Banks, insurance, and asset management companies leverage data to meet imminent customer needs that keep changing with technological evolution. In other words, financial institutions are undergoing a paradigm shift thanks to the ever-expanding technology that has redefined delivery of financial services consumers. The transformation from traditional banking to fintech requires businesses to keep with the technology advancements to maintain a competitive edge in the industry.
However, it is also important to note that while most financial institutions recognize fintech as their digital future, there isn’t any well-laid roadmap that guides these institutions on how they can incorporate technology to bridge the gap between traditional banking and customer experience.
Research also shows that organizations with a robust data integration strategy are fast catching up, especially when these strategies are aligned to the organization’s objectives, goals, current assets, and financial capabilities. Remember, fintech is technologically driven, and it will continue to expand since there isn’t a definite endpoint for technological evolution and innovations. In that light, there are several factors that drive data integration in the fintech, which include but aren’t limited to the following:
Change in Customer Behavior and Expectations
The most valuable asset to any financial institution is its customers. Organizations are, therefore, forced to adapt to changing customer behavior and expectations. And to analyze that, organizations need to bring together customer data from different sources, integrate it, and evaluate the trends to come up with the best strategy to handle customers.
Stiff Competition in the Industry
Fintech companies are already employing data integration techniques to break data silos and offer exceptional financial services, creating stiff competition in the industry that bankers and other institutions strive to match. It is imperative for these organizations to leverage this technology to improve their services and solutions, if they want to remain relevant in market.
Using data integration organizations can not only improve their offerings, but also streamline internal processes and create a consolidated view of their enterprise data.
Cutting Operational Costs
Another factor that drives financial institutions to adapt data integration in the fintech is the need to cut on operational costs. Most financial sectors receive data from different sources, including customers, insurance providers, etc. To streamline internal operations, they need to bring together this data and generate insights.
But extracting data from different sources and integrating it manually is a time and resource intensive process. The alternate is adopting a data integration solution that can close the data-to-insight gap while simultaneously reducing operational costs and improving efficiency.
Pressure from Regulatory Bodies
Financial institutions are highly regulated by both national and international bodies to ensure that they maintain legal and reasonable fiscal policies, protect customer interests, and maintain a healthy economy. Otherwise, vices such as money laundering could flood some institutions.
In the past, most regulatory bodies demand that banks and other financial institutions should divulge more diverse and granular data to central banks or any other regulatory body. Failure to do so can attract penalties, which may include license suspension or revocation. Such pressure compels banks to collect more data in compliance with industry standards and employ solutions to generate automatic reports for ad-hoc inquiries by the regulators. These reports can also be used by stakeholders to make informed investment decisions.
When it comes to the banking industry, technology evolution is always dynamic and supports large amounts of data input. But with massive volume of data coming in, it is essential for businesses to integrate it in real-time to maintain a competitive edge over other players in the industry.
Similarly, the need for real-time data processing and evaluation has seen several technological advancements towards in the fintech sector, giving organizations investment opportunities. Today, investing in emerging technologies such as Artificial Intelligence (AI), the Internet of Things (IoT), and machine learning isn’t that expensive than it was a decade ago.
Data sets have also grown massively, and traditional practices cannot manage them in a timely and economical way. This updated technology aids in processing data in the form of events streaming (large volume in real-time). In-memory data storage is also used where organizations store giant data in Radom Access Memory (RAM) for distribution to multiple servers. Machine learning technology is also indispensable as it enables computers to learn without necessarily being programmed or invoking special software.
The above factors show how different organizations in the fintech industry are opening to data integration. Are you ready to implement data integration in your organization?