How Financial Services Reap Rewards from Big Data

How Financial Services Reap Rewards from Big Data

When you think about it, banking customers are leaving a trail of data when they conduct financial transactions – deposit activity, recurring payments, purchasing behaviours, borrowing activities and even when they just shop for financial services. All customer interactions – whether it is a point of sale, a tap on the screen, or a keystroke – generate insights on purchasing behaviour, clicks, searches, likes, posts and other valuable information.

Data usage has made an important difference in the changing landscape within financial services and the emergence of FinTech companies. Here in the UK, regulatory changes like PSD2 have created a new era of Open Banking where bank customer data will begin to flow amongst financial services providers. With this, the operating model for the traditional financial services companies is changing.

There are new entrant FinTech companies which have shown the ability to access and make sense of data in new and creative ways. Some of these start-ups are giving incumbents a run for their money not because they’re generating or accessing more data, but because they’re looking at it differently and using it in new ways. When FinTech companies get clarity about the use of data, make sense of it, organise and cleanse it, combine traditional and non-traditional sources, they can out-manoeuvre and out-innovate the incumbents.

There are three Vs which are fundamental to the management of data: volume, variety, and velocity.

There are three Vs which are fundamental to the management of data: volume, variety, and velocity. Given the increasingly competitive environment, evolving customer expectations, and regulatory constraints, financial services providers are seeking new ways to leverage data and technology to gain efficiency and a competitive advantage. The adoption of Big Data and new data management strategies is redefining the competitive landscape of financial services and companies that don’t have a strategy run the risk of losing market share.

To address this situation, financial services companies are investing in new and modern data management strategies that address both enterprise data and their Big Data assets. This new data environment must act at the speed of business, offering real-time insights that are created using massive volumes of data. New data-driven innovations include analytical tools such as machine learning and predictive analytics. These capabilities connect and leverage data across their entire enterprise and outside partners.

With all the changes taking place, there are many challenges and opportunities. Based on our experience working with many of the largest global financial services companies, we have observed a lot of focus and investment in these three following areas:

  1. Creation of a Unified Financial Services Data Model.

This represents a standardised, multipurpose data model that creates a single, consistent view of the customer. This modern data environment is a business-driven data model that should serve all analytical requirements. It should also support all business domains such as marketing, risk management, product, customer experience, compliance, regulatory reporting, finance, and other functional areas.

It is critical that this environment is extensible and supports ongoing change. The activation of data that is stored must provide simple access for analytical applications as marketing, customer experience management, risk and other functions must respond in a real-time manner to create the desired customer experience or prevent fraud from occurring.

There are many other capabilities that can be delivered from this Unified Data environment. It is a foundational capability to address the rapid explosion of data, channels, devices, and applications.

2. While data collection is important, collecting more data is not always the answer. Ingesting the best sources and continuously testing them for accuracy and predictive capabilities is critical. New alternative sources of data are being created every day. While some of these sources can create some unique value, other sources may only add complexity to data management and cost without the desired return.

Deep mining of data can help predict needs and enable a much-improved customer experience. Improving the quality and accuracy of data that is collected, stored in the cloud, processed and analysed by artificial intelligence and deployed is important when creating new targeted offers and enhancing a customer experience.

Diligence in the areas of consumer privacy and security is and will continue to be paramount.

3. Diligence in the areas of consumer privacy and security is and will continue to be paramount. Consumer understanding of how their data is used often lags behind the pace of innovation, inspiring new demands from government agencies and consumer advocacy groups around the world. These factors compound the liability every financial services company faces when managing and activating consumer data.

Data security and privacy is an important issue and historically has been a strong point of differentiation for financial services companies, especially in light of the continued discussion around how Facebook and other social media companies manage data. There is and will always be an expectation that financial services companies remain a trusted guardian of data.

As financial services leaders realise that more trusted, connected and intelligent data contributes to their competitive position and survival, they now see data as an essential asset. This asset also requires investment to unlock value. Data should not be looked at as a driver of costs, but an important asset that will pay off handsomely for tomorrow’s financial services leaders.


About Scott Woepke

Scott Woepke is Head of Financial Services Strategy at global data, marketing and technology company Acxiom, where he leads a global team. He has over 30 years of hands-on experience in many facets of marketing, distribution, product, and technology strategy in the financial services and FinTech industries. His work includes working with many of the world’s largest financial services companies across retail/consumer banking, credit cards, investment services and payments.


Source link

How Financial Services Reap Rewards from Big Data
Scroll to top
error: Content is protected !!