integration, and to appreciate that banks are looking for a blend, or omnichannel approach. “Our banking customers, and their customers, want to be offline for certain things, and online for others; they want that flexibility,” says Tan.

A second partnership problem banks face is the sheer number of technology vendors and startups, which can be overwhelming and complicate their digital transformation journey. It is unclear which fintechs will survive and which will not; startups might offer an appealing technology, but if their underlying business model proves unviable, or they cannot raise sufficient funding to support their expansion, or they pivot to a new direction, a bank is exposed.

In many cases, banks take on many different fintechs because no single startup can manage the breadth of their needs, or because the bank wants to diversify its risk. “Since the digital journey is such a long process, a lot of banks feel they need to look at 15 to 20 fintechs to piece together their journey, but the more players they have, the more risk there is,” says Tan.

OneConnect solves both problemsan overly complicated vendor network and the risk of working with fledgling tech companies—by offering a broad sweep of turnkey solutions, with the commercial scale and security that customers can rely on. Typically, a bank will chart its desired journey and up to 80% of those solutions can be provided by OneConnect, says Tan. The company, publicly traded on the New York Stock Exchange, also draws on over 30 years of experience in financial services of its parent company, Ping An, described by The Economist as a window into the future of finance. “No other traditional financial-services group in the world comes close to rivaling Ping An’s ability to develop technologies and deploy them at such a scale,” the magazine recently wrote.

OneConnect: The journey so far

OneConnect has built a broad business in China, serving all of its major banks, 99% of its city commercial banks, and 53% of insurance companies. But its footprint is increasingly global, with over 50 international customers in more than 15 markets, including Singapore, Indonesia, Malaysia, Philippines, and Abu Dhabi.

The company has built new technology solutions to enhance pricing accuracy, such as an alternative data, AI-based credit scoring model for a credit bureau in Indonesia, and supported Malaysian banks to develop user-friendly apps, digital portals, and onboarding. It is leveraging image recognition, a core enabler of “insur-tech” that allows insurers to quickly assess damage claims and pay out to eligible beneficiaries. OneConnect has partnered with Swiss Re, a European insurer, to develop a digital end-to-end solution for motor claims handling, based on AI-based image recognition and advanced data analytics. The tool can analyze photos of vehicle damage, identify repair needs and costs within minutes, offer cash payments, and even offer value-added services, like directing drivers to a repair garage.

OneConnect is also helping build the fintech ecosystem by working with governments, regulators, and stakeholders. It is working with Singapore’s blockchain association to build the skills, literacy, and talent pool needed to enable innovation and has partnered with Abu Dhabi Global Market, a financial center in the United Arab Emirates, to support the development of a “digital lab,” a sandbox for fintechs to collaborate and develop their innovations.   

Working closely with its partners at home and abroad, OneConnect is helping the finance industry move swiftly into the digital era by leveraging the right tools at the right time, benefiting customers and finance institutions alike by widening access to services and lowering costs.

This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review’s editorial staff.

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Will your neighbors get vaccinated?

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Will your neighbors get vaccinated?


As the coronavirus vaccines have rolled out across the US, the process has been confusing and disastrous. States, left by the federal government to fend for themselves, have struggled to get a handle on the logistics of distribution. Many, including Georgia, Virginia, and California, have fallen woefully behind schedule.

But even if there were a perfect supply chain, there’s another obstacle: Not all Americans want the vaccine.

Survey data gathered through Facebook by Carnegie Mellon University’s Delphi Lab, one of the nation’s best flu-forecasting teams, showed that more than a quarter of the country’s population would not get vaccinated if it were available to them today. How people feel about receiving vaccinations varies widely by state and county. The percentage of respondents who would accept a vaccine falls as low as 48% in Terrebonne parish, Louisiana, and peaks as high as 92% in Arlington county, Virginia.

The findings are extremely worrying. The fewer people who are vaccinated, the longer the virus will continue to ravage the country, and prevent us from returning to normal. “It’s one of those things that probably shouldn’t have surprised me,” says Alex Reinhart, an assistant teaching professor in statistics & data science, who was part of the research. “But when you look at the map, it’s still surprising to see.”

The good news—and there is some good news—is that this data could also help fight public hesitancy. The Delphi Lab has been helping the CDC to track and understand the spread of covid infections since the beginning of the pandemic. The latest survey will help the agency identify where to perform more targeted education campaigns. The research group is also working with several county-level health departments to inform local outreach.

