From embracing robo-advisers, to drones helping assess insurance claims and Australia’s major banks scrapping ATM fees, the banking and financial services industry is currently in the process of immense change.
In response to this disruption and changing customer expectations, businesses in this sector have realised that in order to thrive in a constantly evolving market, they need to be able to improve their operational efficiencies, detect fraud quicker and more accurately, model and manage their risk, and reduce customer churn.
All the while, financial data from consumers remains at the epicentre of the financial services industry, and the need to protect, store, and leverage this data correctly is of increasing importance. Last year, Australian Treasurer Scott Morrison has ordered a review into ‘open banking’ – the act of allowing consumers to securely and easily share their financial data with trusted parties such as banks, financial technology firms, or even technology giants such as Facebook.
As a result, big data, machine learning, and advanced analytics have set themselves up as major forces in keeping financial services businesses competitive and protecting the sensitive data within the industry.
Be on guard – all the time
The banking and financial services industry is one where any threat of attack, cyber or anywise, can devastate the entire industry. In 2016, banks across Australia were targeted by malware which allowed hackers access to the online banking login credentials of thousands of customers.
In response to crises like the above, banks and other financial institutions have been working tirelessly to avoid similar situations from occurring again.
Applying machine learning frameworks that can engage data from various sources enable businesses to flag irregular activities in real-time, preventing any potential security attacks or fraud from taking place. Acting on data “as it occurs” is a critical advantage that can help financial institutions stay ahead of criminals. With a converged data platform, analysis on both operational and analytical data can be used to anticipate attacks and proactively prevent them.
Stop casting a wide net and be targeted
The analysis of data will also provide financial institutions the ability to create more meaningful marketing efforts by using data to identify and target segments.
Businesses in the financial services sector will be able to understand customers on a more micro level and offer relevant, personalised and contextual communications through leveraging data. By using data to target specific segments of the market, a brand’s message will resonate, thereby boosting conversion rates, customer share and lifetime value. Unlike legacy tools, a big data platform will allow this segmentation to take place much quicker and more efficiently – ensuring that no resources are wasted.
Leveraging customer data means businesses in the sector are able to increase customer segmentation specifically by analysing customer activities, transactions and behaviour patterns across all channels. This understanding will also aid companies in predicting consumer purchase behaviour to offer customers the most relevant and appealing products to influence their purchasing behaviours.
Optimise customer experience (CX) and keep your customers loyal
One of the biggest changes in the digital age relates to customer service and customer interactions. Nowadays, banks and other businesses in the financial services sector don’t actually need to see or physically deal with customers. As a result, it is more important than ever that businesses have a deep understanding of their customers to ensure customer satisfaction.
Customer experience has never been so prized by businesses wanting to be a step ahead of their competitors. Personalisation has become a key focus for businesses in all industries and as such data from customers is to give businesses a 360-degree view of their customers. Technology is the key to unlocking this view. For example, National Australia Bank recently announced that they will be rolling out ‘virtual bankers’ to personally interact with their business bankers. This will allow banks even greater access to the preferences of their customers and let banks and other financial institutions foster a sense of loyalty in them.
By having a singular platform for analytics that combines data exploration and governance as well as access, integration and storage scalability, businesses will be able to effectively draw insights from this large amount of data to drive revenue. Furthermore, this deeper insight into customers and the resulting improved customer experience will increase customer retention.
Big data analytics will bring about monumental change in value generation for the financial services industry. In order to be a winning business in this sector, data must be used for businesses to make the crucial shift from a product-centric focus to a customer-centric focus.
Organisations must act now and use big data in technology, marketing and cybersecurity strategies to evolve the relationships with their customers, transform data into an asset, and stay ahead of their competitors.