Why Banks Should Embrace Big Data and the Rise of Cognitive Banking

Christian Ball

Head of Retail-Atlantic Region at GFT

Christian spearheads of the GFT Retail offering. Christian joined GFT from Meniga in 2016, one of the top performing FinTech companies in Europe. His previous roles have seen him work with many of the leading banks to shape their digitisation strategies – including positions at Cap Gemini, Fiserv, and Accenture, where he led Business Development for Accenture Software globally.

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Why Banks Should Embrace Big Data and the Rise of Cognitive Banking

15.06.2017 08:15 am

If oil was thought to be the most valuable commodity at the beginning of the 20th Century, then data has now assumed a similar role in the post industrial age that is the 21st century. Customer experience is at the heart of the new banking model, and data is its most valuable commodity. Banks have always held vast amounts of data. The problem they have faced is that historically they have not been good at interpreting and extracting insight and value from it.  This situation is changing as financial services adjust to a new competitive environment in which the ability to identify value and insight from data becomes ever more critical.

Competition from challenger banks alongside new legislation is changing the bank business model. Regulators in the UK and in Europe want to increase competition in the market by pushing towards an ‘open banking’ model.

Open banking will require banks to share data that they have historically held exclusively, with consumers and third parties. Third parties can access this data by connecting directly to customer bank accounts via a standard Application Programming Interface (API). This access will allow third parties to build products on a bank’s infrastructure, enabling new services to be delivered and specifically tailored to the needs of different customers.

Open banking brings bank data, customer data and third party providers together and will radically transform the relationship between banks and their customers. With this development, banks need to reconsider how they create value – it will require banks to adopt a customer centric and data centric view on how they do business.  New businesses will be born on the promise of aggregated real time data analysis, customers controlling not only how they share their ‘financial selves’ but also assembling the financial relationships they want and need.

Banks must identify where the value case exists for insight from their data. Banks should begin with the customer experience both in terms of matching customer need, anticipating customer requirements, and improving communication to customers. This communication is not simply about selling more products, it includes the servicing experience that customers receive. Data is also helping banks streamline processes such as KYC (Know Your Customer) and underwriting that are benefiting customers.

Open Banking and regulations such as PSD2 has created an environment of permissive data sharing. This has increased the value of customer data. Customers can look forward to giving explicit permission for their own personal transaction data to be shared with third parties and to authorise payments direct from current accounts. This development is at the very heart of Open Banking. It is one of the drivers that are changing the dynamic of customer interaction with institutions and their ability to share information in real time and get real-time responses.

Moving from ‘Big Data’ to Fast Data’

Banks already possess vast amount of data but deriving greater value and insight requires the need for ‘Fast Data’. Big data as the term suggests describes large amounts of structured and unstructed data that require orchestration.The defining feature of fast data is the rapid gathering and analysis of data in real time. It is about the ability to consume, analyse and execute on the insight generated from multiple data sources.  The difference between big and fast data is in the accessibility and utilisation of the data to create value.

Open Banking has increased the opportunity for banks and other third parties to consume data in real time on a customer’s transaction history. They need to analyse and gain value from this data in a meaningful timeframe. This means in seconds and not days or weeks. Ultimately, fast data is about the ability to churn vast amounts of data quickly and derive insight. Unlike big data which focuses on storage, fast data takes a consumption orientated view of data. Fast data provides a richer context in terms of analysis and decisions making. This enables banks to provide added value to their customers; ultimately leading to an enhanced and more personalised customer service and experience.

 

Cognitive Banking

Improving the digital banking process involves embracing what can be termed cognitive banking. Cognitive banking should be viewed as an evolution. In the world of digitalisation and the digital economy, cognitive banking expresses all the digital banking requirements and more Cognitive banking is about having fast data, good User Experience and Interfaces (UX & UI) for customers. In addition it  includes automatic or robotic artificial intelligence, deployed in executing data quickly, accurately, cost effectively and predictably.

Not only do banks need to provide services in a digital way, part of the equation now involves reaching conclusions on the engagement strategy with their customer base either directly or indirectly on real time data from multiple data sources. This forms part of the cognitive banking process; it encompasses the analysis, processing and production of insights – new products and deeper more targeted customer value if you like.

Banks are working hard to apply this paradigm to establish new business opportunities by identifying how customers consume and are made aware of products. Decisions can be made on which additional services can be offered to secure customer loyalty along with understanding how banks should communicate specifically with individuals through applying more behavioural analytics to segmentation.

If banks apply greater machine learning and artificial intelligence techniques and technology, they can create a far more personalised, focused message. One that is targeted more effectively and with the added benefit of improving each customer’s appreciation of what their bank can do for them. The holy grail of marketing has traditionally been the customer segment of one because everyone is, in the end,an individual. We have yet to reach that point but banks are on a path towards becoming more accurate in identifying and understanding who their customers really are. Data is critical to this.

The competitive advantage that data brings to incumbents

In 2015, when speaking about digital transformation, the CEO of Spain’s largest banks BBVA, Francisco Gonzalez said that data was the most important competitive advantage that banks have. He said:

“Banks should become data-driven organisations in order to deliver knowledge banking: new and better financial products and services based on information and better suited to every customer’s needs and expectations.”

Faced with increased competition from challenger banks and fintechs, data provides incumbents with an inbuilt advantage that if harnessed successfully will help maintain their dominate position within given markets. They already possess large established customer bases and segments compared to challenger banks. With this presence, incumbents can extrapolate valuable data. This customer base gives incumbents insight which challenger banks do not have. In terms of data access, it is this which gives them a competitive edge over challenger banks.

In the era of Open Banking, the value incumbents can derive from data becomes more significant. How banks choose to consume and monetise their data is an open field. It becomes permissible for banks enable third parties to access segmentation information about their customer base which details consumer consumption behaviour. This permissive data which customers have agreed to share is an important development. The opportunity to sell insights based on segmentation knowledge is a value driver for incumbents which challenger banks do not have. This ability to sell insights to third parties presents potential new revenue streams for incumbents.

The relationship between banks and customers is being radically transformed through Open Banking, new technologies and increased market competition. What we see  are three main areas that banks are addressingto harness data;

Firstly, they must utilise data to better understand the customer experience. This involves identifying the most appropriate communication strategy and messaging in the right context for customers. Data provides an opportunity to obtain a much deeper knowledge and understanding of customers. This allows for a more personalised and insightful customer experience.

Secondly, banks need to know their segmentation. In an environment of fast data, banks can consume large quantities of data in real time. This helps drive a more accurate understanding of customers and the context in which they are operating in whether from a business or personal perspective. Fast data enables more insightful decisions based upon the greater number of factors that can now be considered real time, supporting accuracy of underwriting and the matching of need with solutions better.

Finally, banks must identify what value they can bring to their customers. This can involve better pricing and targeting of products and services from the bank to customer. Equally, with the advent of Open Banking, products and services can be provided through third party partnerships. Banks are no longer obliged to provide all services to their customers. Digitalisation and cognitive banking is about banks recognising where value can be created for their customer. In many cases added value will come from a third party and not from banks.

Exploiting the value of data involves banks bringing together many disparate elements of banking and financial services that meet the needs of customers. Those banks that can help manage and orchestrate these services will be successful as they can take value from their enhanced customer relationship. In order to be successful, banks need to have a clear understanding of their data estate, it must be built in a way that facilitates real time engagement, efficiently alongside an understanding of how they consume third party information. They must augment this data and understand how they derive insight.

Many banks have a long journey ahead before they reach this point but in understanding the true value of data they possess, they will be in a far stronger position to deal with the competitive opportunities they face in the Open Banking era.

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