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The Trading Mesh

Can Big Data deliver a Big Future for banks?

Tue, 12 Dec 2017 22:45:00 GMT           

Banks have always collected and stored large volumes of data to inform their business decisions. Today, the scale and speed at which data is being created and interpreted might seem overwhelming, but for firms that harness big data it can provide critical competitive advantages.

Innovative firms throughout the industry are using advanced analytics tools to inform product and service development, reach new markets, and optimise processes and functions. For example, capital market institutions are using artificial intelligence (AI) and machine learning (ML) techniques to develop trading algorithms, and streamline and automate data-intensive processes, such as asset price trend analysis.

In retail banking, banks are using structured and unstructured data - including purchasing activity, social media interaction and feedback from digital applications - to understand their customer’s needs. While getting to know the customer is nothing new, big data can enable firms to create a more accurate – and increasingly real-time – picture of clients, enabling them to adapt and personalise services accordingly.

Big data, big challenges?

The potential benefits a firm can drive from big data techniques are clear, but it is worth remembering the scale involved in storing and processing the data. By 2021 there will be over 27 billion networked devices and connections, with annual global IP traffic reaching 3.3 zettabytes according to Cisco. While data generation isn’t a problem, the data then needs to be sorted, stored and analysed, often in real time.

Leveraging big data poses challenges to organisations of any scale. The need to run complex programmes across vast data lakes, often consuming great volumes of data at high speeds, requires access to substantial compute power at short notice. Secondly, national governments each have differing approaches to regulating the storage and use of personal data. Multinational enterprises can adopt technology that helps them comply with each country’s regulations and enable them to make lawful use of their data assets.

Lastly, the speed and volume at which data can enter corporate networks for analysis requires a new approach to cyber security protection, especially for highly regulated institutions such as banks. Traditional methods of securing the network through packet analysis at the entry point may not be sufficient.

Putting in place the building blocks for big data

One thing is clear: the old way of networking, based on proprietary data centres and corporate WANs, is not equipped to deal with big data. Banks need secure and cost-effective access to analytics software, virtual storage and high speed connectivity if they are to gain a competitive edge from big data.

The tools, techniques and virtual computing power for big data are typically hosted in the cloud. At Telstra, we are focusing on developing solutions and services that enable banks and other institutions to access these services wherever and whenever they need. We are quickly moving towards a model where firms are seamlessly integrated with a best-of-breed range of cloud service providers, SaaS tools, network resources and capabilities via a single secure, high performance connection. Our software-defined programmable network and cloud services help our customers handle heavy data loads and support fast processing times, while minimising data storage and compute costs. In this way, banks can gain access to the expertise and capabilities necessary for specific tasks through a single gateway. It makes it easy and cost-effective for banks to use big data to create a competitive edge.

Successful financial services firms have always owed much of their advantage to the ability to collate, manipulate and decipher data faster and more intelligently than their competition. The institutions that succeed by innovating off the back of big data are the ones that will get their underlying systems and structures right from the start.