1. Financial institutions will be more data-focused to combat fraud
Organisations are finding out that, as time is of the essence in their battle with fraudsters, real gains can be made with better access to data, including mobile phone data, IP addresses and other alternative data sources. We have an opportunity to reduce fraud losses immediately by taking faster action with better use of data – data that is currently all too often underutilised – to deliver quick wins as well as setting the groundwork for more advanced use of analytics, AI and ML in the future.
2. Social inclusion becomes a key talking point for digital identity
The UK government is currently working on a trust framework around digital identity, because it believes “having an agreed digital identity that you can use easily and universally will be the cornerstone of future economies.”
Currently, proving you are who you say you are often relies on trusted digital data sources, or a physical identity document, such as a driving licence or a passport. But millions of people in the UK and around the world are categorised as ‘thin file’ – meaning that they have no presence on digital data sources and often do not have approved physical documents. For example, 3.5 million people in the UK do not have any form of photo ID, according to Electoral Commission estimates. These are often the most vulnerable people in society, and this can lead to people being locked out of services, excluding them further from society.
With the government firmly putting digital identity on the agenda, expect conversations to pick up over the next 12 months about how technology can make society more inclusive. In the finance world, for example, people that previously could not open bank accounts or take out credit cards because they lacked the right identity credentials may be able to use their mobile phone, and the data associated with their phone and its number, to prove who they say they are and access new services – without the need to have a costly passport or driving licence.
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3. AI will be more widely deployed in the fight against fraud
AI is, arguably, the foundation of the whole fintech industry as it makes digital transactions and data aggregation faster and more accurate. Right now, there is strong intent among financial institutions, including banks, to use AI to reduce fraud. In our own independent research, almost a third of fraud professionals within financial institutions plan to invest in newer AI solutions like machine learning and predictive analytics in the near future.
4. Cross industry collaboration will become more commonplace
As data becomes better and more widely utilised, the value of data sharing will be better understood. A consortium approach is extremely powerful and effective when it is applied to cross-border fraud. Fraud has no respect for geography and with the bulk of fraud taking place online, greater collaboration and sharing of data means you are more likely to be able to spot trends and repeat offenders who are organised across borders targeting smaller financial amounts but at increasing frequency. There are a limited number of fraud consortiums or networks out there, but the bigger banks and insurers have already been successfully data sharing for many years. We will see many more players in financial services and fintech learn from the banks and insurers and begin to collaboratively use data in a similar way to identify and reduce fraud.
5. Context becomes key for digital identity in the finance sector
A growing problem in the finance industry is origination fraud – where a person opens an account, or takes out a loan, with fraudulent or falsified information. This trend is expected to continue to increase throughout 2022. To help combat this, businesses will need to safeguard their onboarding by understanding contextual data points linked to a digital identity. This means not just solely relying on physical documents or static data sets to prove a person’s identity but also understanding the wider trends about that person – have they created new contact data before onboarding, you expect to be associated with them, are they logging on from the location you would expect and are they online at the time you would expect them to be, for example. By leveraging data and adding context to somebody’s online profile companies will be able to reduce fraud, while making it easier for them to keep the bad actors out and let the good customers in.