Finance
How Risk Analytics is transforming the Financial Industry
Global Banking & Finance Review®
Company
By Conor Larkin, Managing Consultant Harnham
Today’s financial firms and departments face a huge amount of pressure to perform efficiently and under reduced costs, whilst simultaneously combatting cyber-crime, improving operational and cyber resilience, and meeting evolving regulations.
Because of this, the financial industry is becoming a strong driver of innovation and is beginning to embrace the opportunities offered by new techniques and disruptive technologies such as risk analytics and AI to enhance its systems and capabilities.
Financial institutions are rich in data and information assets, making them the perfect candidate for the use of models and analytics to harness this data to, for example, make better informed decisions, streamline processes, and calculate future risk.
In recent months Harnham has been witnessing a surge of interest around Risk Analytics in the financial space. According to research, the Risk Analytics market is expected to be worth around $54.95bn by 2027. This buzz can be attributed to a perfect storm of factors coming together at once.
The growth of business procedures and increasing deliverables is driving demand for techniques such as risk measurement, whilst rising incidents of cyberattacks combined with rising digitisation are further catalysing the Risk Analytics market. Not to mention the impact that different macroeconomic elements are having, such as coming out of the pandemic, remnants of Brexit and rising inflation rates.
All of these factors have resulted in positioning Risk Analytics and its services, as not only worthy of investment for businesses and firms, but as vital for financial growth and stability. Investing in security is no longer a luxury reserved for huge corporations with bottomless pockets, it has become an industry-wide concern.
The New Digital World
The widespread digitisation witnessed across all industries, spurred on by the unprecedented shift to remote and cloud-based working, have made concerns around security come to the surface as a problem impacting entire teams. Digitisation offers opportunities for company growth but if not securely managed, can serve up opportunities for criminals to exploit.
Because the shift in working practices was so sudden, some may still be playing catch up with the security side and may not be working as securely as they could be.
Headlines highlighting a ‘fraud epidemic’ have been circling, with reports of fraud and cybercrime in the UK rising from 3,983 cases to 8,614 in a year. Fraudsters are becoming increasingly inventive, and rapid measures must be taken to stay one step ahead.
Giving fraudsters a run for their money
Financial institutions are not just resting on their laurels however, they are busy fighting back by innovating and investing in their fraud and risk analytics departments. Fraud analytics plays an essential part of any business when it comes to profit and loss, and Risk Analytics works to understand the drivers in fraud in order to ultimately prevent it.
Previous fraud detection systems were designed based on a set of rules which modern fraudsters can easily bypass. Innovation such as Machine Learning (ML) has provided solutions to this via its pattern-recognition capabilities.
The systems can be programmed to scan through large data sets to detect and flag anomalies, irregular activity and identify potentially fraudulent financial transactions, which will then be investigated by a human professional. This not only speeds up a long and mundane process but also reduces the risk of human error.
What’s more, the finance industry is recognising the value that risk modelling and ML can provide that goes far beyond security. Analytical practitioners have a vast array of capabilities and techniques at their disposal, such as ‘predictive analytics’, that provide advanced models to forecast and predict the future, as well as ‘prescriptive analytics’ that utilise machine-based learning algorithms to provide interpretations and recommendations to better inform decision making.
These techniques not only allow financial firms to gleam deeper and more valuable insights from their data, but also to deploy these processes on an industrial scale.
Unregulated products emerge
The flood of new unregulated products and technologies into the financial market has added fuel to the fire for opportunistic fraudsters. 2.3 million people in the UK are now thought to own a crypto asset, creating a playground for swindlers looking to misuse unregulated tech.
As new products and unregulated technology such as crypto-assets, decentralized finance and non-fungible tokens (NFTs) rapidly expand into the market, regulators are constantly running to catch up, and can find themselves on the back foot, forced to make up rules and regulations as they go.
Data reveals a staggering £146,222,332 has been lost to cryptocurrency fraud since the start of this year, and unless regulators are able to keep up with the ever-evolving nature of crypto, this will rise.
As a result, we are expecting to see plenty of regulatory changes come into force, to increase protections against consumer risk but also within financial institutions. Regulation stimulates demand within sectors such as Risk Analytics as well as causing shifts of focus within departments.
Financial teams know better than most what is stake when it comes to security and the importance of staying ahead of the curve. The sector is countering the rise in cyber threats by thinking outside of the box and investing in innovative technology such as Risk Analytics.
At the same time, the rise of innovation and digitisation within the finance industry is offering risk departments new opportunities to better measure and mitigate risk and deploy machine algorithms to automate time-consuming, mundane processes. It’s set to be an exciting year for Risk Analytics in finance.
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