From virtual advisors to detailed financial forecasts, here are 5 ways generative AI is poised to revolutionise the fintech sector.

Whether it’s picking winning stocks or rapidly ensuring regulatory compliance, generative artificial intelligence (AI) and fintech seem like a match made in heaven. The ability for generative AI to process, analyse, and create sophisticated insights from huge quantities of unstructured data makes the technology especially valuable to financial institutions.  

Since the emergence of generative AI over a year ago, fintech startups and established institutions alike have been clamouring to find ways for the technology to improve efficiency and unlock new capabilities. Globally, the market for generative AI in fintech was worth about $1.18 billion in 2023. By 2033, the market is likely to eclipse $25 billion, growing at a CAGR of 36.15%.

Today, we’re looking at five applications for generative AI with the potential to transform the fintech sector. 

1. Virtual advisors 

One of the quickest applications to emerge for generative AI in fintech has been the virtual advisor tool. Generative AI, as a technology, is good at agglomerating huge amounts of unstructured data from multiple sources and creating sophisticated insights and responses. 

This makes the technology highly effective at taking a user-generated question and generating a well-structured answer based on information pulled from a big document or a sizable data pool. These tools can also exist as a customer-facing service or an internal resource to speed up and enhance broker analysis. 

2. Fraud detection 

The vast majority of financial fraud follows a repeating pattern of behaviour. These patterns—when hidden among vast amounts of financial data—can still be challenging for humans to spot. However, AI’s ability to trawl huge data sets and quickly identify patterns makes it potentially very good at detecting fraudulent behaviour. 

An AI tool can quickly flag suspicious activity and create a detailed report of its findings for human review. 

3. Accelerating regulatory compliance 

The regulatory landscape is constantly in flux, and keeping up to date requires constant, meticulous work. Finance organisations are turning to AI tools for their ability to not only monitor and detect changes in regulation, but identify how and where those changes will impact the business in terms of responsibilities and process changes. 

4. Forecasting 

Predicting and preempting volatile stock markets is a key differentiator for many investment and financial services firms. It’s vital that banks and other organisations have the ability to accurately assess the market and where it’s headed. 

AI is well equipped to perform regular in-depth pattern analysis on market data to identify trends. It can then compare those trends to past behaviours to enhance forecasting results. It’s entirely possible that AI could bring a new level of accuracy and speed to market forecasting in the next few years. 

5. Automating routine tasks 

Significant proportions of finance sector workers’ jobs involve routine, repetitive tasks. Not only are human workers better deployed elsewhere (managing relationships or making higher level strategic decisions) but this sort of work is the kind most prone to error. 

AI has the potential to automate a number of time consuming but simple processes, including customer account management, claim analysis, and application processes. 

  • Data & AI
  • Fintech & Insurtech

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