Freight-matching services, which pair shippers to freight carriers like trucks and vans, are attracting growing investment. Despite a slow initial uptake -- in a 2018 FreightWaves survey, carriers that use freight-matching services said that they only sourced 11% of their freight from the services -- they've become a larger source of business as the pandemic encourages companies to invest in digital supply chain solutions. Flock Freight, Loadsmart, Next Trucking, and Convoy have raised hundreds of millions of dollars to grow their networks to hundreds of thousands of trucks. While the freight-matching sector is becoming increasingly competitive, new startups with novel approaches -- or what they claim are novel approaches -- are emerging to take on incumbents. Among the newcomers is Parade, which leverages AI-powered technology to help find matches of freight load, route, equipment type, and a carrier's (i.e., shipper's) on-time reliability.

Jeffrey Austin White has joined Holmes Murphy as its Chief Analytics Officer (CAO), bringing his nearly three decades of expertise focused on strategic investments in talent and technology to the national insurance brokerage. In this new role for Holmes Murphy, White will work to increase emphasis on innovation and data intelligence, helping to drive the company's potential and performance for clients. He will largely be responsible for defining and driving analytics and business intelligence initiatives, including assessing the current state of data and analytics capabilities, developing an analytics strategy, and leveraging innovations in artificial intelligence to propel Holmes Murphy and its clients forward. White will also be working to provide insight on potential opportunities for BrokerTech Ventures (BTV), the first broker-led convening platform and accelerator program focused on delivering innovation to the insurance broker industry. "Holmes Murphy continues to raise the bar when it comes to developing technology and innovations within the insurance industry. I'm excited to play a role in advancing their data analytics and AI capabilities," said White.

It will not be an overstatement to say that real estate is one of the biggest drivers of the Indian economy. Currently, the country's third-largest job creator, the sector is expected to contribute around 13% to the national GDP within the next five years. Thus, it is safe to say that technology has been leading the way for the sector to achieve its fullest potential. The past and the present: Understanding real estate's technological evolution Real estate in India has undergone several stages of tech-led transformations in the past decade and a half. The advent of online real estate platforms helped fix the end-consumer challenges to a certain extent.

What I am doing is bypassing the interface to be able to place transactions by using code. If you just need to trade, there is no need to use code at all. In fact, it is likely going to be more complicated. However, if you need to make hundreds of microtransactions per day based on indicators that change every few seconds, then you are not trading normally, you are doing quantitative trading. In this account, I will set up a simulation.

Brokerages who use artificial intelligence could find opportunities to upsell based on changes in a client's lifestyle, according to a software vendor executive. The more data you feed a machine learning model and the more you train it, the better it gets, said Kevin Deveau, managing director of FICO Canada, part of San Jose, Calif.-based Fair Isaac Corp., in a recent interview. Artificial intelligence (AI) is when technology mimics human cognition such as learning from experience, identifying patterns and deriving insights, said Mark Breading, a partner with Boston-based Strategy Meets Action. Machine learning is a type of AI in which computers act without being explicitly programmed, SAS Institute Inc. notes. Bigger brokerages with enough money to invest in AI and machine learning could use those technologies to build a "360-degree view" of a customer, said Deveau, in the context of how the COVID-19 pandemic is forcing companies to change the way they operate.

The number of techy tools that brokers have access to in their toolbox is growing as broker management systems include more and more features, technology vendors offer solutions that allow for the analysis of data coming in from carriers, and insurers plan out brokerage environments of the future that are focused on the customer experience. Not all technology will prove to be useful to brokers, at least not at the outset when these tools are still being honed, and some will fail to be adopted widely – one only has to look at Segways to realize that technology is not always as transformative as it promises. In the case of one brokerage, chatbots were that tech tool that didn't quite take off. "We were one of the brokerages experimenting with chatbots and we never really got to a point where it was there for us to go all in on them," said John McClelland, broker and director of digital for McClelland Insurance, and founder of miBroker, adding that it wasn't a complete enough solution. While the firm's experiments involved using chatbots for lead generation, the next piece of the puzzle was missing.

Insurers are being urged to invest in artificial intelligence after a recent study showed it could lead to a significant rise in revenue for their businesses. According to Accenture's Future Workforce Survey, firms that commit to AI at the same rate as top-performing companies could enjoy an average revenue increase of 17% by just 2022. However, in order to enjoy the potential returns, insurers must also leverage what Accenture calls "applied intelligence" – that is, collaboration between humans and machines. "We believe AI, when synthesized with human ingenuity across the enterprise, will achieve exponentially more," reads the report. "Used in this way, insurers will gain the ability to solve complex challenges, develop new products and services, and break into or create new markets."

Surex Direct, Canada's fastest growing online insurance brokerage, continues to propel the artificial intelligence and machine learning movement – from a broker's perspective – as evident by their latest feature in CI Top Broker magazine. Already incorporating AI to automate and optimize billing processes, Surex Direct is focused on researching and developing AI and machine learning processes in-house. ''We take pride in being a trailblazer in the online insurance space,'' Lance Miller, CEO of Surex Direct, said. Aside from the development and deployment of AI, Surex Direct plans to license products, allowing other brokerages to increase their efficiencies. ''We're fully invested in the AI and machine learning movement,'' Matthew Alston, COO of Surex Direct, said.

Super rich investors in mainland China are skittish towards robo investment advisers taking control of their investments, reflecting a major shift from the US where the asset management tool has enjoyed growing popularity, according to global consultancy McKinsey. Only about 11 per cent of mainland securities investors with investible asset of more than 3 million yuan (US$477,000) endorse the technology to make investments, according the survey released on Tuesday. About 32 per cent of all respondents said they would endorse robo-advisers for full investment dealings. The findings show that the majority of mainland securities investors look to robo advisers as an additional source of investment information and financial product recommendations. However, few are ready to trust artificial intelligence for making calls on investments, in contrast to the faith investors place in robo-advisers in the US and other developed markets, McKinsey said.

Japanese brokerages are launching a consortium dedicated to driving the adoption of blockchain and other innovative technologies in the industry, with the goal of boosting efficiency and providing more convenient services to their customers. The group's 18 founding members include online players like SBI Securities and Rakuten Securities, as well as conventional brokerages like Nomura Securities and Daiwa Securities. SBI Holdings unit SBI Ripple Asia will be the lead organizer for the group. It will hold one or two working meetings a month, as well as carry out proof-of-concept tests on cutting-edge technologies. The group aims to cut costs through industry-wide cooperation. Specifically, the consortium is looking into a shared log-in mechanism for brokerage accounts for customers that uses biometrics and other personal identification information, as well as using artificial intelligence to screen trading activity.