--- description: In this article, we will understand what is artificial intelligence in finance, use of AI in financer along with the applications of AI in financial services. image: https://gdm-localsites-assets-gfprod.imgix.net/images/capterra/og_logo-e5a8c001ed0bd1bb922639230fcea71a.png?auto=format%2Cenhance%2Ccompress title: AI in Finance: Applications & benefits --- # AI in Finance: Applications & benefits Canonical: https://www.capterra.co.uk/blog/1945/3-applications-of-finance-ai Published on 15/11/2022 | Written by Toby Cox, Sukanya Awasthi. ![AI in Finance: Applications & benefits](https://images.ctfassets.net/63bmaubptoky/W55_hjJ_esszfju0u8EEjq60fvKjPhsuftQUwjblpE8/bdfd8c143bfa923e061320d5a4b69271/Finance-AI-1.png) > This article was originally published on 11/03/2021. Artificial intelligence (AI) in finance can possibly help companies cut costs, improve efficiency, and transform how their business manages its money. Read along to learn more about the applications and benefits of using AI in finance. ----- ## Article Content This article was originally published on 11/03/2021.Artificial intelligence (AI) in finance can possibly help companies cut costs, improve efficiency, and transform how their business manages its money. Read along to learn more about the applications and benefits of using AI in finance.In this articleWhat is AI in Finance?How is AI used in finance in the UK?3 Applications of artificial intelligence in financial servicesThe futureAI can automate routine tasks, increase process efficiency, and use machine learning, deep learning, predictive analytics, and natural language processing for more robust features such as chatbots and robo-advisors. According to a Business Insider report, 80% of banks are highly aware of the benefits AI presents to financial institutions. Adding AI to their fintech repertoire can potentially help banks and financial institutions improve their customer experience, reduce costs, and increase revenue.What is AI in Finance?In simple terms, AI in finance is the use of artificial intelligence in financial institutions. According to an article by OECDiLibrary, the financial sector is seeing an increase in the use of AI across a variety of sectors namely:Retail and corporate banking: Tailored products, credit scoring and credit underwriting decision-making, credit loss forecasting, anti-money laundering (AML), chat-bots for client service, natural language processing (NLP) for sentiment analysis, customer serviceAsset management: robo-advice, management of portfolio strategies, risk managementTrading: AI-driven algorithmic trading, automated execution, process optimisation, back-officeInsurance: robo-advice, claims managementHow is AI used in finance in the UK?UK businesses may be adopting AI and ML to advance their operations and explore other uses of AI in finance. Last year, the Bank of England and FCA conducted a survey into the state of machine learning in financial services in the UK. The survey presents some interesting insights regarding the use of machine learning (ML), which is a subset of AI, in financial institutions:There is an increase in the number of firms that use machine learning in financial institutions. A total of 72% of firms that took the survey reported developing/using ML applications. Financial services companies are proactively considering ML. The majority of responders that utilise ML (79%) have a plan for the creation, introduction, supervision, and application of the technology.Firms anticipate that during the next three years, the median number of ML applications will rise by 3.5 times as a result of this trend. The insurance industry is anticipated to grow the most in absolute terms, followed by banking.3 Applications of artificial intelligence in financial servicesLet’s discuss some of the ways that artificial intelligence in finance can be used in order to provide more value to customers, while still saving money.1. Use intelligent automation to save time and moneyBy automating routine tasks, financial institutions can possibly save time and money, minimise errors, and collect data along the way. Here are some examples of processes that AI can automate:Expense management: An AI solution can read receipts and categorise them based on a list of accepted expense types or vendors pre-loaded in the system. Employees will still need to review expenses that the system rejects. Accounts payable: AI can extract and compile data from PDF invoices allowing teams to focus on more complex tasks.Regulation compliance:  AI-powered tools can use natural language processing and ML to scan documents for certain terms that would show compliance with regulatory standards such as GDPR.Using AI to automate processes doesn’t replace workers, but rather gives them time to focus on more complex tasks.2. Use predictive analytics to inform decisionsAI and ML can predict the payment habits of customers. If a customer is deemed likely to pay late due to past behaviour, the business can remind them of their payment much earlier than they would with customers that pay on time. This is called an ML-Improved A/R (accounts receivable) process. As such, there are various benefits of AI in finance which can potentially save teams time, make reliable forecasts, and reduce the possibility of error.AI and predictive analytics can also help financial institutions assess and manage risk. It can also reduce the risks associated with giving loans to clients and also improve fraud detection.3. Personalise the customer experience Another application of AI in finance is the personalisation of customer experience. By using AI, financial organisations can gain more powerful insights into customer satisfaction and can personalise the customer experience. For example, instead of relying solely on a person’s credit score, banks can use AI-powered solutions to consider other factors of a person’s financial history, such as their repayment habits and how many loans they are currently paying.This information can be used to customise the individual’s interest rate. AI can also help clients manage their portfolios more effectively. This can be done through robo-advising and digital wealth management, both of which are on the rise.The futureFinancial Conduct Authority (FCA) has published a report with the goal to spark debate about the potential competitive implications discovered using existing research to guide their strategy for dealing with Big Tech businesses. The report states that the influence of big IT companies in the global and UK financial services industries has been growing, with the potential to expand and swiftly alter market outcomes. This can help financial companies plan and prioritise the use of AI within their operations and reap the benefits of AI in finance.Additionally, FCA has also been hosting webinars and roundtables for ‘those with responsibility for financial services, technology or consumer policy from Big Tech firms, incumbents and fintech challengers, consumer organisations and academia.’AI tools can also potentially save enterprises money and time. Using AI-powered tools such as chatbots, conversational AI for finance, robo-advisors, and analytics can also help you improve your customer’s experience with your business. This in turn may help them attract and attend more customers.Looking for artificial intelligence software? Check out our catalogue. ## About the authors ### Toby Cox Toby was a content analyst for Capterra. ### Sukanya Awasthi Sukanya Awasthi is a content analyst for Capterra, covering emerging technology trends with a focus on retail, construction and ERP. With an educational background in Computer Science, she brings 8 years of hands-on experience to her writing, translating intricate technical concepts into accessible and informative insights. Sukanya’s research and analysis is informed by nearly 200,000 authentic user reviews on Capterra and over 40,000 interactions between Capterra software advisors and software buyers. Sukanya also regularly analyzes market sentiment by conducting surveys of business leaders in the construction space, as well as retail leaders and consumers, so she can provide the most up-to-date and helpful information to small and midsize businesses purchasing software or services. Her work has been featured in Financial Express, Economic Times, and Bloomberg Quint, among other publications. 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