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In the finance industry, Artificial Intelligence (AI) utilizes structured and unstructured data to improve the customer experience and customer engagement, identify irregularities, boost revenues, reduce cost structure, find certainty in patterns, and enhance predictability. AI is influencing the finance sector in several ways.
Firstly, the finance industry is brimming with data. One might expect the data to be embedded in large financial institutions’ hands, but a more significant part of the data is public, and because of the new EU payment directive (PSD2), bigger data sets are accessible to smaller companies also. AI can be effortlessly created and applied in the financial sector as the barriers to entry are lesser as compared to other industries.
Second, several underlying processes can be comparatively easier to be automated while numerous others can be enhanced by either force computation or speed. The finance sector indeed requires this kind of innovation the most. The industry is competitive and is continually looking for ways to generate revenue.
Third, the exchange of wealth across different generations makes AI extremely fruitful for the financial sector. AI requires innovative data and feedback to improve, and millennials are not only satisfied to utilize AI but are also less worried about security and sharing data.
However, there prevail challenges in the finance industry that restrict a smooth and quick implementation of AI. The hurdles can be in the form of data silos and legacy systems that do not interact with each other or bad data quality control. Lack of skill, absence of management vision, and lack of cultural attitude are also some of the factors that hinder the adoption of AI technology.