Banks Are Cashing In on Embedded AI

  • “In 2021, McKinsey released a report that found that AI is quickly becoming embedded in financial institutions. The report, which surveyed over 200 senior executives across the globe, found that AI is most commonly used for robotic process automation (36%), virtual assistants or conversational interfaces (32%), and machine learning techniques (25%) to detect fraud and support underwriting and risk management.
  • According to a recent IDC report, banks worldwide are expected to spend an additional USD31 billion on AI embedded in existing systems by 2025.
  • The embedded AI sector is expected to reach USD38.87 billion globally at a compound annual growth rate (CAGR) of 5.4% within 2021-2026.”

How NerdWallet uses AWS and Apache Hudi to build a serverless, real-time analytics platform

“NerdWallet’s mission is to provide clarity for all of life’s financial decisions. This covers a diverse set of topics: from choosing the right credit card, to managing your spending, to finding the best personal loan, to refinancing your mortgage. As a result, NerdWallet offers powerful capabilities that span across numerous domains, such as credit monitoring and alerting, dashboards for tracking net worth and cash flow, machine learning (ML)-driven recommendations, and many more for millions of users.”

Roadblocks to getting real-time AI right

  • “Analysts estimate that by 2025, 30% of generated data will be real-time data. That is 52 zettabytes (ZB) of real-time data per year – roughly the amount of total data produced in 2020.
  • Over the last decade, technologies have been developed by the likes of Materialize, Deephaven, Kafka and Redpanda to work with these streams of real-time data.
  • But to really make such enormous volumes of data useful, artificial intelligence (AI) must be employed.
  • To make real-time AI ubiquitous, supporting software must be developed. This software needs to provide:
  1. An easy path to transition from static to dynamic data
  2. An easy path for cleaning static and dynamic data
  3. An easy path for going from model creation and validation to production
  4. An easy path for managing the software as requirements – and the outside world – change”

For the metaverse to grow, mobile digital identities are necessary

  • “Gartner expects that by 2026, ‘25% of people will spend at least one hour a day in the metaverse for work, shopping, education, social media and/or entertainment.’
  • I believe that the metaverse isn’t just a destination we reach through technological devices, but rather a digital identity we carry across platforms and experiences. It seems that regardless of how we define this concept, the role of digital identity remains a constant across all visions of the metaverse.
  • For the metaverse to ultimately succeed, I believe there are three main technological capabilities that must be present:
  1. Personalization of the user’s identity or identities.
  2. The ability to carry identities across platforms.
  3. Access from the user’s mobile device.”

Transforming Financial Services with Data-Driven Insights

  • “Banks and financial services institutions face increased competition not only from peer organizations within the industry, but also now from FinTech startups, Neobanks, and others. The way to compete is to deliver highly personalized services and innovative offerings. And increasingly, the way to do that is using AI/ML to derive data-driven insights upon which those services and offerings can be based.
  • The potential for industry disruption is enormous. Open banking enables the exposure of customer financial data via APIs, extending an organization’s reach far beyond traditional financial services institutions. The open banking market is expected to reach $43.15 billion by 2026, growing at a compound annual growth rate (CAGR) of 24.4% through 2026, according to Allied Market Research.”