Data analytics firm Quantexa has entered the unicorn club, reaching a valuation of $1.8bn (£1.5bn) after securing $129m (£103.9m) in Series E funding. Quantexa's funding round was led by GIC, with additional capital coming from Warburg Pincus, Dawn Capital, British Patient Capital, Evolution Equity Partners, HSBC, BNY Mellon, ABN AMRO, and AlbionVC. Several of its backers, including HSBC and BNY Mellon, are also customers of Quantexa. The London headquartered company has developed AI tools to detect and spot fraud and money laundering, along with enterprise intelligence software to assist with business decision-making. The company was previously valued between $800m and $900m in a $153m Series D round in 2021.

Arria NLG, a leading provider of natural language generation (NLG) technologies, has appointed Managing Director and Innovation Strategist, Mark Goodey, to cement Arria Investment Analyst as the Banking, Financial Services, and Insurance (BFSI) industry leader. Arria Investment Analyst uses natural language technologies to bring 100 percent accuracy to investment analysis and to create data-driven investment commentary. "I am excited to lead this initiative," said Goodey. "Arria's Investment Analyst uses natural language technology to analyze investment portfolio performance. It's a technology uniquely placed to support asset managers, asset owners, and the financial services industry, so what used to take hours or days can now be accomplished in seconds."

Pelican AI (pelican.ai), a global provider of Artificial Intelligence-powered payments and financial crime compliance solutions for banks and corporates, announced today that the Treasury Services business of leading global bank BNY Mellon is implementing its AI-based Pelican Secure Sanctions Self-Learning Optimization (SSLO) solution in the coming months to drive efficiency in their global sancti...

CHICAGO, April 15, 2021 (GLOBE NEWSWIRE) -- ModelOp, the pioneer of ModelOps software for major enterprises, today announces release of the first annual State of ModelOps report. Conducted by independent research firm Corinium Intelligence, the report summarizes the first ever research into the state of model operationalization and details the challenges faced by AI-focused executives from top global financial services companies as they scale their AI initiatives. Findings show that while AI is already widely deployed in many large enterprises and investments are growing, nearly 80 percent of surveyed executives reported difficulty managing risk as a barrier to AI adoption, and cite ModelOps as a key enterprise discipline that is receiving significantly increased attention and investment. The report is based on interviews with 100 executives from top global financial services companies in early 2021, providing a unique snapshot of the practices and future plans of large enterprises to govern and scale mission-critical AI initiatives. The findings were combined with commentary and insight from seven industry experts from organizations including Wells Fargo Asset Management, NY Life Insurance, BNY Mellon, FICO and others.

While several traditional banks are testing artificial intelligence, BNY Mellon says it's going further than most, committing to the technology by involving …

Many banks and financial firms are investing in AI and seeing positive return from applying AI throughout their operations. AI-based systems are helping to make more informed, safer and profitable decisions. However, with any technology that's used in a heavily regulated industry there are challenges and pushbacks to adoption. Kumar Srivastava, VP of Product and Strategy of BNY Mellon recently shared with the AI Today podcast insights into AI adoption at the bank. BNY Mellon has a Silicon Valley based Innovation Center that aims to help bring AI innovations to the bank.

Countering digital fraud is a lot like playing whack-a-mole: As soon as one fraudster is taken out, two more pop up where they're least expected. Fighting bad actors is particularly challenging for those in the banking industry, which lost more than $31 billion to fraud in 2018 and is projected to lose even more as cybercriminals become more sophisticated. The popularity of digital banking services has created ample opportunities for bad actors, leaving banks scrambling to protect themselves against the rising tide of fraud. Faster payments have also contributed, as banks now have less time to identify fraudulent transactions. It's nearly impossible for human analysts to examine every sign of malfeasance with banks processing millions of transactions each day, but that is exactly where learning technologies like artificial intelligence (AI) and machine learning (ML) can help.

Artificial intelligence is moving from science fiction to practical reality fast. AI -- technology that teaches machines to learn so they can perform cognitive tasks and interact with people -- is suddenly accessible to many companies. Costs associated with the advanced computing and data-storage hardware behind AI are plummeting. A growing number of vendors also offer AI tools such as robotic processing automation that can be configured without the help of a rocket scientist. So this is clearly an area more banks will need to pay attention to going forward.

Bots that suggest investments to your clients in mere seconds.The future may sound a bit spooky for advisors worried about losing their jobs to automatons. The truth is, as complex digital tools become more practical, advisors will soon have to decide when and where to implement them, says American Banker editor-at-large Penny Crosman. Pitfalls and misfires are bound to come with early adoption. How will advisors avoid missteps, all while pioneering new technology? Striking the right balance between humans and technology is becoming the holy grail for advisory firms.

A robot overlord adjusts Rob's Open Source Android (ROSAL) at the London Science Museum (AP Photo/Alastair Grant) Searching recently for evidence of artificial intelligence taking over our jobs, lives, and everything else, Tom Davenport came up empty. "Nary a robot overlord to be found," he declared at the 14th MIT Sloan CIO Symposium. A day later, at the 3rd RE•WORK Deep Learning Summit, I found many humans who are successfully lording over robots, telling their artificial intelligence creations how to perform a number of narrow cognitive tasks. Davenport, who has published eighteen books on topics ranging from managing organizational data and processes to leading with AI and analytics, is working on his next one, tentatively titled The Cognitive Company. Throughout his distinguished career in a field littered with "hype cycles," Davenport has opted to respond with healthy skepticism to the typical breathless and enthusiastic pronouncements regarding the latest new new thing.