When running a business in today’s market, tackling identity fraud can be one of the most intricate and expensive tasks involved. This, combined with the detrimental effects that failing to meet regulations can bring both financially and in terms of reputation, gives fraud management an unenviable seat in the boardroom – often misunderstood and undervalued, until it’s too late.
Fraud itself is nothing new, however the fraud and identity theft industry is currently undergoing a resurgence. While our increasing reliance on digital services and products has generated endless advantages across professional and personal lives, especially in recent months, it has also expanded new opportunities for fraudsters. Individuals are logging onto online services and applications from remote locations across the globe, extending the potential exposure for digital identities to be accessed. No longer is identity theft simply a hobby for hackers – evidenced by the fact that the fraud sector is now worth trillions.
Business continuity is now reliant on a shift from analogue to digital offerings, and organisations across industries are currently reinventing themselves through digital transformation. As a result, the number of interactions between digital platforms and customers is exploding, meaning that there are more vectors available for fraudsters to exploit.
About the author
Carol Hamilton is Director of Compliance & Fraud, EMEA at GBG
Using data to win the race against identity fraudsters
When it comes to identity theft, we are seeing a surge in both attempts and complexity of attacks. Essentially, as our digital world booms, so does that of cybercriminals. So how can businesses navigate this evolving fraud landscape? As a key first step, they should look to embrace data, collaboration and emerging technologies like advances in identity verification.
What’s more, the ways in which technology can support identity theft prevention are evolving, and we can now use data as a core part of these defences. An ever-growing, flexible, multi-dimensional data set has the ability to support decision-making, risk assessments and market understanding. There’s therefore no doubt that leveraging the potential of connected data points to support identity theft prevention measures will become ingrained within business operations of the future.
Preventity identity theft with verification
Identity verification lies at the heart of fraud prevention. However, with each step forward in identity verification technology, there’s also a progression in identity theft methods. Ultimately, it’s a battle between the two which drives the need to continue innovating and developing new verification technologies.
Most recently, we’ve seen businesses faced with the challenge of remote identity verification. Under remote working measures, businesses have had to suddenly shift from in-person to digital verification, leaving a gap that the online world doesn’t provide for: the certainty that a person behind the screen is who they say they are.
In a time of such heightened concern, there’s more need now than ever before for businesses to be proactive in their fraud prevention solutions – to protect themselves and their customers. Identity verification technologies can be quickly and easily implemented into a business’ services. By embracing connected datasets, organisations can benefit from smarter, more up to date and relevant insights to verify who is a legitimate customer and who’s a fraudster.
Strengthening defences with data orchestration
Data orchestration allows organisations to coordinate the use of data effectively and easily through one layer. As risk officers strive to equip their organisations to be safe and secure, we are seeing a transition from data orchestration being a future goal to becoming intrinsic to secure operations. For example, during onboarding processes, identities will be verified and cross checked with existing datasets to determine if the person is who they say they are, or if they’ve committed fraud in the past. Not only does this add a contextual layer to fraud and identity theft prevention measures, it also improves accuracy and ensures compliance.
Manual data processes and siloed systems are being replaced with intelligent datasets in order to generate real-time responses to identity theft and fraud. Increasingly, behavioural intelligence (i.e. insight into a customer’s behaviour as imprinted in data) is being used to detect the abnormal and increase the power of fraud detection. Furthermore, there is growing emphasis on streamlining processes so that neither customer nor fraudster is aware of the process.
As a further example, device data can indicate potential identity hijacking. Consider the example where an individual’s mobile number has changed sim cards shortly before a significant transaction takes place. Using data to spot suspicious patterns of behaviours such as this can be vital to both the organisations, such as retailers or banks, and the customers involved.
AI and ML: The future of fraud prevention
Combining data and key behavioural intelligence with technologies such as machine learning (ML) can open up a realm of possibilities when it comes to tackling fraudsters. Machine learning can uncover previously unknown fraud patterns and use automation to support real-time fraud detection and prevention. Furthermore, ML can reduce mistakes, improve accuracy and boost efficiency, which in turn will sharpen up operations overall. Organisations across industries are making real progress here and investing more and more.
Ultimately, fraudsters are continually evolving and developing new means of stealing identities – their methods can even change on a daily basis. By adopting data and intelligence driven strategies and leveraging sophisticated AI and ML capabilities, enterprises will be able to detect potential identity theft as it happens, mitigate the impact – and therefore stay ahead in the fraud race.