The Role of Artificial Intelligence in Financial Services

The Role of Artificial Intelligence in Financial Services

Machine learning algorithms and other Artificial Intelligence (AI) technologies are changing the way we finance our lives. By automating tasks such as fraud and risk-management, machine learning helps organisations achieve their goals more efficiently, and also improve customer experience overall.

Artificial intelligence takes many forms, from reactive algorithms of systems such as IBM Deep Blue to sentient processes that we have yet to create. Consider a few of the top ways financial services industries are innovating:

Customer Experience

Perhaps more than ever, customer experience is crucial in business. It has become easier than ever for customers to abandon even the most trusted brands after just one or two experiences where their expectations were not met. Dealing with this new realisation, businesses are facing the challenge of ensuring they can reduce friction and offer proactive support at the point of interaction; this is where AI can truly help these businesses through automating standard processes, providing system data and information that can predict anomalies or issues, or deal with them at the point of service, to avoid escalation, and to provide greater efficiency in human agent resources.

Generative AI can help firms automate many elements of customer service, such as the repetitive and bureaucratic-yet-vital tasks of underwriting loans, processing and analysing data, preparing reports (eg, annual reports or operational performance updates). It can help employees, who are freed from logistical burdens, concentrate on matters of strategy. Generative AI, such as Convin, can scan feedback unceasingly for areas of improvement and keep services attuned to shifting demands.

Courtesy this truth, financial services firms can use hyper-personalisation to communicate directly with each person they meet, while sending tailored alerts about approaching bill payments, available investment opportunities or imminent credit card fraud alerts based on each individual’s unique needs.

Risk Management

Since it can review far more data than an employee can in the same timeframe, AI technologies are therefore instrumental in helping organisational risk managers identify operational risks before they occur, by flagging up odd patterns in otherwise large data sets, or detecting phishing attacks or viruses before they take place, thereby minimising financial loss.

The impact of AI will thus be to enable a financial organisation to anticipate changes in the economy by monitoring markets causing changes in the behaviour of consumers, and making adjustments while there is still time.

It can aid banks in meeting their regulatory obligations, by performing routine, time-consuming compliance checks, as well as extracting and gathering the data that is widely demanded by regulators to report on. This will result in fewer human errors, and speed help them meet regulatory deadlines.

Fraud Detection

Fraud and cyberattack avoidance – AI plays a key role here in assisting financial services to identify fraud. Machine Learning (ML) and Artificial Intelligence (AI) tools help to monitor incoming data against predefined rules, to look for patterns that flag potential fraudulent activity (or other similar cyberthreat or harmful activity) and, once detected, raise alerts to notify a team to investigate those instances of potentially suspect activity.

Banks and credit card companies stop another form of criminal activity, money laundering, by deploying their AI for the same purpose, recognising suspicious patterns of behaviour.

On the other hand, financial businesses need to be vigilant in how they implement AI. Poor data, or AI’s inability to grasp concepts such as ethics or philosophy, may render AI solutions impotent. They therefore need to establish a regulatory framework, and provide suitable training to their staff, ensuring that their tools can be used responsibly and in line with the law.


AI can help businesses in the financial services sector to get faster insights, faster responses and more predictive accuracy, lower operations costs and more delightful customer experiences – all while living within rigorous privacy and security protocols, and working within specific industry standards.

For instance, cyberattack prevention could be one of the first real-world applications of artificial intelligence in finance. Being able to monitor and track financial data quickly will allow organisations as well as individual customers to profile the digital world and ‘look’ for unusual behaviours. Algorithms can prevent time- and money-wasting relationships by identifying suspicious behaviours like breaches or risky transfers.

A chatbot powered by artificial intelligence can quickly analyse customer data and provide tailored recommendations, and even automate back-office functions such as document capture and compliance with know-your-customer rules. But unlike those flesh-and-blood employees, they never take sick days or vacations; instead, they stay online non-stop, freeing up time for more valuable activities – something that financial services companies that are contending with coronavirus infections and a shift in customer behaviour to digital channels need more than ever.

Rooney Carter

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