AI banks, next big thing in SA market

  • “One hindrance in the adoption of AI could be the perceived complexity and expenses of the exercise. A requirement to have data clean and in central point, employing data scientists to undertake analysis, build and test models, then having the flexibility to react to a model’s outcome sounds like a difficult and expensive journey.
  • Winjit’s PredictSense is an end-to-end machine learning platform powered by AutoML to create AI-powered analytical solutions. Drag-and-drop low code functionality gives the layman a tool to be able to generate machine learning models and deploy them in to live databases.”

2021 Fintech Predictions – Finextra

“With competition reaching critical mass in the banking industry in recent years, agility is essential in being able to compete and drive new products quickly to market. A bank can no longer decide to forgo modernisation and cloud adoption, unless they are open to the risk of becoming overtaken and obsolete.

COVID-19 has plunged banks into an unknown future. Banks have had to adjust processes and policies overnight in response to changing regulation and customer requirements, which legacy, on-premise systems were not built for. As the crisis continues to evolve, banks are navigating blind on how to proceed. This has emphasised the need to have a system that allows banks to pivot quickly and smoothly.”

How Traditional Banks can Stay Ahead of Fintech Firms with Conversational AI

  1. “Customers Want Quick Contactless Payment Methods
  2. Legacy Systems Costs Banks Huge Chunks of Money
  3. Offering Omnichannel Banking Services
  4. Conversational AI is a Key to Increase Revenue
  5. Conversational AI Adoption is a Survival Imperative for the Banks
  6. Banks can Avail Enterprise-Grade Security
  7. Conversational AI Helps Banks Adapt Quickly”