From internal operations to external transactions, there are many areas throughout the financial industry that can be improved with the use of data intelligence.
Data intelligence is making a strong impact in terms of cost savings and customer service in the financial services industry.
From internal operations to external transactions, there are many areas throughout the financial industry that can be improved with the use of data intelligence.
Technology has been instrumental in advancements in the financial services industry for many years. The use of automated teller machines and online banking are examples of that. But as data intelligence expands, financial institutions can now get a handle on things like safety and privacy, better customer service and error detection.
Fraud has long been a thorn in the side for those in the banking industry as it brings along with it a high cost to the institution.
But with well-integrated data intelligence, those in the financial services can detect and address fraud more efficiently and effectively. In fact, Forbes reported that by 2030, the use of data intelligence, including Artificial Intelligence (AI) and Machine Learning (ML), is expected to save the banking industry $1 trillion.
AI not only provides more customer service opportunities to clients outside of what would have been normal business hours, but it serves a host of other benefits as well. The data technology can analyze the habits of customers, allowing the institution to use that data to develop financial moves and offer advice based on the information.
Human mistakes are unavoidable, but technology’s ability to find those mistakes is indispensable. Especially when money or health is involved.
In terms of the financial market and investment sector, data intelligence is also paving a way for more efficient and accurate decision-making. The combination of AI and ML leads to data analysis that enables faster decisions about transactions.
Data experts can use mathematical modeling when analyzing both structured and unstructured data in real-time to help clients strategize their next financial move.
Regardless of the industry, data intelligence is performed by the use of certain technologies that are customized for each unique situation. These technologies are housed under the roof of Big Data.
Big data, or the large amount of information that is collected from areas such as billing statements, social media usage and online search habits, is composed of three workflows:
AI and ML fall within the Analysis tool, or data analytics. With the use of these technologies, experts are able to build processes such as cloud frameworks that house the data in one central location and make it more easily accessible.
Another crucial technology that data scientists use to help in a wide variety of industries is Application Programming Interface (API).
An API interface allows a company’s applications to share their data with other devices internally or externally. An example of an internal API could be employees accessing patient information in a portal. In an external API, customers can make a payment using a third-party platform such as PayPal.
Data intelligence is proving to be a game changer for entities in the financial services industry.
Whether these companies are looking for ways to improve their internal operations or handle more effectively their external transactions, the use of integrated technology is elevating service in several areas.
