The use of artificial intelligence (AI) is not new in the banking and financial services industry. Fintechs have been exploring the technology, using it to create chatbots, personalised financial services and data analysis before AI went mainstream with the launch of ChatGPT.

AI in finance revolves around creating intelligent machines to help deliver better financial services to customers or to smoothen operating processes for banks and fintechs. AI tools utilise algorithms to scrutinise data, recognise patterns, facilitate predictions and make decisions.

How has the recent surge in AI adoption affected the banking and financial sectors? Progress in machine learning and natural language processing has significantly enhanced AI’s capabilities in personalization, fraud detection, risk management, and customer service. Currently, 35% of companies have incorporated AI into their systems.

However, with the growing influence of AI in banking and finance, it has received its share of concerns, especially around data privacy and regulation. We’ll discuss all that and try to pinpoint how AI will colour the future of financial services.

 

How AI is applied in Financial Services

 

AI in credit risks

AI plays a pivotal role in risk management, specifically concerning credit risk. By diving deep into credit histories and myriad other factors, AI credit tools can offer precise readings of credit risks and make credit decisions based on that. 

These machines rely on techniques like support vector machines for accurate decisions when predicting critical credit risks like payday or loss-given default loans.

This detailed analysis helps financial institutions make well-informed, informed, and practically clairvoyant lending decisions. It’s no wonder financial institutions are turning to external consultants proficient in deep learning to devise revenue forecasting models, especially under stress scenarios.

 

AI in compliance

Ensuring compliance is a must for financial institutions, as it safeguards them from severe penalties and reputational harm. In the intricate realm of finance, noncompliance is not an option. Leveraging the power of Artificial Intelligence (AI) becomes crucial in this scenario.

AI is a potent tool for automating compliance processes like anti-money laundering (AML) and know-your-customer (KYC). These AI-powered solutions play a vital role in detecting and preventing unlawful activities, thereby enhancing the security and reliability of the financial industry.

 

AI in fraud detection

Another crucial application of AI in finance is in fraud detection. By employing AI-powered algorithms, financial institutions can meticulously analyse vast datasets, swiftly identifying potential fraudulent activities and preventing them proactively. 

This isn’t just a money-saver for financial institutions; it’s a guardian, shielding them from colossal losses and customers’ heartaches.

 

AI in risk management 

AI’s role in risk management has become increasingly significant, especially in the context of real-time insights. By analysing extensive customer data, AI offers valuable information about market trends, customer behaviour, and financial risks. 

These insights empower financial institutions to make well-informed investment decisions, effectively reducing the risk of potential losses. Additionally, AI is crucial in enhancing portfolio management, optimising risk management strategies, and pinpointing new investment opportunities.

 

AI in customer service

The transformation doesn’t stop there. AI has revolutionised customer service within the banking and financial services sector. Virtual assistants and chatbots have become the unsung heroes of customer service in banking and finance, providing round-the-clock support to customers. 

This continuous assistance ensures that customers can swiftly and efficiently resolve their concerns, enhancing customer satisfaction and service efficiency.

 

AI in personalisation

Personalisation is another one. Customers are no longer faces in the crowd; they are unique individuals with unique needs. AI crafts tailored solutions, making every interaction personal and efficient. It’s no wonder Gartner earlier reported that customer satisfaction will grow by 25% by 2023 in organizations that use AI.

 

AI in data analysis and data mining

AI technologies that are pivotal in handling vast amounts of real-time data are a cornerstone of the financial industry. By employing AI, financial institutions gain profound insights into customer behaviour, market trends, and investment possibilities. 

This knowledge is instrumental in refining product development, enhancing customer experiences, and devising effective risk management strategies.

Furthermore, integrating blockchain technology with AI has created more secure and transparent systems. This combination enhances the overall reliability and trustworthiness of financial transactions and data management. 

Then there’s explainable AI, the storyteller. It’s becoming the guiding light, ensuring that AI systems aren’t enigmatic mysteries but comprehensible companions, ready to be understood and audited.

But, and there’s always a but, isn’t there? The rise of AI also raises concerns, especially about privacy and rules. How do these concerns affect the future of financial services?

 

Going concerns and the future implications of AI in financial services

 

 

Data security is a major concern, but will it only get better

As AI algorithms evolve into intricate tapestries of complexity, ensuring their ethical and transparent use becomes non-negotiable. 

Data privacy is a major concern in this regard. AI relies heavily on vast customer data, raising the risk of data misuse or theft. 

Upholding customer trust demands financial institutions prioritise data security and implement strict protection policies to safeguard sensitive information. This involves addressing intricate issues related to data privacy and adherence to regulations, guaranteeing the responsibility for deploying AI technology.

 

AI will replace more jobs, but service efficiency will improve

Furthermore, AI has and will continue to disrupt job displacement in the financial sector.

Functions like data entry, analysis and forecasting, traditionally performed by humans, will be partly or fully automated, leading to workforce reductions. However, this shift creates fresh jobs and opportunities in burgeoning fields like data science and AI development.

But as automation sweeps regular jobs in fintech under the rug, brands will witness minimal data errors, more reliable risk management parameters, elevated customer experiences and reduced operational costs. This efficiency boost reshapes the industry landscape significantly. 

Financial institutions will rely more on AI’s creative ability to craft innovative business models. Robo-advisors, for instance, leverage AI to provide personalised financial advice and investment recommendations, revolutionizing investment platforms. 

Similarly, peer-to-peer lending platforms employ AI to assess credit risk and connect borrowers with suitable lenders, driving transformative changes in the lending landscape.

 

AI will make compliance better but will require regulations

AI can help compliance service providers create better AML, KYC and CBT technologies. We already see that in AI facial recognition tech, AI-assisted biometric authentication and more. It will only get better from here.

However, integrating AI into financial crime-fighting comes with regulatory complexities. Regulators ensure that financial entities adhere to AML and KYC regulations when employing AI technologies. 

Transparency, ethics, and fairness in AI-powered compliance solutions require vigilant oversight to maintain industry integrity.

Now, to the meat of this discussion; how do you prepare your financial service business for an AI-augmented future?

 

Preparing your financial service business for an AI-powered future. The “why” and “how”

Like when financial businesses had to adjust to the internet age, banks and financial service businesses that don’t prepare for an AI-augmented future might find themselves out of business. 

Embracing AI by investing in AI tools and experts to build financial solutions powered by AI is the no-brainer correct decision. However, what and how financial service providers adopt AI is up to each organisation’s business needs and priorities.

If you’re confused about where to start integrating AI into your financial service business, you cannot go wrong thinking about customer satisfaction first. Investing in efficient chatbots and consumer data analysis AI systems will give you the data needed to build personalised product experiences for your customers.

From here, deploy applicable AI systems to streamline operations, compliance, fraud detection, credit decisoning, risk management and all other aspects of your financial service business. And since new technology is always at risk of cyber attacks, you must invest in AI infrastructure security.

At Finslack, we’re forward-thinking regarding using AI in financial services. That’s why we provide partnering businesses with a future-proof and agile financial engineering platform where they can endlessly integrate AI systems into whatever financial offerings they build and launch with Finslack.