Level Up Your AI Skillset and Dive Into The Deep End Of TinyML

“One prevalent use of ML on microcontrollers (TinyML) includes wake word detection, which is also known as keyword spotting. For example, if you say “Alexa” or “Hey Siri,” your phone or nearby smart speaker may come to life, waiting for further instructions. The smart speaker uses two types of machine learning. The first kind is TinyML, where inference is performed locally in the speaker’s microcontroller to listen for that wake word. Once the speaker hears the wake word, it begins streaming the subsequent audio to an internet-connected server, which performs a much more complex machine learning process known as natural language processing (NLP) to figure out what you’re asking.”


Increasing demand for solutions to simplify banking operations is driving the AI in Banking Market

  • “Due to increasing implementation of AI-driven applications in the banks, including customer relationship management (CRM), data analytics & visualization, and chatbot to enhance customer experience and back-office activities, the software segment is projected to register a significant revenue CAGR of 43.1% during the forecast period.
  • In terms of market share, the deep learning & machine learning segment is expected to lead among the other technology segments in the global AI in the banking market during the forecast period due to growing adoption of deep learning & machine learning approach for risk assessment in banks.
  • Increasing need to optimize customer engagement by introducing AI-driven virtual assistance and provide 24/7 customer services and answer customer queries and grievances is expected to contribute to revenue growth of the customer service segment in the global AI in the banking market during the forecast period.
  • Due to growing need to offer improved customer service in the banking industry, the Chatbot segment is projected to lead in terms of revenue share in the global AI in the banking market during the forecast period.
  • Factors such as growing emphasis of banks in countries in North America on enhancing banking operations with the use of advanced technologies are resulting in the market in the region accounting for comparatively larger revenue share than other regional markets.”


Why Consumers Aren’t Banking Like It’s Still 2019

  • “Doug Brown, president of digital banking at NCR, told Karen Webster in an interview that banking in the branch is not what it was — but what it will be will borrow liberally from the great digital shift.
  • And in revamping in-person banking, he told Webster, smart automation can improve the experience for credit unions’ consumers. Machine learning and artificial intelligence can boost revenues and reduce costs.
  • About 15% of the population, he said, came into the proverbial fold and embraced digital banking — and they haven’t gone away.
  • Combining Video, Audio and Virtual Assistants. The combination of visual and audio, AI and algorithms, said Brown, mean that banking is getting smarter. And high tech, he said, can improve trust and confidence amid “surge activity,” such as during periods of high economic stress or when, for example, a customer has forgotten a password or has been the victim of fraud.”


AI in Banking: Beyond the Bots

– “80% of financial institutions are “highly aware” of the benefits of AI and machine learning.

– 75% of banks with more than $100 billion in assets are currently implementing AI.

– 46% of FIs with less than $100 billion in assets are currently implementing AI.

– By 2023, FIs are projected to save $447 billion by using AI, the majority of that being derived from customer-facing apps like chatbots, and back-office uses like anti-fraud and risk applications.

81% of IT executives in banking agree that ‘unlocking value from AI will distinguish winners from losers.’

– 85% have a clear strategy for adopting AI in the development of new products and services

– 78% say that using AI will help them achieve their business goals and priorities, with 46% of those saying ‘to a great extent.’”


Artificial Intelligence in Banking: Top Priorities for 2022 (And Beyond)

  • “Several surveys and market research studies have found that people actually prefer interacting with bots instead of humans. Although some of these surveys are conducted by conversational AI vendors, skeptics should consider the fact that there are 24 million users of Bank of America’s digital assistant Erica and they completed 123 million interactions in the fourth quarter of 2021, up 247% year over year.
  • Juniper Research forecasts that chatbot interactions will save 862 million hours for banks globally, which equates to $7.3 billion in cost savings.
  • ‘With no shortage of customer data, financial institutions are sitting on a treasure trove of answers in terms of where customers are headed next and what their financial needs will soon be,’ Everfi writes. ‘Armed with that data, institutions can grow wallet share and generate revenue by catering their products and services to customers in anticipation of their time of need.’”