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financial institutions


Starting a conversation: How conversational AI is advancing revenue - CUInsight

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Artificial intelligence (AI) has been trending for some time and not slowing down in its speed, ability, or usefulness. Many financial institutions have implemented at least a basic form of AI to enhance their consumer experience and level of service. This may be a chatbot for online banking or basic IVR (Interactive Voice Response) for the business phone line. As technology gets smarter, consumers experience fast, seamless customer service with other industries, and they are coming to expect the same type of service from their banking and lending institution. Consumer demand and a desire to remain competitive is expediting digital transformation in the financial institution sector, with many financial institutions seeking out conversational AI over conventional AI.


The View From Space: QuantCube Harnesses Satellite Data to Build Environmental Intelligence Tools – A Team

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Alternative data vendor QuantCube has created a slew of environmental intelligence products using satellite data sourced from the European Space Agency combined with other alternative data sources. As well as creating four environmental and social economic indicator services, the Paris-based company has also incorporated the new information into its benchmarking and analytical overlays. The offerings are the fruit of a two-year collaboration with the European Space Agency (ESA) and the French Space Agency (CNES), which gave the company access to its Earth observation data through its business application programme. Using data beamed from the Copernicus programme's Sentinel satellites, QuantCube is providing its clients with four environmental indicators at macro-level: The data is processed by artificial intelligence software after being harvested from orbiting technology that can take detailed images down to 30 square centimetres on the Earth's surface. Satellite technology can also identify concentrations of greenhouse gases and pollutants, including carbon dioxide (CO2), nitrogen dioxide (NO2) and sulphur dioxide (SO2).


6 Digital Banking Transformation Trends for 2022

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Playing a game of catch up, banks and credit unions have accelerated their digital banking transformation efforts. They have invested increasing amounts of capital and human resources into data and advanced analytics, innovation, modern technologies, back-office automation, and a reimagined workforce with a mission to improve the customer experience while reducing the cost to serve. Much of the impetus is because the fintech and big tech competitive landscape continues to expand, offering simple engagement and seamless experiences, causing customers to fragment existing relationships with their existing bank and credit union providers. The good news is that there are a multitude of options available to work with third-party providers that can deploy solutions faster than can be done if developed internally. Incumbent institutions can also partner with fintech and big tech competitors while modernizing their existing systems and processes at the same time.


AI for Trading

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"What fire was to the cavemen, artificial intelligence will be to us." One industry participant explained the influence of disruptive technology on a staid industry in this way. AI is changing the stock market game. While people remain an important part of the trading environment, artificial reasoning is becoming increasingly important. According to a new study by Coalition, a U.K. research group, electronic exchanges account for about 45 percent of money values swapping revenues. While hedge funds are mistrustful of automation, many of them develop AI-powered analysis to create investment ideas and build portfolios.


AI/ML and fraud detection

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A solution like ML is capable of dealing with enormous amounts of data from several sources and knows what the normalized levels of activity are with regard to banking and other financial transactions. Consequently, it can alert the supervisor in case of any deviations from the expected trends. In addition to account owners, fraud can come from merchants and issuers, and their transaction information can be used to train a machine learning model to recognize transactions processing properly.


Seven technologies shaping the future of fintech

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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.


Digital Banking Transformation to Focus on Channels & Analytics in 2022

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Digital banking transformation has enabled many financial institutions to become more prepared for the future as the world was disrupted by the pandemic. For those banks and credit unions that have become the most digitally mature, the focus on improving the customer experience, increasing the use of data and advanced analytics, and deploying new technologies has positioned them at a competitive advantage. Despite the progress made, all financial institutions will need to increase investment in digital banking transformation initiatives, responding to marketplace expectations and adjusting business models to reflect a highly altered banking ecosystem. A great deal of the focus in 2022 will need to be on back-office processes that are highly outdated and have slowed the progression of all digital banking transformation efforts. The future will also see a greater involvement of banking staff in building humanized experiences for transactions that were initiated digitally.


The Impact of AI on the Finance Industry

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A race towards digitization is bringing a revolution in the Financial and FinTech sectors. At the core of this digitization lies the availability of a vast array of data (such as Big Data), advancements in affordable computing technologies, and the advent of intelligent technologies such as Machine Learning and Artificial Intelligence. AI has been around for nearly 70 years, its practicality and intelligence have increasing over time. Today, AI has become an integral part of the industrial landscape as well as the lives of common people. Examples of this can be seen in the voice assistants in smartphones, the use of AI robots in supply chain logistics, self-driving cars, movie recommendations on Netflix, and more.


Singapore launches national AI schemes, adds $133M investment to research

ZDNet

Singapore has unveiled two new programmes to drive the adoption of artificial intelligence (AI) in the government and financial services sectors. It also plans to invest another SG$180 million ($133.31 million) in the national research and innovation strategy to tap the technology in key areas, such as healthcare and education. The fund is on top of SG$500 million ($370.3 million) the government already has set aside in its Research, Innovation and Enterprise (RIE) 2025 Plan for AI-related activities, said the Smart Nation and Digital Government Office (SNDGO) in a statement Monday. These investments have been earmarked to support various research in areas that address challenges of AI adoption, such as privacy preserving AI, and of societal and economic importance including healthcare, finance, and education. The funds also will facilitate research collaborations with the industry to drive the adoption of AI.


Winning the Anti Money Laundering War with Ongoing AML Solutions

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While money is the prime necessity of life, it is also the feeding grain for criminals and terrorist organisations. One term that we hear quite often regarding money-related crimes, is'Money Laundering'. In simple words, 'money laundering' is the unlawful act of deliberately trying to conceal the origins of financial assets, in order to legitimise the financial transactions used for criminal offences. The money launderers try to mask the trail of their assets by introducing illegal profits in their financial history, which makes the process of money tracing'obscure' for the financial institutions. The illegal money, which is not traceable, is then used to carry out criminal activities.