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By 29 June 2022 | Categories: feature articles

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By Takalane Khashane, Managing Director, Iron Mountain South Africa

It is predicted that the amount of digital data created over the next five years will be greater than twice the amount of data created since the advent of digital storage. The IDC’s Worldwide Global DataSphere Forecast estimates that 200 exabytes of data is generated worldwide which equates to 1.1 gigabytes per person per hour. In South Africa, average traffic per capita per month has increased from 6.5GB in 2016 to 18.6 GB in 2021.

As an unprecedented amount of big data – characterised by high volume, high velocity or high variety –  is created and collected, between 60% and 72% of data remains unused for analysis becoming dark data. According to Gartner, dark data is the information assets organisations collect, process and store during regular business activities, but generally fail to use for other purposes. Often, it is retained for compliance purposes only. However, this is not so in the financial services sector as the organisations are leaning more toward data and are actively using it to offer services to their customers.

The growth of big data in financial services

Technological advancements throughout the ages have had a major impact on the accumulation of data in financial services. Starting with the introduction and widespread use of the credit card in the 1950s, which allowed consumers not to carry cash and make purchases on credit to pay off at a future date. In the 1960s, ATMs were introduced which liberated people from waiting in long queues and only withdrawing money during bank hours.

Additionally, the use of computers banks and having a centralised platform for accounts allowed the streamlining of processes and for banks to focus on enhancing customer services. As the years went by, online banking - referring to the use of a terminal, keyboard and TV screens to access banking services – was introduced in the 1980s. The arrival of wireless technologies in the early 2000s saw the introduction and mass adoption of mobile banking services. In the 2020s, the Covid-19 pandemic accelerated the digital transformation journeys of the industry, and entrenched emerging technologies like AI, hybrid-cloud, machine learning, etc. These technological touch points have allowed banks to continuously analyse and store all information from traditional and digital sources, creating a data trail of each client.

Today, big data is the cornerstone for the banking industry and financial services sectors as a whole. This is due to consumer demands and expectations shifting towards convenience, relevance and ease. Consumers are looking for hyper-personalised and relevant communication from both online and offline interactions. They want their financial institutions to update them about their finances and notify them if there’s something that needs their attention at the right time and moment without initiating contact.

Through the accumulation and access of big data, financial institutions are prime positioned to help customers make well-informed financial decisions. Banks can use AI-powered apps and services to tap into that data and offer customers advice on financial literacy, spending, saving, and investment based on customer profiles or personalised requests. For example, through predictive analytics, bank apps can send notifications to customers alerting them if they will overspend for the month based on their spending patterns.

Besides personalised services, big data also presents many benefits for the banking sector such as faster innovation cycles, more informed financial advice, and major cost savings across the value chain.

Challenges posed by big data for the financial sector

However, big data also poses some serious challenges to the finance sector. Customers are becoming increasingly wary about how their data is collected and when it is used.  Research by the Internet Society and Consumers International has found that 69% of consumers are concerned about how personal data is collected in mobile apps – the primary source of internet connection for South Africans and the rest of the continent. The fact that there could be as many as 30 billion connected devices on the planet by 2027 also comes with stark warnings from privacy advocates about privacy and security for customers.

Areas where big data analytics is helping financial services

Despite these challenges, the future of data in the financial services sector is a promising one that firms can leverage to the benefit of their customers, the environment, and society as a whole.

In sales and marketing, big data can dramatically improve the efficiency of routine sales and marketing processes by offering a comprehensive view of the entire customer lifecycle from acquisition to activation to cultivation.

For customer experience and support, big data can help firms become more customer-centric by providing a full view of the history of inquiries and transactions from a particular customer. With regards to risk management and mitigation, data analytics is being used to manage supply chains, customer relationships, and employees to automate the approvals for products such as small loans.

As data innovations continue, more traditionally laborious processes will become automated. The banks are also leaning on big data to bolster security for both customers and organisations. A Danish bank, Dankse Bank, struggled to mitigate fraud by using legacy detection systems and had a low detection rate of 40% with a 99.5% rate of false positives. They adopted machine learning and AI to fight fraud. The result was a 50% increase in fraud detection and a 60% decrease in the false-positive rate.

In product research and development, financial services can tap into the potential of big data to deliver new products and services, as well as improve the way they deliver value. By using insights derived from a wider range of data streams, it will be possible to power everything from better algorithmic trading to personalized wealth management advice and financial management. For offering integrated financial services, banks can use big data to offer banking-as-a-service options to their clients as the sector is seeing the rise of open banking and moving towards bank 4.0.

Conclusion

Data is one of the most abundant resources of all, and financial institutions are applying this technology better understand customer needs, offer personalised services and make accurate decisions. They are also using it to be more efficient and respond to market demands to ensure business continuity and resiliency. Thanks to the mainstreaming of advanced digital technologies to tap into data, the future of the financial service sector is dynamic and exciting.

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