To bring positive disruption to stale markets, risk is usually necessary. Here, Daniel Horton, technical manager at Parker Software, explains the technological risks the financial services sector needs to undertake to stay ahead of increasing regulatory requirements.

There are always risks when implementing new inventions and technologies, especially in highly regulated or particularly sensitive markets. The Financial Conduct Authority (FCA) has an overall objective to ensure that financial markets work well — maintaining consumer protection and overall market integrity. However, the FCA is also eager to promote competition in the interest of consumers, something that many new financial technology — or FinTech — innovations can provide.

Traditional financial organisations can be hesitant to embrace new technology. However, it is important that the industry understands how this innovation brings positive market disruption by forcing adaptive thinking and processes.

FinTech is already making significant changes to efficiency in the financial sector, but there is a long-standing view that increasing regulation will hinder growth. Financial services could be described as one of the most complex, highly regulated industries on the planet. In any industry, regulatory and compliance issues are important, convoluted and resource-consuming. Regulatory technology, or RegTech as it has become known, may provide a better solution for the financial services sector to meet these increasing regulatory demands.

The collaboration of regulatory standards and technology has existed for some time. However, increasing penalties for non-compliance — as well as a greater focus on data and reporting in the industry — has added more pressure for innovation and investments in the RegTech market.  Recent years have seen a significant change in technologies used in RegTech solutions, with innovators embracing technologies such as big data analytics and artificial intelligence.

Artifical intelligence in RegTech

Artificial intelligence may be one of the biggest sources of opportunity for the RegTech industry. By nature, artificial intelligence modelling — and to some extent, machine learning — is ideal for tasks that need to be handled accurately and logically, such as reporting and document archiving. The strict regulatory fashion of the finance industry makes it an ideal sector to invest in AI, because the technology can automate tasks that are based on specific systems, set rules and procedures.

We are likely to see an increasing presence of artificial intelligence in the financial services sector in the next few years. Tasks such as providing soliciting or financial advice could easily be provided through a bot interface, using existing artificial intelligence and automation technologies. Some companies are already using more advanced AI applications, such as IBM’s Watson. However, most of these companies are using this technology in an experimental fashion, as opposed to completely overhauling their existing procedures in favour of artificial intelligence.

Despite its potential, artificial intelligence is still in its infancy. Until it is fully developed, there will still be arguments about the accuracy and ability of AI over a well-trained human representative.

[easy-tweet tweet=”Predictive analytics technology can use pattern recognition to assess data from across the globe” hashtags=”Technology, Fintech”]

Using big data to manage risk

Alongside artificial intelligence, any sector that is dealing with large amounts of valuable data has the potential to use this information to make intelligent predictions. In the financial services sector, one application of big data analytics is to identify potential instances of fraud.

Predictive analytics technology can use pattern recognition to assess data from across the globe.  Naturally, manually assessing this data is a time-consuming process. However, combining this with artificial intelligence could allow the technology to automatically scan and categorise potential areas for fraud according to the amount of risk, and then pass on this fraud detection for human review.

As new types of fraud are identified, these incidences could be flagged and integrated into the machine learning logic. Using this method, automation could detect similar activity in the future and prevent fraudulent activity.

For the time being, artificial intelligence will simply assist the financial services sector — not become an integral part of regulatory compliance and standard management. There are clear advantages to handing over the reins of regulatory compliance to a computer designed to review and complete administrative tasks. However, while the technology is still in a state of learning, it will not have the upper hand over human employees for another few decades.

+ posts

CIF Presents TWF – Professor Sue Black


Related articles

How Businesses Should Tackle Big Data Challenges

In today's data-driven landscape, Big Data plays a pivotal...

UK IP Benefits and How to Get One

There are many reasons why you may get a...

Navigating the Landscape of AI Adoption in Business

In today's rapidly evolving technological landscape, the integration of...

Three Ways to Strengthen API Security

APIs (Application Programming Interfaces) are a critical driver of...

A Comprehensive Guide To The Cloud Native Database [2024]

Databases are crucial for storing and managing important information....

Subscribe to our Newsletter