Shin Kong Financial picks DataRobot for AI, data democratisation

Photo courtesy of Shin Kong Financial Holdings

Shin Kong Financial Holdings is working with DataRobot to tap the latter’s AI Cloud Platform and its end-to-end AI and machine learning technology.

The collaboration is intended to strengthen the Taiwan-based Shin Kong Financial’s AI modeling capabilities through implementation of AI and data democratisation strategies for leveraging data science at scale to accelerate digital transformation goals.

With DataRobot’s rich automation features that extend to model risk management and model validation, Shin Kong Financial Holdings plans to alleviate tedious and repetitive tasks from the data technology teams, who will in turn, focus on the design and development of innovative products and services.

Shin Kong Financial Holdings will use DataRobot to build, deploy and monitor AI models, to achieve data-driven goals that include optimising existing digital services and improving customer digital experience.

These also include providing accurate and customized recommendations and services by predicting the demand for digital financial products; and implementing AI citizenship and data citizenship.

DataRobot will support Shin Kong Financial in its drive for value-based finance through the provision a unified AI Cloud platform, allowing users to quickly experiment, execute and deploy AI-model projects.

DataRobot will also accelerate the time-to-market of innovative services enabled by AI, such as to assist Shin Kong Financial and its subsidiaries to better analyse target customers, market segments and new product positioning, and identify the best cross-selling opportunities.

DataRobot’s AI Cloud Platform can handle a large variety of data types, promotes enhanced collaboration amongst various user personas and facilitates continuous optimisation of AI models across the AI lifecycle.The DataRobot AI Cloud Platform can be deployed in the cloud or in an on-premises data centre, providing a high degree of risk management through robust security management and controls.

“The emergence of automated machine learning (AutoML) has broken through the limitations of applying machine learning at scale. With the automated model training process, DataRobot combines hyper-automation and data citizenship,” said Zhang Weixiong, senior associate of digital technology development at Shin Kong Financial.

“These two characteristics effectively help data scientists and practitioners focus on high value business analysis to clarify and solve key problems,” said Zhang.

Also, Zhang said that AutoML is the first step in the journey towards AI and data citizenship. While Data scientists used to spend a lot of time on manual tasks such as coding, DataRobot now completes model building with a simple point-and-click method. 

The platform adopts an easy-to-navigate graphical user interface which reduces the barrier of entry and learning curve for data citizens to get started — thereby improving the efficiency of cross-team collaboration and communication.

Further, extensive automation of the end-to-end model building, validation, deployment and management processes drastically reduces the development time of AI models.