With the generative AI boom in full swing, a future of automation in fintech is imminent. While this may be a cause for concern among employees, the reality is set to be far more collaborative.

The artificial intelligence in fintech market is expected to reach a value of $17 billion in 2024. This figure is set to soar to $70.1 billion by 2033, representing a CAGR of 17%. 

This rapid acceleration of AI and the automation technology it can deliver throughout countless facets of fintech will be a major source of disruption, equally proficient in driving efficiency and uncertainty. 

However, automation within fintech appears to be pointing towards a more collaborative future for its early adopters. 

What is Automation in Fintech?

Automation in fintech refers to the streamlining of processes end-to-end. This typically involves enterprise automation platforms that are capable of taking care of repetitive tasks by gathering and acting on data insights. 

Given the vast volume of data accessible within the world of fintech, and the insights that can be gathered in the age of open finance, we’re likely to see automation technology take center stage throughout the industry to drive efficiency and save on time-intensive activities like data entry at scale. 

There are many ways that fintech automation can be delivered with the help of artificial intelligence. Let’s explore some of the most transformative developments set to sweep through the industry as a result of autonomous technology:

1. Smart Insights

The automation revolution will be built on data and can help generate powerful insights to facilitate more intelligent business decisions throughout the fintech landscape. 

The age of open finance promises to democratize different subsectors of fintech, and the data that this interconnectivity will generate will be invaluable to machine learning algorithms. 

This customer data will help to provide a better customer experience by creating rich visualizations of purchasing behavior, investment insights, actionable advice, and introducing helpful new tools that suit user needs. 

Large-language models (LLMs) like ChatGPT have already provided a glimpse into the future of fintech. The ability of LLMs to analyze social media, news data, and other unstructured datasets to analyze public sentiment towards leading fintech products or services will offer a powerful means of improving the CX firms can provide.

2. Automated Risk-Assessment

Because machine learning has the potential to fully automate data processing, the technology can revolutionize risk assessment within the fintech landscape. 

Where traditional risk assessment relies on one-size-fits-all processes and rigid credit scores, automated systems can delve into an applicant’s financial history and spending patterns to provide a more holistic view of their application and level of risk. 

This can help to equip open finance firms with a more holistic risk profile to determine creditworthiness and to leverage more personalized lending decisions at a scale that humans would be incapable of replicating.

3. Robots as Bankers

An abundance of financial data means that robotic process automation (RPA) can empower AI algorithms to replicate human tasks such as the opening of new accounts for customers. 

This can help to prevent human errors and reduce friction throughout the account creation process for banking services. 

Banks are already actively utilizing RPA financial services to make it easier to open accounts by automatically populating application forms with customer details for their central banking systems and undergoing know-your-customer (KYC) checks autonomously. 

In introducing RPA for this area of account creation, fintech firms can actively improve the customer experience while reducing waiting times through the utility of accurate data throughout the application process.

4. Blockchain Automation

Best known as the mechanism that powers cryptocurrencies like Bitcoin, blockchains will invariably play a powerful role in the future of fintech automation. 

Because blockchain technology acts as a distributed digital ledger of transactions that can trace ownership and is entirely immutable, it provides a foundation for all open finance participants to access the same data in real time. 

This will be invaluable in the future of automation because it paves the way for the utility of smart contracts, which can work with blockchains to automatically-execute transactions when predefined conditions are met. 

Through smart contracts, borrowing can be revolutionized through peer-to-peer (P2P) lending, supply chains can become more visible, and complex credit agreements can be arranged efficiently without the necessity of middlemen to broker deals.

5. Around-the-Clock Compliance

The future of open finance will be borderless, and this can present plenty of complicated ramifications for fintechs seeking to manage their compliance throughout different nations and continents. 

With global regulatory environments constantly changing and evolving, machine learning algorithms can streamline their compliance by automating the monitoring of the regulatory landscape. 

When new compliance obligations are launched in the US, France, China, or Mozambique, machine learning will study the new regulatory guidelines and generate an actionable report that covers the changes that need to be sanctioned on an operational level. 

Every adaptation can then be recorded for future reference through a generative AI report to ensure that all decision-makers are aware of the actions that have been taken. 

Collaboration, Not Replacement

Naturally, news of automation technology can be a cause for concern among many employees within the fintech landscape, but we’re far more likely to see artificial intelligence change job roles within fintech rather than replace them. 

In the coming years, AI is expected to create 133 million jobs globally, and this will include the burgeoning open finance landscape within fintech. 

As automation sweeps through the world of fintech, we will see the skillsets of staff become more globally focused and supervisory. This will see more employer of record (EOR) services switch to discovering remote talent that can act decisively on AI and ML insights. 

This will see EOR costs become a core function of modern fintech as more talent becomes outsourced throughout the world and the emphasis switches to innovation as opposed to data management. 

Finding Synergy with AI

Automation will bring revolutionary change throughout the fintech landscape. For businesses that synergize AI, ML, and human oversight to act decisively on the wealth of data within the growing open finance ecosystem, the potential for more efficiency, accuracy, and a positive customer experience can be a powerful driver of growth. 

The innovations driven by automation are already being tapped into by the world’s most ambitious fintech firms. By acting today, it’s possible to unlock the benefits of automation technology before the wider industry begins to play catch-up.