Big Data in Banking
Big Data in Banking

Big Data in Banking

In the past, we reviewed big data utilisation in the health sector, energy industry and start-up/SMEs. In this article, we are going to look at Big Data in Banking industry.

The banking industry has developed in its service delivery and technological innovation. Banking services is a critical component for the day to day activities as most transaction are undertaken through the banking sector. The number of customers served in the banking sector has increased exponentially. Each transaction in the banking sector amount to data creation and collection. The banking industry produces a large volume of data on a day to day activities. The adoption big data analytics of the generated data will revolutionise the banking sector at present and in the future.

Customer segmentation

The banking industry is entitled to a lot of personal information of their customers. The available information has a lot of potentials when utilised by the banking sector effectively. The banks currently can track customer transaction in real time. Through the available information, the bank can segment the customer based on different parameters such as net worth; customer preferred credit card among others. The segmentation of customer enables the bank to customised services and bundle packages that are deemed suitable for the different customer segments with high accuracies. Big data allows summarization of the available information into an actionable data that the bank can leverage.

The segmentation of customers has improved banking industry marketing sector. The bank can now develop a marketing strategy that is channelled to particular market niches. The customised marketing strategies have increased market reach in the banking sector and widened the customer base of banks.

Improvement of products and services

The bank can follow the conversation of clients on the digital platforms. The available information is used to determine the different needs of the customers and make them available to them in real time. Through evaluating the services offered by other banks, the company can be able to customise its services so that they are unique and gain competitive advantage. Most of the banks believe that leveraging Big data creates competitive advantage in the banking sector.

Operation efficiency

The banking industry is a fast growing industry with ever increasing expectation of customers. The volume of information gathered in the sector is enormous too and is expected to increase in the future. A significant amount of information is challenging to analyse and simplify in the absence of big data. Implementation of big data analytics ensures that the banking industry databases can store and process the information faster and safer for efficient use. The big data thus enabled improved efficiency through which the data of customers is handled.

The aim of many businesses is to lower the cost of operation and increase the business profitability. The big data adoption in the banking industry ensures the operation cost are reduced. This is through automation of most of the repetitive activities in the bank sector that lower the cost of undertaking such activities. The efficiency of operation is also improved through real-time analysis of information and integration across the bank platform and access to the information from all the bank branches.

Big data in the banking sector provides the bank with real-time information in all the operation levels of the company. There are many indicators put in place to monitor the banking operation. As such, a problem can easily be identifying even before it has a catastrophic effect on the bank operation. Big data analytics in banking helps in reducing technical error that impact on the customers.

Big data have been accredited with stimulating innovation. The banking operation succeeds on the basis of innovation which not only improves the efficiency of operation but also gives the banks a competitive advantage. The banking industry has adopted big data to come up with innovation to enhance operation such as the mobile banking.

Risk management

The banking sector is left vulnerable due to the large amount of information that it handles. Fraud is one of the major risks that banks face in its day to day operation. The big data enables monitoring of all the transaction. With increased availability of information, the banks can distinguish a genuine transaction from a fraudulent one, and this has drastically reduced the loses of the bank from fraudulent activities. This is though integrating all bank information in a central place that ensures the security of data.

Cyber security has been one of the major safety issues relating to information handled by banks. The big data provide the organisation with real-time information that is able to detect any security breach in its platform. The information available also enable the bank to identify any weak spots in its system, and a meant them before cyber criminals exploit them.

The financial market is now globalised due to technological innovation. A ripple of instability in any one economy can be felt across the globe similar to the 2008/9 financial crisis. The Big data provides the banking industry with the ability to evaluate all factors in the market that may impact their operation and be able to put contingency strategy to protect its operation and the interest of its customers and thus lowering risks.

Future of banking

The adoption of the big data in the banking industry has not yet been fully explored. The expenditure in big data analytics in the future is expected to increase as more and more banks fully adopt big data analytics. There is expected to be more innovation and big data techniques in the banking industry. Banks will have to select the most effective technique that will transform its operation. The phase of the banking industry will change when the industry fully adopts the broad application of the big data.

The customer experience is expected to change in the future. The efficiency of bank operation, real-time sharing of information, linking to bank industry to other industry and automation of some function will greatly improve service delivery and customer satisfaction in the banking industry. For sure the future of the banking industry relies on big data analytics.

Looking to implement Big Data Analytics related use cases at your organization? Do reach out to me at nikunj@dataone.io. I’ll be happy to discuss and collaborate further.

Originally published at: https://blog.dataone.io/big-data-in-banking-2ae1bbc782c8 

frappier yseult

J'aime aider ceux qui sont dans le besoin c'est sa ma joie de vivre

7y

Je suis un financier particulier qui offre des prêts à des personnes de bon moralité et responsable.Si vous êtes intéressé veuillez me contacter par mail: raymond.nicolasyaves@gmail.com

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Axel Winter

CEO | CTO | VC Partner | Retail & FinTech

7y

Not sure I would agree that Big Data in banking hasn't been fully explored. Could individual banks do more? Yes! Are banks in general investing heavily in "Big Data" yes they are. For the region I think my team started over 3 years ago with heavy investments into the Hadoop environment and are probably are in the leadership group - what we do and the bank wide completeness. Yet, I have talked to many Technology teams of Banks and every single one has invested people and effort here. To my feeling better than many other industries. Many banks have _not_ made the mistake of leaving big data to just vendors and outsource staff, but have recognized the importance of building in-house skills and staying closer to the open source frameworks.

Márcio Alexandre

Serviços Financeiros | Cooperativismo Financeiro | Arquitetura Empresarial | Governança de TI | Conselheiro do Open Finance Brasil

7y

Thanks for sharing Renato Guimarães

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Saurov Ghosh

Buy-side| Sell-side| Investment Banking| Hedge FundI QuantI Wealth| Asset Management| Market Data| Reference Data| SaaS| FinTech| Data Feeds| Account Management| Customer SuccessI BullionI Strategic Sourcing

7y

nice, thanks for the post. Unfortunately, purely from South Asian & SE Asian context, most C level are non-adaptive and unclear about big data and not in sync with technology and blend of tech with banking. In most C level meetings, they speak about "our vision is to serve and under stand our customers better using big data - so tell me, how can you help us?" - that's it - what ever you say & explain & draw, there is good old nod of the head and nothing more in form of ownership, innovation, change, new process, execution or implementation. You get past it, they bring you down to "how can I reduce the cost?" & "how can I get more business - am spending so much - you see, our stakeholders will ask - where is the ROI?" - excellent questions, thank you very much for your time.

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Tom Ward

Sr. Economist / Innovation Advisor at Int'l Dev - on social media as a private citizen. 18k+

7y
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