The Delphi researchers collected the data via a large-scale survey that it has been operating through Facebook since April 2019. It works with the social media giant to reach as wide a cross-section of the US population as possible, and surfaces daily questions to a statistically representative sample of Facebook users. An average of 56,000 people participate daily, and the company itself never sees the results.

During the pandemic, the survey has included a variety of questions to understand people’s covid-related behaviors, including mask adherence, social distancing, and their mental health. Some of the results are fed into the lab’s coronavirus forecasting model, while others are summarized and given directly to public health officials and other academic researchers. The questions are regularly updated, and the vaccine acceptance question was added at the start of January—after the first vaccines had been authorized by the US government.

The map visualizes each county’s polling average from January 1 to January 14. For counties with too few daily respondents—less than 100—the Delphi researchers grouped the data from neighboring counties. This is reflected in our map above, which is why various clusters of counties show up with the same percentage. The researchers also independently verified their results with some of the CDC’s own surveys and Pew Research.

Next, the researchers plan to expand their survey to understand why people are reticent about the vaccine. They’re also exploring questions that could help identify what blocks people from accessing vaccines, especially for at-risk populations.

This story is part of the Pandemic Technology Project, supported by the Rockefeller Foundation.

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Worried about your firm’s AI ethics? These startups are here to help.

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A screenshot of Parity's library of impact assessment questions.


Parity is among a growing crop of startups promising organizations ways to develop, monitor, and fix their AI models. They offer a range of products and services from bias-mitigation tools to explainability platforms. Initially most of their clients came from heavily regulated industries like finance and health care. But increased research and media attention on issues of bias, privacy, and transparency have shifted the focus of the conversation. New clients are often simply worried about being responsible, while others want to “future proof” themselves in anticipation of regulation.

“So many companies are really facing this for the first time,” Chowdhury says. “Almost all of them are actually asking for some help.”

From risk to impact

When working with new clients, Chowdhury avoids using the term “responsibility.” The word is too squishy and ill-defined; it leaves too much room for miscommunication. She instead begins with more familiar corporate lingo: the idea of risk. Many companies have risk and compliance arms, and established processes for risk mitigation.

AI risk mitigation is no different. A company should start by considering the different things it worries about. These can include legal risk, the possibility of breaking the law; organizational risk, the possibility of losing employees; or reputational risk, the possibility of suffering a PR disaster. From there, it can work backwards to decide how to audit its AI systems. A finance company, operating under the fair lending laws in the US, would want to check its lending models for bias to mitigate legal risk. A telehealth company, whose systems train on sensitive medical data, might perform privacy audits to mitigate reputational risk.

Parity includes a library of suggested questions to help companies evaluate the risk of their AI models.

PARITY

Parity helps to organize this process. The platform first asks a company to build an internal impact assessment—in essence, a set of open-ended survey questions about how its business and AI systems operate. It can choose to write custom questions or select them from Parity’s library, which has more than 1,000 prompts adapted from AI ethics guidelines and relevant legislation from around the world. Once the assessment is built, employees across the company are encouraged to fill it out based on their job function and knowledge. The platform then runs their free-text responses through a natural-language processing model and translates them with an eye toward the company’s key areas of risk. Parity, in other words, serves as the new go-between in getting data scientists and lawyers on the same page.

Next, the platform recommends a corresponding set of risk mitigation actions. These could include creating a dashboard to continuously monitor a model’s accuracy, or implementing new documentation procedures to track how a model was trained and fine-tuned at each stage of its development. It also offers a collection of open-source frameworks and tools that might help, like IBM’s AI Fairness 360 for bias monitoring or Google’s Model Cards for documentation.

Chowdhury hopes that if companies can reduce the time it takes to audit their models, they will become more disciplined about doing it regularly and often. Over time, she hopes, this could also open them to thinking beyond risk mitigation. “My sneaky goal is actually to get more companies thinking about impact and not just risk,” she says. “Risk is the language people understand today, and it’s a very valuable language, but risk is often reactive and responsive. Impact is more proactive, and that’s actually the better way to frame what it is that we should be doing.”

A responsibility ecosystem

While Parity focuses on risk management, another startup, Fiddler, focuses on explainability. CEO Krishna Gade began thinking about the need for more transparency in how AI models make decisions while serving as the engineering manager of Facebook’s News Feed team. After the 2016 presidential election, the company made a big internal push to better understand how its algorithms were ranking content. Gade’s team developed an internal tool that later became the basis of the “Why am I seeing this?” feature.

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