Collaborating Authors

Banking & Finance

Regulators should encourage adoption of fair-lending algorithms


In 1869, the English judge Baron Bramwell rejected the idea that "because the world gets wiser as it gets older, therefore it was foolish before." Financial regulators should adopt this same reasoning when reviewing financial institutions' efforts to make their lending practices fairer using advanced technology like artificial intelligence and machine learning. If regulators don't, they risk holding back progress by incentivizing financial institutions to stick with the status quo rather than actively look for ways to make lending more inclusive. The simple, but powerful, concept articulated by Bramwell underpins a central public policy pillar: You can't use evidence that someone improved something against them to prove wrongdoing. In law this is called the doctrine of "subsequent remedial measures." It incentivizes people to continually improve products, experiences and outcomes without fear that their efforts will be used against them.

Global Big Data Conference


Nearly two years after a global pandemic sent most banking customers online, the majority of financial institutions appear to be embracing digital transformation. But many still have a long way to go. For example, a recent survey of mid-sized U.S. financial institutions by Cornerstone Advisors found that 90% of respondents have launched, or are in the process of developing, a digital transformation strategy--but only 36% said they are halfway through. I believe that one of the reasons behind the lag in uptake is many banks' new reluctance to use artificial intelligence (AI) and machine learning technologies. The responsible application of explainable, ethical AI and machine learning is critical in analyzing and ultimately monetizing the manifold customer data that is a byproduct of any institution's effective digital transformation.

Data science and AI: drivers and successes across industry


The pandemic accelerated a phenomenon that was already taking place across industry: digital transformation. Lockdowns and similar changes in our behaviours drove a massive increase in demand for online services and this demand is now unlikely to return to pre-pandemic levels. In reaction to this, businesses of all shapes and sizes are striving to make their existing business models increasingly automated and digital-first in a bid to avoid being disrupted. They are also disrupting themselves, changing their ways of working using data and technology in a bid to improve their products and services, remain competitive and create new markets. Central to successful digital transformation is the effective use of data.



The graph represents a network of 7,377 Twitter users whose tweets in the requested range contained "chatbot", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Friday, 01 July 2022 at 13:01 UTC. The requested start date was Friday, 01 July 2022 at 00:01 UTC and the maximum number of tweets (going backward in time) was 7,500. The tweets in the network were tweeted over the 7-day, 8-hour, 36-minute period from Thursday, 23 June 2022 at 15:20 UTC to Thursday, 30 June 2022 at 23:57 UTC. Additional tweets that were mentioned in this data set were also collected from prior time periods.

Leveraging Artificial Intelligence In Capital Markets


The financial industry produces enormous amounts of data. Deep insights in this data are analyzed with machine learning as it interacts with the trading operations and uses sophisticated algorithms to generate trading choices quickly. FREMONT, CA: The swift adoption of artificial Intelligence (AI) by capital market organizations indicates its responsible approach to a safe, effective, efficient, and transparent deployment of models. AI is the newest concept in the financial markets. The international securities markets are changing from art to science with artificial intelligence.

SingularityNET Latest Ecosystem Updates: June 2022


SingularityNET development and blockchain teams have partnered with MLabs, experts in Plutus development for Cardano, to create the AGIX-ADA staking contracts. The contracts are currently under evaluation in testnet and will soon be audited externally. The final stage of development will be creating the staking portal on the SingularityDAO v2 Dapp. The SingularityDAO v2 Dapp is gearing up for launch in Q3, and the staking portal will be launched shortly after that, approximately mid-Q3. The Loyalty Rewards wallet was created to demonstrate the gratitude of SingularityNET to the Phase One token holders for supporting the Phase Two initiative; as well as an opportunity to incentivize and reward community growth through new token holders on the Cardano blockchain. The technical backend portal has been designed and is under evaluation on testnet, and the team is also actively working to integrate more wallets. The portal is expected to be ready for community launch in Q3, and further details on the program will be coming shortly. We look forward to community feedback and discussion as we work with the community to design an optimal system.

Skills or jobs that won't be replaced by Automation, Artificial Intelligence in the future


Roles that involve building relationships with clients, customers or patients can never be replaced by automation. Indulge in digital reading experience of ET newspaper exactly as it is. Download The Economic Times News App to get Daily Market Updates & Live Business News. Who entered the ring of stock markets first? Uber CEO Dara Khosrowshahi dismissed talk of a sale, but should it keep the India biz?

La veille de la cybersécurité


It's simple: In financial services, customer data offers the most relevant services and advice. But, oftentimes, people use different financial institutions based on their needs – their mortgage with one; their credit card with another; their investments, savings and checking accounts with yet another. And in the financial industry more so than others, institutions are notoriously siloed. Largely because the industry is so competitive and highly regulated, there hasn't been much incentive for institutions to share data, collaborate or cooperate in an ecosystem. Customer data is deterministic (that is, relying on first-person sources), so with customers "living across multiple parties," financial institutions aren't able to form a precise picture of their needs, said Chintan Mehta, CIO and head of digital technology and innovation at Wells Fargo.

The quest to understand every voice globally


A speech recognition startup just landed $62 million in Series B funding. How will the money be used? In a quest to enable a computer to understand every voice in the world. If that doesn't strike you as hugely ambitious you haven't spent enough time trying to get Siri to compose a text message. Speech recognition has been a huge challenge for developers, and it's a puzzle that's being closely watched in a variety of industries. The technology has implications for human-machine interfaces in fields like robotics, autonomous vehicles, and personal computing, all of which will benefit from computers that can accurately interpret natural speech.

Matrix AMA -- June 2022


Today is the 28th of June. As usual we are having this June AMA with our CEO Mr. Owen Tao. And just for your information, Owen has just been released from a 17 days quarantine because he has been identified as a cross contact, and as a result of visiting a shopping mall. So why don't you, Owen, share with us what's the life like being quarantined in a hotel, is it a hotel? So the environment is good, yeah?