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What is the impact of AI in the banking sector? First of all, it helps financial institutions get on a completely new level regarding customer experience. Secondly, it may be utilized to improve cybersecurity and fraud detection. Thirdly, it comes with a new level of personalization. Finally, AI impacts banking by reducing operational costs, along with increasing the ROI on marketing and customer acquisition. Do you want to learn more? Then read on.
Table of Contents
The Impact of AI in Banking
The best way to understand the impact of AI in the banking sector is to analyze the benefits that come with this technology. Therefore, let’s review them now.
Finances
To begin with, we shall take a look at the financial impact of AI in the banking sector. It is quite multidimensional so let’s look from every possible perspective.
Firstly, let’s look at the reduction in customer acquisition costs. Here, we need to consider the use of AI in banking for the sake of customer onboarding. Artificial intelligence, along with biometric technology, is utilized to accelerate the process and make it less strenuous, actively reducing abandonment rates. This way, you can increase your marketing (and sales) ROI by turning more leads into clients. Its impact is perfectly depicted by the case study of SGB – a bank which we implemented an eKYC solution for that will pay off in just three years!
Secondly, we need to consider your operational costs. Take, for instance, your customer support agents. When aided by AI, they can navigate through your financial institution’s regulations more efficiently, hence solving more queries. This results in a lower demand for CS agents, which translates directly into savings.
Thirdly, there are intelligent product recommendations. AI-based solutions, like those prepared by us at Ailleron, can provide your agents with smart sales suggestions based on customer data, hence boosting your sales and providing a steadier income stream to your organization.
Finally, AI also impacts the financial side of the banking sector by improving overall decision-making. NLP models can improve fraud detection, consumer segmentation, and even data processing and security, decreasing the costs required to do this manually.
Security
When discussing the impact of AI on banking, we must mention the way it affects security. This can sometimes be a double-edged sword, though in most cases, artificial intelligence does improve general data and financial security significantly.
The first instance of AI being used for this sake can be seen in fraud detection. Artificial intelligence, when trained on proper data, can spot anomalies indicating shady transactions or activities on your customer’s accounts, hence helping you detect them and prevent them more quickly. This is especially important when you consider the large financial fees that may be imposed on your institution for insufficient anti-fraud measures.
Secondly, artificial intelligence itself can help you protect your data. When trained for this purpose, it is capable of detecting potential cyberattack attempts and alerting your teams about potential breaches. This way, you can react more quickly and gather customer trust, so important when it comes to acquiring new clients.
Why did we say that it’s a double-edged sword if it is so beneficial? Unfortunately, AI itself may become a target and be fed with toxic data to disrupt your operations. Therefore, you need to ensure the security of your models first, and only then can you use them to boost the security of your data.
Loan Decisions
The impact of AI may also be felt in other banking and financial sectors, namely loans. The organizations specializing in them frequently use AI-ML systems to automate their loan decision-making processes and make it more thorough by analyzing additional data, such as transaction history, or detecting fraud (as mentioned before). Yet, this is an approach that is quite risky.
While, in theory, such systems can be quite beneficial and do a day’s work in a matter of seconds, in practice, you really need to consider how to implement such AI in your business. Any bias in the data may have far-reaching consequences; hence, it is critical that you engineer your data thoroughly, and even then, it might be impossible to fully get rid of it. Therefore, while such a solution can be beneficial, it will only be so if you use it with caution – for instance, to analyze additional information that would not be taken into account otherwise.
But on the other hand, there are many institutions that use AI for such purposes, so it is definitely impacting this area of banking already and it should do so in the future.
Risk Management
When it comes to decision-making, loans are not the only area impacted by AI in the banking sector. Another major shift can be observed in general risk management, where artificial intelligence is used to predict the…unpredictable.
For example, such systems are used to analyze currency fluctuations, or even predict the consequences of natural disasters. This way, financial institutions can make better-informed decisions and mitigate risks related to external factors.
Sustainability
Whether AI is sustainable or not is a matter of discussion, but it can definitely help banks become “greener.” How exactly does it work?
With the new EU regulations, banks are obliged to classify their transactions (and publish them) based on whether they are eco-friendly or not. This requires major data processing capabilities – ones that AI has.
With AI-powered systems, it is possible for the banks to process the information acquired from their commercial customers and define which deals are indeed “green” and which aren’t, helping banks become more sustainable and remain compliant with the EU legislation.
Customer Experience and Satisfaction
AI also impacts the general customer experience and satisfaction in the banking sector. Like financial benefits, this is multi-dimensional.
Firstly, due to its data-processing capabilities, AI reduces the time required for most processes, leading to shorter turnaround times and happier customers. This refers to anything from customer service (due to the use of chatbots) to loan decisions (as mentioned before).
Secondly, AI makes the processes easier and more convenient, especially for customers in the digital-only or mobile-only segments. Intelligent eKYC processes, videobots, and widely accessible chat support (often powered with AI) help customers get their business done without leaving home, which is crucial for many younger consumers.
Thirdly, AI enables high-level personalization. This means providing customers with intelligent product recommendations, but also tailored content that is in line with their priorities and expectations, hence building loyalty and satisfaction. Solutions such as AI Prompter can provide tailored answers to customers’ questions much faster than traditional ways of communication.
Finally, it’s possible to use artificial intelligence for additional services that build customer loyalty. Take, for instance, our ai-powered transaction classification solution for a major Polish bank. With our ML model, we were able to classify 92% of the transactions accurately, which enabled our client to better understand their customers’ needs and provide them with more adequate recommendations, hence increasing customer satisfaction.
Conclusions
The impact of AI in the banking sector can be observed in almost every aspect of financial institutions’ operations. From reducing costs, automatic document processing and boosting profits to strengthening security, supporting decision-making, and delivering tailored customer experiences – artificial intelligence already helps with all of that. Therefore, we recommend that you implement AI as soon as possible. Do you feel that you need help? Contact us – we are more than happy to design, train and implement a cutting edge AI model for you!
You might also read: Big Data in the Banking and Financial Services sector: use cases and challenges
