5 Cases of AI Applications in Financial Services

5 Cases of AI Applications in Financial Services

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Artificial intelligence (AI) is revolutionising how businesses interact with and deliver services to their customers. From groundbreaking new generative chatbots to automated task and project management solutions, AI tools are rapidly evolving and growing in use across industries, with the common goal of increasing efficiency and productivity in business.

According to Oxford Economics, AI could boost UK GDP by roughly £65 billion per annum by 2030. That is something that UK businesses cannot afford to ignore, especially as Accenture predicts increased spending on blockchain technology in the coming years.

The highly-competitive and regulated financial services industry is also experiencing rapid evolution. Many might wonder how AI tools can be leveraged in a sector with such heavy compliance requirements and high levels of risk. However, financial institutions can use these industry regulations to influence how technology is adopted within their companies, from deploying innovative, new solutions to automating time-consuming and repetitive tasks, such as eSignature solutions.

Financial companies can benefit hugely by leveraging AI technology, and this guide will explore how that’s possible, along with some top-level examples of processes that can be left to smart algorithms and machines, leaving experienced financial advisors and specialists to be more creative, strategic and intuitive.

Benefits of AI in Finance

Automating tasks in financial services with AI has the potential to save businesses millions every year. A study from Yell in 2022 found that annually, businesses could save roughly $35,000 in costs from AI. Not to mention the booming healthcare sector in the US which could see annual savings of $360 billion, according to McKinsey and Harvard researchers.

Below are just some of the most common advantages of AI in financial institutions, ranging from large-scale, international banks and fintech corporations to smaller, independent brokers, advisors and consultancy firms.

  • AI can reduce the need for repetitive, time-consuming work, allowing humans to tend to more strategic tasks.
  • AI can eliminate the need for excessive paper use, lowering companies’ carbon emissions.
  • AI can reduce the number of false positives and anomalies spotted in automatic detection processes.
  • AI can be entrusted to deliver website product description text and metadata, which can support a company’s online marketing efforts
  • AI can eliminate the risk of human error when collecting and aggregating data and delivering reports.
  • AI can allow companies to offer round-the-clock, 24/7 consumer interactions, and to more people dispersed across geographies and regions.

Of course, each use case will vary in influence and profitability with each business that adopts such technology. However, considering the growing consumer demand for the digitisation of financial products and services, financial companies are under increased pressure to increase their budget on technology to meet these standards. This, coupled with the regulatory and legal compliance boxes they must tick, makes this task quite difficult. 

However, the below examples should give you food for thought when considering how you can embrace AI within your company.

How Can AI Be Used in Financial Services?

Risk Assessment and Management

In banking and many other financial specialisms, AI and machine learning can help identify trends and identify risks. These tools can assess a person’s mortgage or loan suitability, as well as pinpoint industry and market trends to provide personalised and accurate investment options on the stock market. 

Many banks and lending apps are using AI/ML algorithms and real-time market data to continuously provide assessments and recommendations, simultaneously alerting companies of potential high-risk applicants.


Financial companies rely on the opinions and activities of existing investors and shareholders, but future trends and analyses can be conducted by algorithms. AI helps these financial companies secure tangible returns against market patterns which are influenced by real-time and past historical data. 

AI tools can then recommend solutions to satisfy the requirements of every investor based on their investment behaviour, alerting them of potentially falling markets and stocks which are attracting interest.

24/7 Customer Service

AI virtual assistants and chatbots can be a constant, round-the-clock point of contact for customers with general queries, meaning they do not have to wait to speak with an advisor. AI can therefore make companies more productive, responding to customer needs with minimal employee input. Human intervention is only required in the event of non-resolution.

However, that is not the only customer-facing function that can be left to AI tools. AI technology can be used to detect irregular patterns and risk areas during ‌due diligence and KYC (Know Your Customer) processes where human involvement is minimised.

Data and Document Automation

With more accounting companies opting to invest in digital solutions, the benefits of automation are a valid reason for doing so. AI tools have the power to scan identity documents and supporting material for the purposes of automating and streamlining the customer experience when, for example, applying for a loan or credit. AI technology can alert companies of anomalies and potentially forged documentation to allow them to mitigate potential risks as they relate to financial misuse and illegal activity, such as fraud and money laundering. 

For the most part, AI algorithms can be entrusted to analyse a person’s profile and documentation safely and efficiently. However, should potential red flags be spotted in an applicant, the company can be alerted promptly to take decisive action. It’s vital that companies fulfil their fraud and AML obligations.

Collection and Reconciliation

Banks and financial companies can use AI to resolve delinquency issues through efficient and proactive debt collection. Invoice capture technology can allow companies to automate their billing services, reminding clients and consumers to pay by the due date. This, in turn, allows businesses to improve their productivity, reducing the need for humans to manually chase for payment. 

AI can be adopted to reconcile accounts by analysing assets and liabilities for a company, as well, making accounting much more automated and error-free. 

The Future of AI in Finance

The world of artificial intelligence is booming and it’s likely that every sector or industry will begin to embrace it and witness its true potential in the coming years. With AI becoming more widespread, especially given the rise in digital transformation following Covid-19, AI is predicted to be nearly worth $2 billion by 2030, according to Statista.

However, despite the incredible potential, organisations must exercise care, consideration and prudence when utilising AI. Consider the appropriateness of the data that your tools will collate and dispense to you, and be mindful of how that will influence informed decision-making when it comes to customer profiling and credit scoring. 

It’s wise, at this present time, to ensure that trusted professional financial experts are casting watchful eyes over these tools, especially as it relates to a company’s legal and regulatory compliance. Misuse and misappropriation of customer data can have financial and reputational implications, which are hard to overcome, especially if your chosen AI tools end up causing GDPR breaches or the spread of misinformation. 

AI failures can still happen; algorithms can glitch and distort data. This is where companies will have to exercise accountability and transparency if AI makes an incorrect decision, before correcting that decision. Too much of this can affect consumer trust and faith in that company’s brand. We cannot become completely reliant on AI to replace human jobs with complete failsafe accuracy; however, it can certainly alleviate workers to take care of high-value responsibilities, so its benefits are hard to ignore. 

In summary, AI needs to be ethically and responsibly used in order to see its true benefits. We are well past the stage where AI is a ‘luxury worth pursuing’; it is now a ‘must-have’ but we as users need to practise constant observation to prevent it from becoming too influential and, dare we say, dangerous.

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Author Bio

Dakota Murphey is a Brighton-based, established freelance writer with experience in business growth and a strong interest in all things digital. Aside from her love of writing, she loves good times with family and friends and admits to being a bit of a film buff.