Taishin International Bank launched a data-driven project in 2021 to use ‘big data’ more effectively in a better integrated, updated technology stack that uses Machine Learning (ML) algorithms to analyse customer needs and a real-time personalised marketing platform to meet them. It was Highly Commended (HC) in the Best Next Generation Offering category at the 32nd PBI Global Wealth Awards 2022.
Taishin wanted a better customer management model and realised that this meant enhancing its data import, integration, and application – if it was to meet its aim of providing a better service and moving its marketing efforts from an active to an interactive basis.
The IT and organisational overhaul of how Taishin, headquartered in Taiwan, processes and uses data launched last year, faced two major challenges – namely:
Using unstructured ‘big data’: the financial services (FS) industry has traditionally been better at using structured data internal applications that mine its own information about customers and find data about correspondent FS firms, infrastructures (FMIs) for connectivity purposes, and so on from its own internal sources. Unstructured ‘big data’ emanating from social media, web browsing, voice services, financial market news showing sentiment and trends, and so on is difficult to analyse and apply. But it contains a lot of valuable information. Taishin needed to master ‘big data’ and integrate it into their IT operations. ML was the answer.
Shorter attention spans: modern people receive and process up to 34 gigabytes of information a day, according to a recent study by the University of California, San Diego. This means they may not pay attention to information provided by a bank if it’s in a pre-existing communication pattern that isn’t relevant to their lives anymore – say a postal letter. This adversely impacts the customer experience (CX), satisfaction and marketing responses rates.
Taishin has resolved these issues by adopting new artificial intelligence (AI)-inspired ML systems and techniques. The deep Machine Learning technologies it is now using, such as AutoEncoder neural network and the Light Gradient Boosting Machine (LGBM) ML algorithm that can rank, classify and improve data consumption, are helping it transform its operation.
When used in conjunction with a new application, such as a new real-time personalised marketing platform recently introduced, the business benefits of improved data mastery become plain. Marketing response rates, customer satisfaction and ultimately revenues have risen.
An enhanced application programming interface (API) transmission mechanism has also improved the synchronisation of Taishin’s channels to market, and its self-learning, data-driven CX improvement model. It truly now has a next generation, customer-centric service that is fit for the modern age.