Incidents of fraud are becoming increasingly sophisticated, and financial institutions have a responsibility to detect and prevent illicit financial activity. Enforcement agencies fined global financial institutions £186,208,915 for anti-money laundering compliance breaches in the first half of 2022. Many institutions still avoid making full use of their data in their fraud detection models in a bid to avoid these fines and remain completely compliant with regulators.
Yet, as inflationary pressure and rising costs continue to contribute to the cost-of-living crisis, the threat of financial fraud is more present than ever. According to research compiled by LexisNexis Risk Solutions, 43% of financial services organizations expect the cost-of-living crisis to increase the risk of fraud over the next year. Financial institutions should make use of new privacy enhancing technologies to combat the rise in fraud.
Using Technology to Tackle Financial Fraud=
Fraud rose by 24% during the COVID-19 pandemic, with firms struggling to adjust to this challenge whilst remaining compliant with regulators. This surge in fraudulent activity suggests that fraud within financial services is unlikely to end anytime soon.
However, technological innovation has emerged as a promising tool in the fight against fraud. There has been a significant increase in the use of technology to analyze large amounts of data and spot patterns of criminal activity.
Nevertheless, data sharing continues to dominate as an issue for financial institutions as they try to combat fraud. In addition to copyright and licensing requirements, data sharing has high costs. Financial institutions often find it difficult to present data in an organized and useful format. The challenge of sharing and collaborating over data in a secure way has led to the emergence of new privacy enhancing techniques, many of which are being embraced by financial institutions.
Despite the bid to keep up with increasingly sophisticating financial criminals by adopting emerging technologies, businesses are still struggling. A recent IBM report found that over 90% of fraud signals are false positives. False alerts are a problem for firms because it makes handling fraud cases operationally expensive and increases customer friction. Consequently, we continue to see a concerning proportion of financial crime accounting for 2% to 5% of global GDP, according to the World Economic Forum.
Likewise, the stringent regulatory backdrop also makes it hard for financial institutions to make use of required data to monitor and implement intelligent decisions. It is incredibly difficult for the industry to detect and track criminal behavior as they are only seeing a small fraction of their customers’ activity.
The privacy and data sovereignty rules prevent large organizations from freely moving or centralizing data to analyze it. This not only limits their ability to detect criminals but also limits the extent to which organizations can collaborate.
In an ideal world, financial institutions could utilize and share data while meeting all regulatory and compliance obligations. This way, they would be able to improve all services needed to combat fraud, money laundering, and illicit finance.
Embrace Confidential Computing
Confidential computing and other privacy enhancing technologies are revolutionizing fraud-detection models. According to Gartner, organizations that promote data sharing will outperform their competitors on most business value metrics.
Banks often avoid sharing data due to the strict regulatory backdrop, and therefore minimize the potential insight they can obtain from not just their own data but other bank datasets. However, by making use of privacy enhancing technologies to confidentially share intelligence across datasets, banks can pool, process, and analyze sensitive customer data. With this, banks will be better equipped to spot complex patterns and provide critical intelligence, without ever revealing the raw data to one another.
Not only do privacy enhancing technologies ensure that sensitive customer data is protected, but they also give banks a competitive advantage at a time where data sharing is becoming the norm. Better yet still, banks can benefit off this secure data collaboration without putting any competitive advantage at risk, as any data that may give the banks an edge over their competitors will never be revealed.
The trust mechanism is also a key component to data sharing. Gartner also predicts that through 2023, firms that implement digital trust will be able to take part in 50% more ecosystems. Confidential computing provides banks the required assurances that the data sharing process is secure via its remote attestation feature. Furthermore, this emerging technology even removes the ‘trust’ from the trust model itself. Banks will never need to ‘trust’ banks with their data. Instead, they’ll just need to trust the technology.
Going forward, banks that fully embrace privacy enhancing technologies will not only increase their opportunities to generate revenue by reaping the benefits of data sharing, but they will also be able to fight fraud more effectively.
The Way Forward
According to McKinsey, over half of consumers make sure that a company has a reputation for protecting its customers’ data before making an online purchase or using a digital service, and 52% of B2B purchasers reported that they stopped buying from a company when it violated digital trust.
With the recent rise in global fraud, there has never been a better time to harness the power of confidential data analytics and collaborative fraud detection to upgrade financial crime monitoring models.
Confidential computing paves the way forward for financial institutions to make full use of their data while remaining compliant with the stringent regulatory requirements. This empowers institutions with the ability to fully embrace data analytics without the risk of large fines.
Ivar Wiersma is the head of Conclave at R3, a global enterprise technology and services firm.
