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Business analytics: shaping financial services

Posted on February 2017

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​​An ever-increasing amount of data comes into businesses in enormous volumes, in different forms and at a range of velocities. As a result; companies are investing more time and money into analytics. By gaining greater data insight they are not only able to enhance cybersecurity and reduce customer turnover, they are also well-placed to create a more personalized customer experience, boost customer loyalty and present innovative offerings to those customers.

Data management and analytics were key issues for financial institutions in 2016; this will increase in 2017. Spurred on by new regulations, as well as pressure from customers and investors, data (specifically Big Data) is driving the future of the Financial Services sector.

Growth in the analytics market

As the sector continues to embrace big data and analytics, businesses can manage information flow and use insights for problem solving. As big data technologies take center stage, the sector is also benefiting from a boost in risk management and targeted marketing. If the current trend for investment in big data analytics continues the global market will generate an estimated $2.41 billion in revenue between now and 2020.

Driving the analytics market

It is widely recognized that financial, insurance and banking organizations are some of the most fiercely data-driven industries within business. These companies depend on technology and merchants that can withstand the enormous data load and analytics.

According to Market Research Hub, the three primary drivers within the market are:

  • Exponential growth in data and portfolio risk solutions

  • Growing requisite to fulfil regulatory requirements

  • The need for greater efficiency and productivity

This growth of data and portfolio risk solutions means an increased reliance upon the use of analytics and risk compliance solutions. A report by the IDC found that analytics investment within banking will focus as much on security and compliance as on customer insights.

Of course, with more data comes more digital devices and in response to this, businesses will need to turn their attention to the issues of data privacy and data security. Both are vital to the industry, but both present a market challenge.

Innovation is key

One of the more innovative ways financial institutions can maximize their use of big data is through social media. Social media marketing and collaboration are becoming widely used within the sector. An increasing number of banks are utilising platforms to collect customer feedback, offer product updates, provide real-time answers and boost insight generation. By linking unstructured social media comments with structured customer feedback, businesses are beginning to create a more comprehensive customer profile.

Attracting analytics talent in 2017

Analytics has seen an incredible rise over the past few years where investment continues to grow as industries recognize the importance of being more data-driven.

However, data is useless without the skills to process and analyze it. Unsurprisingly, analytics talent is becoming increasingly sought-after; a survey by Talend revealed that a lack of in-house skills is one of the biggest barriers to adoption of big data in banking, with 28% citing it as the main obstacle to realizing the benefits of big data analytics.

Over the coming year, businesses will be keen to secure the best talent, with the sort after skills sets being: 

  • Data/Business Analysts and Managers 

  • Data Scientists

  • Business Intelligence Professionals

Businesses want to be able to make the right decisions at the right time and these are the roles that can enable that to happen.

Will demand outweigh supply of talent? 

Analytics roles require a high level of particular expertise; while the supply of talent is certainly growing, demand is accelerating exponentially. This may mean frustration for the companies looking to hire analytics talent, but it also means plenty of opportunities for candidates who have the right experience, for example:

  • Master’s degree in statistics, Mathematics and Computer Science

  • Knowledge of R and Python programming languages



Mean Salary ($)

Salary Range ($)

Entry Level Data Analyst


$70,000 – $105,000

Experienced Data Analyst


$95 000 – $160,000

Generalist Data Engineer


$100,000 – $165,000

Data Engineer - Subject Matter Expert


$140,000 – $240,000

Data Scientist


$120,000 – $250,000

Analytics Managers (VP’s)


$130,000 – $200,000

Senior Vice President


$185,000 – $250,000

Director / Executive Director


$230,000 – $350,000

What does this mean for data science and data technology professionals? 

If you have the skills to be a key player in enabling a company’s big data initiative, now is the opportune moment to make your move. An increasing number of institutions are looking to build robust analytics teams, offering all the security and benefits that permanent positions provide. As such, this has evolved into a heavily candidate-driven market with many contractors now considering a move in-house.


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