This article will explore the role of data analytics in Fintech operations, as the disruptive innovation space continues to grow
Making use of data using a single view of all relevant assets, in real-time, has never been more vital, and for financial service institutions this is no different. Data-driven decisions, aided by analytics, are crucial in an ever-competitive landscape where consumers will look elsewhere if their needs aren’t met.
With this in mind, we explore the role that data analytics can play in Fintech operations.
The state of play
Historically, financial service companies have dealt with data in their own respective departments, leading to disconnected pictures of business progress and customer behaviour. In today’s business world though, organisations can’t afford to continue with this approach, and need a unified view to gain true insights.
Current market research projects the global financial analytics market to grow to $25.38 billion by 2028. While the role of analytics in Fintech-powered operations is becoming more prominent, complexities remain when it comes to gaining insights from rising amounts of data, which can be attributed to skills gaps plaguing tech generally. This can be mitigated by establishing strong partnerships with vendors such as cloud service providers (CSPs) such as AWS and Azure, which are continuously adapting analytics capabilities.
Processing rising data
To effectively process data in financial services, democratisation across the workforce is a must. No longer can assets afford to be kept solely with traditionally skilled IT personnel.
James Corcoran, senior vice-president of customer value at KX, explained: “Whether it’s seeking Alpha, managing risk, ensuring compliance or identifying fraud, the financial services sector has always been at the forefront of data analytics.
“The challenge facing financial services firms today is that there is simply too much data to process intuitively and without support. Insights are no longer visible; they must be mined and they must be mined quickly before either a problem occurs or an opportunity passes.
“Throw in the disruption brought about by the pandemic, an ever more complex regulatory environment and the relentless impact of digital transformation on the sector and it’s clear that the focus on data, its management and its analysis, has never been greater. At KX, we’re hearing a lot from financial services customers on the need to democratise access to data across an organisation, and the need for data to be viewed as an enterprise asset rather than through the lens of individual teams or domain-specific requirements.
“The consequences of not doing so are blatantly clear in too many organisations: the dreaded data silos that are costly to manage and hard to eliminate. The global datasphere is growing at an incredible rate, and much of that growth is coming from data created in real-time. Financial services firms must ensure their data analytics strategy can keep pace.”
Analytics is proving particularly fruitful in the open banking segment of Fintech. With open banking being all about portability of personal financial data, to offer consumers more personalised services, data science and analytics have a fundamental role to play
“It’s difficult to overstate just how important data analytics is in Fintech. Not only can it be the basis for a huge range of different business offerings it also plays a critical role in optimising and informing how companies operate,” said Alistair Dent, chief strategy officer at Profusion.
“Startups can differentiate themselves and gain a competitive edge by offering more creative and useful services. The only way to do this is to have a strong and innovative data science capability that can support development. Put simply, you cannot have AI-driven financial advisors or financial aggregation platforms without data analytics.
“Advances in data science and fintech are inextricably linked – they are driving each other forward. More creative fintech solutions require more complex data science techniques.”
Analytics at board level
Of course, no tech deployment project can drive that all important business value if board leadership isn’t involved in the vision. Once this is achieved, financial service boardrooms can use analytics to make data-driven decisions that affect the company bottom line.
“Once an IT issue, data should be at the heart of business models and strategies. Board level decisions need to be based on accurate insights rather than on approaches used in the past, which are not fit for purpose in the current environment,” explained Anurag Bhatia, senior vice-president and head of Europe at Mphasis.
“To harness innovation and monetise their data, the first step for leaders is to instil the right digital infrastructure to eliminate siloes and make quality data more accessible. Cloud is a strong enabler here, facilitating continuous innovation and opening the door for the use of advanced AI and machine learning capabilities for optimum data analytics.
“Once leaders gain full visibility of their data, not only can they use it to arrive at meaningful insights, but they can also more easily comply with a changing regulatory landscape – particularly when it comes to data protection, fraud prevention, and risk management.”
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