Reach the future of banking through modern operations and data management

EVENT COVERAGE: HITACHI Reach the future of banking through modern operations and data management

Banks are now compelled to up the ante to compete with fintechs, which has grown wise in leveraging data.

Banks have mainly supported customers’ financial needs in the past. However, as needs started changing and the technologies evolve, fintechs have entered the scene and are now becoming a threat for banks who are late to innovate.

Now under extreme pressure to keep up with the competition, banks now have to employ the same technologies to ride the digitalisation and automation waves. They also have to modernise their operations and maximise the full value of data to reach the future faster.

This has been the main topic of the latest virtual roundtable hosted by Hitachi Vantara, in partnership with Asian Banking and Finance. Entitled “Bringing the Bank of the Future to Today,” the event sought to identify the bottlenecks in data management that limits banks to utilise the full potential of data and reimagine data management practices that are fit for the future. Hitachi Vantara’s Chief Solution Architect at Asia Pacific Seng Joo Lim opened the roundtable with a discussion on the evolution of data architecture over the years, fast-forwarding to today wherein a data lake house has been established. It is a new open data management architecture that combines the flexibility, cost efficiency, asset transactions, data warehouse, enabling business intelligence machine learning on the data. “What does the future hold?. Demand requires improved efficiency, reduced costs, and agility to data. We call it DataOps,” Lim said.

Right data, right time, right person

Lim observed that data ops has been going up the innovation trigger. DataOps has three key pillars: agility, governance, and operations. The purpose of the office is to streamline the whole flow from source to consumer and be more agile.

With banks having a lot of information and data to process, this raises the question of data protection. Lim mentioned that they can leverage on data catalogues, such as Lumada, or AI to automatically search and type such sensitive information. He added that the engineers for such solutions also increase the accuracy of protecting the correct data. Certain less sensitive data such as phone numbers are also masked for downstream consumption without any breach of customers’ personally identifiable information.

Data liberation in the industry

Meanwhile, CIMB Group’s Group Chief Technology & Data Officer Ros Yusoff shared her insights on how data can be leveraged responsibly. She said that over the years, CIMB has begun using data to have more of a 360-customer view, to increase product penetration, and improve cross-sale rate but for nothing other than better revenue uplift, which she noted as ‘quite typical of any financial institution.’ Through the data CIMB has collected, Ros said the bank is now able to do real-time triggers, such as financial transaction reminders and targeted campaigns. The bank has also embarked on digital personalisation to provide solutions that matches consumers’ behaviours. However, this poses a challenge of struggling to find good use cases when it comes to data. Whilst they have the platforms and the means to leverage data, they have to see as well if the data is usable.

“Coming up with good business, good cases that can be measured by linking it directly to revenue uplift, is an uphill battle, something that we have not figured out yet,” she said. Financial products and systems are added over a long period of time, having been developed with their own specific rules and specs.

‘Actionable insights’

For Ros, having that data quality can also be a problem, but there were bandages added for various reasons over time, which added to the complexity to get quality data across various systems.

She emphasised that the main reason data and processes need to be liberated is to increase banks’ ability to use the information to generate ‘actionable insights’ that could help organisations achieve their goal. However, it is also crucial for banks to act responsibly and minimise the risk of any misuse of data, in line with regulations and privacy laws. Lastly, Ros mentioned that data ethics is also a challenge for financial institutions.

Ros added that customers’ consent and transparency in collecting, storing and using data collected, followed by ensuring data subjects’ privacy, are key to banks.

Demand requires improved efficiency, reduced costs, and agility to data. We call it DataOps