AI in banking: Where it works and where it doesn’t

  • “‘A lot of organizations embrace AI and start to work on it,’ he said. ‘But they have been in continuous experimentation mode, so nothing has really gone into production to drive through business value in terms of new revenue growth, efficiencies or better recommendations. So there’s a lot of money going into it, but no return coming up.’
  • ‘Not just in banking, but in all industries there is going to be some amount of disruption in terms of customer expectation management, financial institutions included,’ Kagoo said. ‘If they do not continue to innovate and drive more hyperpersonalized services and meet their customer where they want to be met, they will lose out right in terms of market share, because the consumer is continuing to get used to, or be introduce to, these kinds of digital models and personalized service.’”

How MIT OpenCourseWare became an educational resource to millions around the world

“That committee’s recommendation was to launch OpenCourseWare, a website offering all of MIT’s course materials, available for free to anyone. Within one year, OCW had published a pilot website with 50 courses and attracted worldwide acclaim. Today, OCW offers materials from over 2,570 courses spanning the MIT graduate and undergraduate curriculum, from 1,735 MIT faculty and lecturers from 33 academic units across all five schools, including syllabi, lecture notes, problem sets, assignments, and audiovisual content including recorded lectures. To date, OCW has been a resource for over 210 million unique users, with over 70 percent of users in 2020 coming from outside the United States.”

How to build a machine learning model in 7 steps

“Step 1. Understand the business problem (and define success)

Step 2. Understand and identify data

Step 3. Collect and prepare data

Step 4. Determine the model’s features and train it

Step 5. Evaluate the model’s performance and establish benchmarks

Step 6. Put the model in operation and make sure it works well

Step 7. Iterate and adjust the model”

No-code A.I. is coming. Is your company ready?

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  • “So Primer has developed a no-code platform it calls Automate. It allows a non-expert to take data from something like a Microsoft Excel spreadsheet and, in about 20 minutes, train an A.I. system to perform some key NLP tasks at accuracies that can approach human-level.
  • Some competing no-code A.I. platforms cost a fraction of that. for instance costs just $145 per month. Akkio starts at $500 per month for a version for small-to-medium-sized businesses but cost more for a license suitable for a larger corporation.”

Sean Gourley


Aunalytics unifies siloed bank customer data with AI-driven data mart and NLP

  • “Aunalytics announced an update to its Daybreak for Financial Services platform that employs machine learning algorithms to enable midrange banks and credit unions to more easily analyze data.
  • The latest update adds a data mart that automatically discovers and aggregates customer data residing in siloed lending, mobile banking, automated teller machine (ATM), customer relationship management (CRM), wealth management, and trust applications.
  • The platform has also added support for a natural language processing (NLP) engine that eliminates the need to know SQL to query data. Companies can automatically create visualizations of those query results as well.”