LexisNexis: UK Firms Spend the Equivalent of £21k Hourly to Fight Financial Crime
- A new study examines the costs of fighting financial crime
- Surveys were distributed in the UK
- Another survey by Intelligent CSIO reveals that the number of victims is growing
While we focus on fraud in the US, it's important to understand fraud trends across the globe as well -- these markets can bring valuable insights.
A recently released report by LexisNexis, working in collaboration with leading research agency Oxford Economics, reveals that UK firms spend the equivalent of £21k (roughly $26,625 USD) hourly to fight financial crime.
We carried out in depth qualitative surveys of over 300 UK firms to quantify spend and split of activities across the full range of compliance obligations, exploring how people and technology are employed in the fight against fraud and money laundering and asking the question: is the sector doing enough of the right things?
The report, entitled The True Cost of Financial Crime Compliance, also reveals:
- The shifting balance of technology vs people costs since 2020
- The leading external factors responsible for driving up compliance costs
- the biggest expected compliance cost drivers over the next three years
- how firms have enhanced compliance processes
- how compliance spend compares between big banks, challengers, and fintechs
Meanwhile, Intelligent CISO reports that more and more people are becoming fraud victims:
Three in ten (30%) UK adults have been a victim of financial fraud, and more than half (55%) have seen an increase in the number of scam attempts in the last 12 months.
UK and USA Heavily Invested in AI for Fraud Detection
To combat climbing fraud rates, UK firms are investing in AI and machine learning technologies to combat the fraudsters.
As reported by LexisNexis:
Equally, the rise in the sophistication, capability and availability of AI and machine learning in recent years has not gone unnoticed and the financial services sector is shifting its focus to explore and test how these more advanced techniques can be harnessed to realise greater efficiency and effectiveness across financial crime compliance processes and controls.
Forty one percent of firms reported that they’d already implemented new technologies such as AI, machine learning and other analytical tools in 2023, and continued investment in developing these capabilities is expected to be a major ongoing driver of rising FCC costs across the industry moving forward, with almost all (99%) firms polled expecting to have increased their adoption of these new technologies by the end of 2026. The same proportion also expect to recruit and train more data science and technology specialist over the same period.
Additionally, OrboGraph's newest partner, Featurespace, recently announced the results of a major pilot with Pay.UK -- the independent, not-for-profit operator of the UK’s national retail payments system, to protect UK consumers from APP fraud -- with participants’ results showing an average uplift of more than £112m worth of additional fraud detected in a year.
“Banks across the UK have been harnessing this data and using AI and Machine Learning technology for good for over a decade. By creating an anonymised profile of an individual in real-time, we can use the good behaviour (of which there is significantly more), to identify and stop unusual, potentially fraudulent bad behaviour in milliseconds, protecting banks and their customers from fraud. The recent Pay.UK proof of concept demonstrates that when banks share intelligence amongst the group, the positive impact on reduction of loss for consumers is striking.”
Financial firms in the US are also investing in AI and machine learning technologies to fight fraud, particularly when it comes to check fraud. These technologies power solutions like transactional/behavioral analytics and image forensics to detect both account anomalous behaviors as well as counterfeit, forged, and altered checks.
Fraud is a global issue. However, the power of the internet allows firms around the world to leverage AI and machine learning in their fight against criminal deception.