Data intelligence

  • Andrew Hutchings, Editor in Chief at Financial IT

  • 28.12.2021 03:30 pm
  • Huawei

It’s accelerating digital transformation everywhere – and financial companies take note.

Financial IT editors

For a financial institution, as is the case in global commerce more generally, digital transformation is a highly complex challenge.

The handling and transmission of information is being altered by massive trends such as the growth of the Cloud, the development of smart and autonomous systems, the arrival of big data and the opportunities from 5G communications networks.

New technology is not the only issue

Customers are becoming more sophisticated and demanding. Increasingly, payments are digital and good user experience (UX) is crucial to the retention of clients by a financial institution.

As banking services become more integrated with people’s lives, finance will – as industry guru Brett King notes – become less of a service and more of a behavior.  The consequence of this is a surge in banks’ need for scenario-based data applications .

Finally, it is worth noting that the competition from gigantic internet-based companies is - increasingly - being limited by anti-monopoly laws in a number of jurisdictions. This is, perhaps, the main trend that makes the challenge easier for a financial institution.

What is data intelligence?

At Huawei, we would argue that, if digital transformation is the challenge, the solution is data intelligence. 

Utilizing data intelligence requires banks and financial institutions to build data system with a central planning in two tracks: plan-driven and consumption-driven. The plan-driven approach builds unified data capabilities and brings all data into a central pool. Conversely, the consumption-driven approach supports business modelling and data services, enabling agile and real-time data capabilities.

Finally, and perhaps most importantly, data intelligence recognises that the boundaries between banking and other services are becoming very blurred. Whether the clients are shopping, travelling, socialising or consuming healthcare services, they are interacting with financial companies the whole time.

In short, business application scenarios and data assets are deeply integrated: with the right solutions, that banks and financial institutions should be able to discover more data value and improve core competitiveness.

Putting it all together

To make this happen, data is gathered from all parts of the organisation - whether customer facing or not – by Huawei’s solution in real time. Predetermined standards are applied to data collection, data aggregation, security/ governance and analysis.

Department silos, data inconsistency, and lack of on-demand agile data analysis are also common pain points. Traditionally, in many countries, banks’ data has been decentralised. It has only been possible for management to gather and use data after a credit risk event has taken place.

Working with Huawei, banks are able to react in a far more timely manner and to adjust their risk controls accordingly. Over time, the banks will be able to manage credit risks proactively - and across large and diversified portfolios of assets. Crucially, banks have the ability to see what action is needed by them across a range of potential scenarios.

To make all this possible, Huawei takes advantage of the opportunities from Cloud computing and from smart and autonomous systems.

Data intelligence in practice

In 2020, China CITIC Bank replaced its traditional data storage with Huawei’s high-end OceanStor Dorado all-flash storage system. This was an important step in China CITIC Bank’s   digital transformation. The OceanStor Dorado system improves data processing efficiency and shortens response times - enabling the bank to provide better service to its customers. The system also reduces operations and maintenance (O&M) risks. This is partly because the OceanStor Dorado system requires just 10% of the cabinet space of traditional data storage systems: energy and air-conditioning costs are 70% lower than those of traditional systems.

China CITIC Bank also chose Huawei's cloud data warehouse GaussDB as their data warehouse.  As of mid-2020, they have used it for almost a year. They found the average performance of the Product Data Management (PDM) layer had been improved by up by nine times. As for data applications, the average data supply time had been shortened by four hours.

As new business scenarios emerge from autonomous driving to intelligent coal mines and warehousing, the finance sector will need to harness data intelligence. In this way, banks and other institutions will be ready to support new business models, and to prepare for the next wave of digital transformation.



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