Collaborating Authors

Financial Services

Resona forms 31-firm consortium on facial recognition payment system

The Japan Times

Banking group Resona Holdings Inc. on Thursday established a consortium of 31 Japanese companies across a range of industries to discuss and share know-how on the development of a payment system using facial recognition technology. The bank unveiled the plan for the payment system in August, aiming to allow users to make deposits and withdrawals at banks and shop at stores without presenting anything if they register their facial images in advance, with hopes of creating a standard that can ultimately be utilized in different settings. The joint project is also headed by Panasonic System Solutions Japan Co., a unit of electronics giant Panasonic Corp. which has expertise in facial recognition technology, credit card firm JCB Co. and Dai Nippon Printing Co. The newly announced consortium includes West Japan Railway Co., Seven & i Holdings Co. and Hankyu Hanshin Holdings Inc., among other companies. The facial recognition technology requires customers to register a picture of their face through a website and other personal data.

Artificial Intelligence at American Express - Two Current Use Cases


Ryan Owen holds an MBA from the University of South Carolina, and has rich experience in financial services, having worked with Liberty Mutual, Sun Life, and other financial firms. Ryan writes and edits AI industry trends and use-cases for Emerj's editorial and client content. American Express began as a freight forwarding company in the mid-19th century. Expanding over time to include financial products and travel services, American Express today reports some 114 million cards in force and $1.2 trillion in billed business worldwide. American Express trades on the NYSE with a market cap that exceeds $136 billion, as of November 2021.

Low Adoption Rate for Explainable AI in Financial Services Expected to Grow


People have become very familiar with the term artificial intelligence (AI), but many of its users have only a rudimentary understanding of how it actually works. As a result, to date financial services and many other industries have yet to leverage its full capabilities. For financial services firms, adoption of explainable AI could drive adoption of AI-related technologies from the current rate of 30% to as high as 50% in the next 18 months, according to Gartner analyst and vice president Moutusi Sau, adding that lack of explainability is inhibiting financial services providers from adopting/rolling out pilots and projects in lending and from offering more products to the "underbanked" -- those who don't seek banking products or services, many because they don't think they will qualify. Moving to "explainable AI" will remove much of the mystery around AI, and, as a result will drive adoption of more AI-driven services experts agree. The Global Explainable AI (XAI) market size is estimated to grow from $3.50 billion in 2020 to $21.03 billion by 2030, according to ResearchandMarkets.

Connecticut Money: Artificial intelligence and the AI revolution


The endless possibilities and concerns about future technologies are staggering. Some suggest that through AI's enhanced productivity we will get to a point that humans will be free from working monotonous jobs. In return, we may find ourselves receiving stipends from the work that our robot counterparts are performing. Others fear that our robotic workforce will work their way up the corporate ladder and push us out to pasture long before were ready to leave. No one really knows what the future holds, but one country has an interesting perspective on artificial intelligence and how it will be harnessed to serve its citizens.

Council Post: Three Critical Facets For Financial Services To Succeed In The Digital Future


Parijat Banerjee is Global Business Head for the Banking, Financial Services, and Insurance (BFSI) sector at LatentView Analytics. The pandemic pushed us years forward, and the notion that every modern company is a technology company has only been reinforced by rapidly transforming business practices. We are at an apex of digital transformation, and precision analytics is driving the most successful innovation initiatives across many industries. The unequivocal rise of the connected ecosystem has forced consumers to engage across digital channels, and banking and financial services evolved almost overnight. The race to digital has always seemingly been easy, but the adoption and implementation remain an uphill climb, particularly in the financial services industry, where legacy solutions and antiquated IT infrastructure have a stranglehold on business processes. Over the last 18 months, exponential improvements in digital technology have underpinned the evolution of banking for both internal processes and customer-facing experiences.

Using Artificial Intelligence In Financial Sector - ONPASSIVE


Financial services were one of the first industries to see the potential of the Big Data revolution and the wave of new technology that has accompanied it – including AI. AI is a powerful technology that is already being used extensively in the financial services industry. It has a lot of potentials to make a big difference if firms use it with enough caution, wisdom, and care. Artificial intelligence (AI) is on its way to becoming mainstream in the financial services industry shortly. FinTech firms are more likely to utilize AI to develop new goods and services, whereas incumbents are more likely to improve current ones. An increasing number of FinTechs are approaching AI deployment from a product standpoint, offering AI-enabled services as a service.

Seven technologies shaping the future of fintech


Technological progress and innovation are the linchpins of fintech development, and will continue to drive disruptive business models in financial services. McKinsey estimates that artificial intelligence (AI) can generate up to $1 trillion additional value for the global banking industry annually. Banks and other financial institutions are tipped to adopt an AI-first mindset that will better prepare them to resist encroachment onto their territory by expanding technology firms. In financial services, automatic factor discovery, or the machine-based identification of the elements that drive outperformance, will become more prevalent, helping to hone financial modeling across the sector. As a key application of AI semantic representation, knowledge graphs and graph computing will also play a greater role.

Do Bots Understand Risk?


A financial services company had a problem. It faced increased risk exposure from its artificial intelligence (AI) due to inconsistent monitoring, risk identification, governance, and documentation of multiple applications across its business units. It had to be addressed. The issues potentially exposed the company to poor customer experiences; negative brand image; and legal, regulatory, and compliance violations. Their AI models and applications were generating results quickly, sometimes within a few hours.

Digital transformation is changing banking from the inside out

MIT Technology Review

Companies across all industries are faced with the urgent need to transform the way they do business, including financial services, but changes abound with governance, security, and culture. A shift in mindset and perspective away from "the way things have always been done" is key to a successful digital transformation and to providing the frictionless customer experience banks and other financial services businesses strive to offer. To stay competitive in the wide-ranging fintech landscape, says Michael Ruttledge, chief information officer and head of technology services at Citizens Financial Group, banks need to become more agile and embrace new technologies. He described the five pillars he has used to guide digital transformations at financial institutions: "The first pillar is moving to agile. Second is moving to a more modern architecture. Third is doubling down on the engineering talent at the bank, and fourth is being more efficient and transforming the technology cost structure. Finally, the fifth pillar is maniacally focusing on security and availability." We're trying to make it frictionless for our customers--for instance, we don't want it to take a long time for them to open an account because of the amount of information they have to enter.

Datametrex Signs Additional $750K Contracts with Shinhan Financial and LOTTE


Toronto, Ontario--(Newsfile Corp. - November 9, 2021) - Datametrex AI Limited (TSXV: DM) (FSE: D4G) (OTCQB: DTMXF) (the "Company" or "Datametrex") is pleased to announce that it has received further Purchase Orders ("P.O.") for approximately $750,000 CAD from LOTTE Data Communication Co., Ltd. and LOTTE Hi-Mart Co., Ltd. The P.O. from SHINHAN is for CronMind, an integrated management tasking system that provides job performance results analysis. "As Datametrex continues to keep pace with the global AI transformation, we are pleased that its artificial intelligence systems are being employed by some of Korea's largest conglomerates," stated Andrew Ryu, Chairman of Datametrex. LOTTE Group is the fifth largest conglomerate in Korea with annual revenues of approximately $60 billion USD consisting of over 90 business divisions. LOTTE is engaged in diverse industries that include hotels, resorts, fast food, beverages, retail, financial services, heavy chemicals, electronics, IT, construction, publishing, confectionary products, and entertainment.