If you are building financial software in 2024, you may have noticed a shift in people’s expectations. Investors, advisors, executive management, board of directors, and, to some extent, users, expect a certain level of AI integration.
This is not about a tick-the-box exercise or embracing ‘nice-to-haves’; the expectation is because they know that integrating with AI is now a necessity for all companies in the financial sector. According to a study posted on Gartner, “By 2026, 90% of finance functions are expected to deploy at least one AI-enabled technology solution.”
Companies know adapting to the AI evolution is no longer something that they can ignore. With competitors already using AI to streamline operations, detect fraud, and offer hyper-personalized customer service, delaying any further could lead to missed opportunities and following behind.
So how is AI used in FinTech software development? Below are 4 ways that financial companies are integrating with AI in 2024.
How is AI Used in FinTech?
1. To Supercharge The Software Development Process
To begin with, companies are using AI-powered tools to bolster the software development process itself. Tools such as GitHub Copilot, TensorFlow and Open AI’s Codex allow developers to generate new code based on prompts, reduce technical errors, automate testing, spot defects, and speed up repetitive tasks. Integrating with AI tools can allow software development teams to catch bugs early and build out features more efficiently. This means that firms can bring software to the market faster than ever before.
In a highly competitive landscape such as the financial sector, this is significant, as getting your software product to market faster than your competitors can provide a lasting market advantage.
At Keeper Solutions, we worked with an international FinTech company who wanted to explore all the ways that GitHub Copilot could improve their refactoring process. This ultimately resulted in the company reducing its engineering team from 35 to under 20 developers while improving coding quality. You can read more here.
2. To Enhance Security and Fraud Detection
Cyber criminals have been increasingly more sophisticated in recent years and, with financial institutions being a lucrative target, attacks on financial firms have become a regular occurrence. To counteract this, financial institutions are turning to AI to enhance security. These AI models are continuously learning and adapting to new attack techniques.
Companies such as JP Morgan Chase have used AI to revolutionize fraud detection and protect customers from increasingly sophisticated fraud attempts. Read more about the company’s fascinating AI journey here.
Fraud detection is, of course, an ongoing concern for financial institutions. By adopting machine learning algorithms, companies can protect their customers’ accounts and minimize financial losses related to fraud. While doing this they can also gain the trust and confidence of their customers.
Chances are you’ve seen this type of anti-fraud protection in action. Firms use AI tools and machine learning algorithms to analyze transaction data and spot anomalies in real time. This could include a customer making a number of lavish purchases that differs from their usual spending habits, or logging into their account from an unfamiliar device.
This proactive approach allows financial institutions to mitigate risk and, ultimately, provide a better service to their customers.
3. To Elevate Customer Services
Customers’ expectations are on the rise. It’s the reason why 90% of businesses, regardless of the vertical they are operating in, have stated that they have made customer experience their primary focus (CX Index).
Customers expect 24/7 assistance and instant access to information and support. It’s no wonder then that the first port of call for most financial institutions that want to integrate with powerful AI technologies is to look at customer support chatbots.
Gen AI chatbots provide real-time, around-the-clock user support, answering queries and promptly resolving issues. And the support they provide goes beyond what many people have come to expect from customer support bots. Chatbots built with the latest AI technology can give tailored financial advice and handle complex requests with minimal human input. What’s most significant is that the interactions between customers and Gen AI chatbots closely resemble human discussions where chatbots can pick up on customer intent and provide context-driven responses, greatly improving the overall customer experience.
Capital One’s ‘Eno‘ and Bank of America’s ‘Erica‘ are examples of custom-built generative AI chatbots that are helping financial institutions to provide fast-paced intuitive support to its customers.
See how you can build your own Gen AI chatbot, here.
4. To Streamline the Onboarding Process
When a customer signs up with a financial institution or a company in the financial sector, the onboarding process can be quite cumbersome for all involved. A typical onboarding process requires several layers of authentication and identity verification. The financial institution needs to process and validate whatever documents it receives. It can be an unpleasant experience for all involved.
For businesses, it can provide a real strain on resources. For users, it can be a less-than-appealing way to start a business engagement.
AI is streamlining the onboarding process for financial institutions. Intuitive Gen AI chatbots walk customers through the entire process, verifying IDs and processing all documentation without the need for human intervention. AI chatbots can also ensure compliance with regulatory requirements. This provides financial institutions with significant peace of mind and allows companies to focus their attention on higher value tasks — providing a great service to their customers.
How is AI Used In FinTech? Further Examples to Come.
These are just four ways that companies are using AI in FinTech. We will be back with even more AI applications in a future blog post.
If you are interested in integrating with AI in your company, our main advice is to start small, check out this article to learn more.
