Artificial intelligence (AI) within the financial services industry has been a hot topic of late, with experts and analysts far and wide predicting its revolutionary uses.

In the current economic ecosystem, AI-powered solutions are being harnessed in order to minimize operating expenses, assist with regulatory change management, provide better payment protection and directly address fraud risks, amongst other things.

Unlike any other technology, AI has the power to analyze mammoth amounts of data simultaneously, without the risk of human error. Used in different ways across FS, the general consensus among financial services professionals (83% of them) is that AI is vital for future success.

Fintechs are disrupting the industry and driving change and innovation by offering a customized, consumer-centric approach that goes above and beyond the capabilities of traditional institutions, simply by adopting AI technology. By choosing to invest in this exciting evolution, all organizations will be able to see how the broader context of AI adoption can provide tangible workplace transformation, revolutionizing stakeholder and consumer value.

In this article, I explore the current key uses of AI within the financial services industry, along with potential future uses and how both will be key contributors to continued success.

The present-day picture: AI in financial services

So, how is AI currently operating within the field of financial services? These eight areas have so far proven to be incredibly successful.

1. Regulatory change management

With AI, keeping compliant has never been easier. Automating the process of regulatory change means that non-compliance fines can be avoided. This is possible thanks to AI’s ability to detect patterns in vast amounts of text, forming a unique understanding of the regulatory environment’s shifting sands.

2. Better payment protection

Payment protection is paramount when it comes to keeping consumers safe and satisfied. With AI, financial firms can improve security and transparency throughout their system via identity verification, fraud detection and the regulatory requirements associated with Anti-Money Laundering (AML).

3. Better protection against fraud

Using AI to tackle fraud has been implemented extensively already — and will only become more prevalent. With the power to monitor things like transaction history and to identify anomalies that might indicate fraud including ATM attacks and money laundering, it just doesn’t make business sense to dismiss it.

4. Improving business operating models

As a direct result of AI, business models are able to evolve further. With everything becoming connected, businesses can collect more data, obtain insights and innovate. Thanks to AI, we can expect faster, leaner and more vibrant marketplaces.

5. Business advantage with better intelligence

The addition of AI makes for a more streamlined process. For example, it can help eliminate false positives in a more reliable format than with the margin for human error.

Conventional rule-based compliance alert systems are generating thousands of false positives each day. These flags are looked at by a compliance officer, which drives inefficiency and exposes the system to human error.

6. Improved automation

Voice agents, or virtual assistants, offer a dual benefit – not only do they harness the power of AI to assist customers, but they also free employees from recurring tasks, boosting productivity and personnel power.

7. Fewer human errors

Human errors cost regulated industries billions of dollars each year. There’s not one single area alone that consistently falls short due to human error, as it is affected by everything from inadequate or antiquated processes to obsolete technologies and negligence.

AI and machine-learning technologies can help identify these errors, spotting trends and patterns that even the well-trained human-eye can easily miss.

8. More personalized experiences for customers

Doing wonders for user experience (UX), AI-based personalization enables brands to boost consumer engagement, drive loyalty, improve sales and understand their target audience — and they can do this in real time.

Firms can even use AI to customize online content based on what it knows about a specific person. This level of customization naturally increases online conversions.

What does the future of AI in financial services look like?

The problems of today which we can look to solve with AI are mainly compliance problems. In 2021, the average fine value for AML-related compliance breaches was $34.4 million. This is despite the fact that implementing AI technologies allows firms to seek out money laundering patterns. By using AI to ground compliance into data, firms can future-proof themselves and avoid costly penalties.

There’s little doubt that this influx of unrivaled AI capability will impact people in back office jobs, and that some jobs may become obsolete. However, just as one door closes, another one is certain to open, as there will likely be a huge demand for coding and software development roles.

Recruitment can also learn from AI, with its impartiality and a complete lack of unconscious bias. For example, words like ‘support’ and ‘understanding’ have been revealed to target female candidates, while ‘competitive’ and ‘lead’ target male candidates, meaning each ad lost out on potentially 50% of candidates. AI-generated content will remove these words and keep things neutral, attracting more talent.

AI in action: Where is it successfully used today?

There are a plethora of examples of AI currently in action, with most existing in the sphere of anti-fraud algorithms. These include:

• American Express, which monitors every transaction on their platform in real-time using algorithms, for more than $1.2 trillion spent annually. Their AI integration can detect fraud and make decisions quite literally in milliseconds.

• Citibank uses AI to monitor consumer payments and keep fraud in check.

• The Bank of America has one of the best examples of an AI chatbot, named Erica, that can handle client requests such as card debt reduction and security updates.

• Many banks, such as Goldmann Sachs and Merrill Lynch, now use an AI-based search engine to determine market trends and conduct keyword research.

AI in the asset and wealth management industries

Specifically in the asset and wealth management industries, artificial intelligence is being used to determine stocks to hold and ones to sell – and it’s doing this far more efficiently than a human financial advisor could.

Using data-driven algorithms, AI can assess multiple factors – even thousands of factors – at the same time and extremely quickly, to determine a non-biased outcome while taking into account different levels of risk and ensuring regulatory compliance.

Although this may sound like jobs could be put at risk, I believe a more likely outcome will be that asset and wealth management firms will use AI to enhance the work their employees do. Skilled financial services advisors will be able to leverage AI to provide a better service, improve productivity, enhance cross-functional work and determine better outcomes for both your business and your clients.

Contact me if you’d like to find out more about recruiting AI-experienced leaders who can help drive innovation in your business.