Collaborating Authors

AI in banking: from the innovation lab to production


Some 80% of the world's top financial firms are spending billions on artificial intelligence to improve their services and compete with each other. New research from NVIDIA uncovers what those firms are doing and how they're deploying these resources. Competition for consumers and their financial data continues to intensify across incumbent banks, fintech, big tech, and big-box retail. This is compounded by highly innovative digital experiences being deployed across industries, which continue to shift consumer expectations. Kevin Levitt, head of NVIDIA Financial Services says that financial services companies must enhance the level of personalisation, data security, customer service, pricing, and more in the creation and delivery of financial products or expect to lose market share to those who do.

How AI is powering the future of financial services


Financial institutions are using AI-powered solutions to unlock revenue growth opportunities, minimise operating expenses, and automate manually intensive processes. Many in the financial services industry believe strongly in the potential of AI. A recent survey by NVIDIA of financial services professionals showed 83% of respondents agreeing that AI is important to their company's future success. The survey, titled'State of AI in Financial Services', also showed a substantial financial impact of AI for enterprises with 34% of those who replied agreeing that AI will increase their company's annual revenue by at least 20%. The approach to using AI differed based on the type of financial firm.

VMware BrandVoice: How AI Is Powering Modern Banking Transformation


This post is sponsored by NVIDIA. AI is enabling digital transformation across the financial services industry, from fintech and investment firms to commercial and retail banks. With AI, banks can better protect their customers' accounts, secure payments, improve return on investments, and personalize content, investments, and next-action recommendations for their customers. These AI-enabled services were also the top use cases for AI found in the NVIDIA "State of AI in Financial Services" survey of C-suite leaders, managers, developers and IT architects in the global financial industry: fraud detection, portfolio optimization, and sales and marketing enablement. The growing capabilities of AI and increase in available data mean that financial firms need to execute an AI strategy, or risk being left behind their competitors.

How Can Artificial Intelligence Fight Fraud with NVIDIA


NVIDIA has been a presence in the financial industry for more than 15 years. Financial institutions harness NVIDIA's full stack accelerated computing platform to power AI and high-performance computing applications that utilise vast amounts of data to increase revenues, reduce costs, and mitigate risk across the enterprise. NVIDIA works with the largest banks, credit card issuers, and insurers across the globe helping financial institutions deliver AI-powered solutions. Financial institutions bring a range of problems and opportunities to NVIDIA to solve through AI. Ultimately, financial institutions, including fintechs, seek NVIDIA's expertise in accelerated computing to AI-enable hundreds of applications to drive better insights, increase revenues and remove operational inefficiencies.

The Future of Banking: How AI is Transforming the Industry


Today's blog post is a Q&A session with top fintech influencer and founder of Unconventional Ventures, Theodora Lau. Named one of 44 "2017 Innovators to Watch" by Bank Innovation, ranked No. 2 Top FinTech Influencers 2018 by Onalytica, and named to the list of LinkedIn Top Voices 2017 for Economy and Finance, she's a powerful voice in the industry. If you probe into the rapid adoption of artificial intelligence (AI) initiatives in the enterprise, it quickly becomes clear what's behind it: big data. In a 2018 NewVantage Partners survey of Fortune 1000 executives, 76.5 percent cite the greater proliferation and availability of data is making AI possible. As Randy Bean in an MITSloan Management Review article puts it, "For the first time, large corporations report that they have direct access to meaningful volumes and sources of data that can feed AI algorithms to detect patterns and understand behaviors….these