Increased digitisation has caused an immense uptake of new AI solutions within the workspace. The growing demand for no-code technology which does not encourage human bias was also a key factor for companies developing and implementing AI in 2021.
AI is undoubtedly changing finance, but what trends are we going to see in the new year? Anshul Pandey, co-founder and CTO, Accern, a company looking to improve AI workflows for enterprises with a no-code development platform, spoke to The Fintech Times to gives his views:
As the world goes digital, AI has continued to infiltrate enterprise tech, notably within financial services. In fact, the global fintech market is projected to reach $46.8million between now and 2030 – compared to a mere $7.7million in 2020. Showing no signs of slowing down, AI will continue to take over the fintech and financial services industries in the months and years ahead.
Particularly within the banking and insurance industries, AI has proven beneficial across multiple use cases. For example, banks now rely on AI to determine who qualifies for a loan, while insurance firms rely on AI to help clients make claims. One common theme across use cases is that AI has proven to reduce risk throughout financial services.
As business leaders and consumers grow accustomed to interacting with AI and developing trust in its recommendations, the most prominent trends for the year will consist of using AI to increase efficiency, save valuable resources, act on timely news and customise services for clients, among other purposes.
Four Ways AI is Transforming the Financial Services Industry
One major use case within the financial services industry is using AI to automate manual processes. More than 40 per cent of finance leaders report that demand for faster, higher-quality insights is the biggest factor in moving toward automation. In today’s data-driven world, it’s more important than ever to be able to capitalise on data as quickly as possible. AI provides a solution to automate manual tasks and provide faster insights as models can be trained to make informed decisions based on a specific set of rules.
Historically, tedious tasks like evaluating someone’s loan application or processing insurance claims have been manual. Now, data teams can use AI’s natural language processing benefits to find data quickly and train AI models to follow rules. Manual processes such as identifying fraud, finding information relevant to mortgage, loan, and insurance applications, and more can be executed with little or no human interaction. Saving valuable resources usually spent on manual processes, AI transforms how financial services firms work while providing more efficiency and savings on costs.
Not only can AI take time-consuming tasks off human’s hands, research shows that AI-powered hedge funds vastly outperform yield returns three times higher than the global industry average. Hedge funds that use AI reap the benefits of algorithmic trading by recognising patterns in historical data. Unlike trading that relies on human decision-making, often influenced by emotion or personal bias, algorithmic trading uses AI models to make better-informed and more fact-based trades. Over 60 per cent of trades over $10million in 2020 were conducted using algorithms, and the algorithmic trading market alone is expected to reach $19billion by 2024. Helping firms reduce risk and act quickly on current trends, algorithmic trading is significant, especially within hedge funds, and will remain a key trend in 2022.
Additionally, to stay competitive in today’s environment, it has become crucial for financial services firms to offer personalised services to their customers. By using AI, firms can segment customers into groups with similar interests, demographics, and needs to let professionals target different strategies and services for each. The data and insights gained are valuable in determining where firms should deploy their resources, leading to greater ROI and more relevant customer offerings. Some have found that firms could see a six per cent increase in revenue even with the most basic personalisation strategies. Throughout 2022, enhancing customer experience will continue to be a primary goal for financial services firms. AI will be a determining factor that can help firms engage better with their audience and reduce client turnover through greater personalisation.
Lastly, more companies in financial services are using AI to execute credit risk analysis, helping banks make informed credit decisions. AI provides real-time indicators of a potential borrower’s creditworthiness, such as their current income, employment opportunities, and earning potential. As such, banks can now use alternative data to help provide affordable credit without compromising on profitability. Alternative data makes this possible by analysing large amounts of data to detect hidden interactions and provide better insights, which generally wouldn’t be possible to consider through human efforts alone. Firms can offer clients more equitable solutions when using AI to make credit decisions. It also helps mitigate the bias common in human decision-making while still allowing banks to maintain their preferred risk exposure.
The advantages of AI within the financial services industry are clear. However, some of the biggest challenges facing AI adoption in the financial services industry are the lack of education and skilled subject matter experts. However, with the growth in digital data, digitisation, and changing consumer expectations, financial services firms will have to find ways to leverage the benefits of AI to remain competitive. In 2022, firms will find ways to implement AI across their operations with minimal disruptions in workflow.
A More Innovative Solution
Despite how advanced technology is, financial services firms do not have to hire experts or train employees to code to implement AI and machine learning into their operations. No-code AI solutions are an asset to companies in the financial services field, as they are an easy way to reap the benefits of AI without the technological complexity. Firms can process large amounts of data in less time, automate manual processes, build AI models, and more using no-code AI, leading to better and faster decision-making.
Financial teams can still capture valuable insights from AI without having the same training as data scientists. By allowing financial services firms of all sizes to extract recommendations from AI and find better solutions using alternative data, companies using no-code AI solutions in 2022 can reveal real-time trends and act on the most up-to-date data.
Because of the pandemic, 52 per cent of companies accelerated their AI adoption plans in 2021, 2022 will likely be another year of further AI integration into financial services firms. Utilising no-code AI will not only give companies the upper hand in their competitive advantage using the latest technology, but it will allow them to see better cost savings, more personalised services, and greater efficiency.