Standard Bank’s data science efforts recognised by Microsoft

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A few years ago data was compared to oil in how valuable it would inevitably become. Much like oil, however, data needs to be analysed and worked with to be of any real value.

It’s all fine and well to have a massive database, but if that database isn’t being used, it’s just taking up storage space.

Data science then has emerged as a valuable commodity in a data driven world and Standard Bank’s efforts in the sector have been recognised by Microsoft.

So what has Standard Bank done?

A team using artificial intelligence and machine learning created a model which is able to predict when a client is going to cancel their short term insurance. Standard Bank didn’t disclose how accurate the model is.

This allows Standard Bank Insurance to proactively contact certain clients to find new ways to satisfy their needs, and ultimately, to improve client satisfaction and retention rates.

The model analyses a range of data points and is continuously learning Standard Bank says.

The team behind the model have been invited to present it at the global Microsoft Business Applications Summit this week.

“We have proven that data analytics can be democratised using the power of AI, and this will further empower the Standard Bank workforce as we accelerate the implementation of our future-ready strategy,” explains head of business intelligence for Insurance at Standard Bank, Dharmesh Kalain.

“We can now quickly build machine learning models without the long wait times associated with the traditional approach by data scientists. This capability allows us to better understand our clients and solve everyday business problems at a rapid rate,” Kalain adds.

Another potential use case of this model is being able to forecast business volumes based on factors such as marketing and COVID-19-related lockdown restrictions.

The model could also predict whether new products or app features are likely to be successful, and can assist with operational budget forecasting to ensure the decision-making is made more efficient.

“We will continue to look at ways to use data science that will help enable self-service analytics throughout the group. We are excited about the business intelligence opportunities created by cloud-based technologies, which will ultimately allow us to have a better relationship with our clients,” Kalain concludes.

Brendyn Lotz

Brendyn Lotz

Brendyn Lotz writes news, reviews, and opinion pieces for Hypertext. His interests include SMEs, innovation on the African continent, cybersecurity, blockchain, games, geek culture and YouTube.

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