27 January 2020
Financial services institutions need to make sense of the vast amounts of data they sit on and drive meaningful outcomes. Photo: HKEJ
Financial services institutions need to make sense of the vast amounts of data they sit on and drive meaningful outcomes. Photo: HKEJ

FSI digital transformation: how to squeeze more value from data

The pressure from non-traditional financial services institutions (FSIs) is driving the whole financial ecosystem to digitally transform. To become data-driven enterprises, banks and insurance companies need to address three key data management trends: data volume, ubiquity, and user demands.

Mobile apps and devices generate massive volumes of data from the media, such as images, audio, and video. Combined with new business models and actors in the value chain that increase the digitalization of financial services, this new data provides enterprises with opportunities to gain additional insight and value.

Today, data is everywhere. And FSIs need to capture it all: customer information, financial transactions, product and service purchase histories, customer journeys, marketing campaigns, service inquiries, market feeds, social media streams, Internet of Things (IoT) streams, text messages (including emails and SMS), etc.

The industry is ever evolving, and new challenges are emerging. The race towards digital disruption continues alongside consumers’ growing demand for a seamless end-to-end experience, and FSIs need to keep innovating to stay relevant and thrive. The key enabler of this innovation is data. Specifically, FSIs need to make sense of the vast amounts of data they sit on and drive meaningful outcomes.

Big data cleaning – the first roadblock to innovation

FSIs collect structured data and use well-understood tools like data warehousing and numerical regression, but data cleaning (analyzing organizational data to make strategic decisions) remains time-consuming. The process often eats up precious days or weeks, keeping experts away from doing the actual work of data mining or modeling that is necessary to provide input to business strategy and decisions.

As it is, powerful artificial intelligence (AI) platforms and tools already require a hefty investment. But FSIs are beginning to realize that the costs and resources for keeping up with data cleaning can chalk up an even bigger bill over time. It is important to speed up the process of data cleaning with a data-centric architecture that can support heavy volumes and workloads with agility and flexibility.

Breaking data silos to get smarter

A study by Dresner Advisory Services has found that Asia Pacific clocks in at 44 percent for big data analytics adoption among organizations, the lowest in the world. This suggests that there are barriers in place that prevent organizations from getting more value from their data.

A likely culprit is data silos. Data silos are common within companies and departments, but the unique geographical diversity in the region has far-reaching implications in the way data is collected, moved and regulated. With more than one billion people having no access to formal financial services, Asia’s rural communities are largely unbanked or underbanked. Data collected from these communities, if any, may not always be updated or logged onto a centralized hub.

Regional FSIs may sit on huge data stores, but these often stay siloed within the confines of each country. The result is the lack of an enterprise-wide database, with data shared only at a city or country level. Data then becomes limited to the use of immediate tasks such as forecasting and reporting.

Like other modern organizations, FSIs need to access and share data in real time through a consolidated data hub to remain competitive. For these reasons, legacy platforms are increasingly being replaced by unified storage architectures that allow data to be accessed anytime, anywhere – whether on-premises or through the cloud. This lays the path for FSIs to enrich existing products and services and glean insights for a more cohesive organizational strategy.

The role of data in fostering innovation

With more FSI services going digital, industry players will focus more on creating a seamless end-to-end consumer experience to stay competitive. Whether it’s expanding financial inclusion through digital banking services or customizing solutions for the happily banked, having the right data infrastructure is the first step of the journey.

Some FSIs continue to work with lean IT teams, which are bogged down by day-to-day operations, and therefore spend an average of only 46 percent of their time on innovating. And now, by using AI algorithms to analyze data and make predictions and recommendations to users, some of these administrative tasks can be automated and accelerated. This can free the time for IT staff to focus their attention on higher value work.

Taking it a step further, FSIs can also make the best use of their data by fostering a culture of innovation. Given more time, IT teams can partner more closely with the business to understand the organization’s larger strategic objectives. At the same time, employees in other functions will also be able to shore up their data literacy, enabling them to innovate and respond more quickly to changing business needs.

To sum up, three of the barriers to FSI innovation include:

● Cleaning up big data;

● Data silos; and

● Onerous administrative tasks.

Where should we start? Build reserves, not walls

The prospect of building up digital reserves can appear costly and daunting, but the solution to a smooth digital transformation journey may be simpler than it appears. It starts with improving what FSIs already have, modernizing legacy infrastructure with progressive data architecture and solutions that enable flexibility and agility. By automating and optimizing infrastructural tasks, FSIs can leverage data more effectively, turn around workloads faster and experiment more than ever before. Focus on building digital reserves, not walls, as you embark on the journey to breaking down FSI innovation barriers with data.

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Country Manager, Hong Kong & Macau, Pure Storage