To fix roads, fix the fixing Roadway owners and operators today are under pressure from multiple trends. To keep pace with projected growth in passenger and freight road transport, governments around the world will need to invest $900 billion per year once traffic returns to prepandemic levels.
Banks hold a record of much of what we spend, save, and borrow—from electricity bills and mortgage payments to our weekly spend on fuel and coffee. Now, some of that customer data is being shared with third parties in a global movement known as “open financial data” (sometimes referred to as “open banking.”) Roughly half a decade in the making, it’s unlocking a wave of digital financial innovation—and likely disruption.
The thoughtful use of advanced analytics is transforming the efficacy and efficiency of public-sector agencies’ most critical work. For example, in the United States, it has helped the Internal Revenue Service (IRS) identify potentially fraudulent tax returns, helped the city of Las Vegas create targeted restaurant inspections by gathering information about public-health concerns from social media, and supported NASA’s Jet Propulsion Laboratory in generating weight-reducing designs for space exploration.
AI Handshake getty The business of ensuring protection from financial loss and mitigating risk is as old as human civilization. The Code of Hammurabi, King of Babylon, written in 1750-1755 B.C., specified the first provisions of what we would now know as marine insurance.
Cost pressure in grocery is an evergreen topic. Despite unprecedented sales growth caused by the pandemic, grocers can still pursue many opportunities to become more profitable. As sales levels stabilize, both public and private companies will again face cost pressures.
A midsize bank wanted to go completely cloud native: modern core-technology architecture, agile, and DevSecOps . It moved aggressively, recruiting top engineering talent and automating many controls. However, it quickly realized that it needed to bring its risk and security functions along on the transformation journey.
In the decade since US banking regulators published their seminal guidance on model-risk management (OCC Bulletin 2011-12 and SR Letter 11-7), the development, monitoring, testing, and validation of models have evolved considerably.
If you’ve visited a doctor lately, you may have experienced how your healthcare data — records, scans, prescriptions — is increasingly accessible wherever you interact with a healthcare provider. But you don’t control your own healthcare data storage.
The COVID-19 pandemic has rapidly transformed the packaging industry in several ways, not least by accelerating the need for digital adoption, an area in which the industry has historically lagged. To understand the current state of play and the opportunity space for digital and analytics (DnA) in the industry, we launched a global survey with industry executives backed up by interviews with industry experts covering multiple packaging substrates and regions.
The Covid-19 crisis exposed stark differences in the fortunes of different small and medium-sized businesses (SMBs). Well-capitalized startups have weathered the storm better than cash-poor community businesses; manufacturers of PPE equipment have experienced unprecedented demand while hospitality venues have been shuttered; and digitally enabled retailers have been able to shift delivery and customer services online, pivoting into entirely new business models.
Advanced analytics, including artificial intelligence, offers a big opportunity for the retail industry. McKinsey Global Institute estimated in a study the potential annual value of artificial intelligence for the retail industry at $400 billion to $800 billion globally.
As biopharma companies continue to cope with the COVID-19 pandemic and position themselves for recovery, digital and analytics can be a powerful tool in manufacturing and operations. It can drive the next wave of business optimization by transforming operational performance, shortening time to market, improving quality and yield, reducing supply chain volatility, and accelerating technology transfers.
As we noted at the beginning of this series on the AI bank of the future, disruptive AI technologies can dramatically improve banks’ performance in four key areas: higher profits, at-scale personalization, smart omnichannel experiences, and rapid innovation cycles.
What is a ? A decision support system (DSS) is a computer program application used to improve a company’s decision-making capabilities. It analyzes large amounts of data and presents an organization with the best possible options available.
