Artificial Intelligence is making light work of routine tasks and helping businesses to save both time and money. In this blog, we’ll explore which areas of risk management are affected by the AI revolution and what it all means for future jobs in the risk sector.
The adoption of AI in risk management efforts is fuelled by increasing data regulations and traditional methods of data oversight becoming unreliable, given the large volumes of data that organisations are handling.
There are several key areas in risk management which are being enhanced by AI.
Fraud Detection and Prevention
AI systems can analyse patterns on a scale which no human can replicate, using algorithms trained with historical data. AI therefore excels in detecting fraudulent activities in real time. It can identify any anomalies, and therefore potentially fraudulent transactions - offering a vital layer of protection for financial institutions.
Project Risk Management
Project risk management has been significantly enhanced with AI's ability to forecast potential roadblocks, challenges, and inefficiencies in real time. The predictive modelling capabilities of AI help in pre-empting risks and allow businesses to mitigate them effectively – before they occur.
All companies, regardless of size or industry sector, are vulnerable to data breaches. An IBM report states that the average data breach in the US comes at a cost of $4.24 million per attack. Detecting and acting on these threats quickly and early is therefore vital. AI sorts through high volumes of data to identify and eliminate any threat. It can also use the latest knowledge of global or industry-specific threats to better understand what is most likely to be used to attack a company’s systems, enabling risk managers to make informed decisions on what to prioritise.
Even the most proficient humans do occasionally make innocent errors when it comes to contract management; particularly after spending endless hours reading, interpreting and dissecting the lengthy and often complex legal language found within contracts. AI can assist with risk identification efforts by locating vague passages, highlighting expirations and missing data and identifying contract standard deviations. AI can rapidly scan and evaluate and this valuable insight can help risk managers to make crucial decisions around contracts.
What does all this mean for the future of risk management roles?
There’s no doubt that AI makes risk management more efficient. Many routine tasks are now automated – but it doesn’t mean that job opportunities are reduced; it simply means that the workforce may need some reskilling and upskilling, in order to work effectively with the technology.
The rise of AI has sparked a demand for specialist tech skills, which means that candidates who are adept in machine learning, data analytics, and AI integration are highly sought after.
It brings a new set of challenges to risk management, too. There are ethical considerations – for example, who takes responsibility for a ‘bad’ decision by AI? And then there’s the question of data privacy. With an ever-increasing need to ensure that personal and financial data remains secure, can AI be trusted?
These and other concerns over the future of AI are making some risk professionals wary. But AI hasn’t quite taken over the world just yet. Traditional roles in risk management do still exist - but they are evolving. Many risk managers will now be expected to collaborate closely with data scientists, AI specialists, and other tech professionals to ensure seamless integration of AI tools and to make informed risk-related decisions.
If you're looking to hire in risk management, having access to Leonid’s talent pool ensures you get the best professionals with the skills that focus on navigating this new landscape.
Or, if you're a risk professional with experience of working with AI, now is a great time to be seeking out a new role, as businesses look to hire that perfect blend of solid experience and a tech-driven mindset.