5 Ways How AI Can Benefit Financial Services

ai in financial services

AI – or Artificial Intelligence – tends to be associated with innovation and entertainment rather than with long-established institutions that seem to have been functioning perfectly well without it. The role of AI in financial services might therefore still be unclear, though many financial institutions are beginning to see its potential. Artificial Intelligence indeed provides major opportunities in terms of client offerings, big data, compliance, security and more. Improved customer engagement and new sales avenues are some of the advantages that derive from implementing AI-based recommendations.

Big Data

ai in financial servicesData collection is not something the financial world is new to. Several aspects of customer behaviour are significant to the industry and help to determine pricing models, for instance. In recent years, however, big data has become even more important as is now monetizable in and of itself. Integrating AI in financial services – especially in the form of explainable AI where human experts can interact with the solutions directly – is particularly relevant. AI specialists such as Dreamquark.com offer highly scalable solutions which collect, extract and interpret pertinent information, including:

Product demand and how it influences the popularity of other products

Customer location and how it impacts their choices

Price comparison and fluctuations

Highly precise trading patterns

Relative costs of various commodities

Open exchange price volatility

Risk Management

The importance of AI in financial services goes well beyond its usefulness in trend analysis. Instead, as artificial intelligence handles enormous amounts of data in a very short time, it can be configured to analyse past issues financial institutions have faced and to identify potential risks before they materialise. Such accurate forecasts make AI a powerful fintech ally to examine the consequences of critical decisions.

Customer Experience

AI in financial services plays a part in regulatory and compliance tasks, where its algorithms have a tangible impact. They are indeed able to guarantee higher levels of transparency than more traditional methods and simplify the process of wiping personally identifying information from the data used and stored by actors of the financial sector.

Artificial intelligence also provides better account protection by detecting any irregularities more rapidly. More demanding compliance standards directly benefit the customers who can rest assured their assets are in good hands thanks to an effective fraud detection system.

AI in financial services also improves customer support, for instance by reducing wait time thanks to chatbots, giving clients relevant answers to their queries immediately.

The integration of AI in financial services offers customised investment recommendations and delivers intelligence straight to the customers who can feel more confident in their financial decisions. Thanks to efficient, convenient and secure services, banks achieve better customer loyalty.

Financial Crime

As much as it impacts the customer as explained above, financial crime weighs heavily on the industry as a whole. Fraud is an especially challenging issue to monitor for human experts who process thousands of false alerts each day while still missing actual threats. AI in financial services can take the form of real-time fraud identification solutions and reduce the occurrence of false positives thanks to machine learning.


AI naturally lends itself to data-driven investments as it is capable of monitoring both unstructured (news, social media, etc.) and structured (spreadsheets, databases, etc.) data at an incredible speed. This allows for more accurate predictions for stock performance and stronger recommendations which can be tailored to suit short-term or long-term goals. Thanks to artificial intelligence, traders have efficient financial tools at their disposal to manage their portfolios seamlessly. This enables them to make informed decisions more quickly and to achieve faster, more numerous transactions.

Explainable deep learning has the potential to generate new revenues, to provide better investment guidance and to reduce losses significantly, making it an invaluable asset for the financial world.

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