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The continual growth in online fraud has led to a shift in Financial Services and Telecommunications business priorities. Experian’s latest research report shows that nearly 3 in 4 senior decision-makers are now prioritising investments to improve protection against fraud. This illustrates the severity of the fraud threat as more organisations find it necessary to look for new solutions to this problem.
The same survey shows that 73% of respondents consider improving customer experience just as necessary in addition to tackling fraud.
Fraud checks often have a negative impact on customer experience and conversion rates. Technology offers the opportunity to address both problems. The advanced analytical capabilities provided by Artificial intelligence (AI) and Machine Learning (ML) are creating new opportunities for organisations to enhance the way they combat fraud and improve their customer journeys. These innovative technologies are already having a considerable impact with 62% of the survey respondents saying that AI and ML are radically changing the way they do business.
Reducing fraud and meeting customer expectations
As digital adoption continues to expand, there is a corresponding increase in customer expectations for fast and simple application journeys. The research highlights the fact that a simple application process is the second most important factor for consumers looking for a loan or credit card.
A simple application journey is, apart from the cost of borrowing, now more important than ensuring affordability, the security of the provider and the speed of access to the funds. This indicates how critical a simple customer application is for businesses to drive conversions and stay competitive.
According to 43% of the surveyed consumers, an online application was inconvenient if there were too many fraud checks. The negative impact of a slow application journey can even be significant to revenue growth. Finding the right balance between adequate fraud prevention and rising customer expectations is challenging for many organisations.
The research also indicates that around half of the surveyed businesses are responding to this challenge by increasing their year-on-year budgets for fraud prevention, advanced analytics and digitalisation of their customer and internal processes. Investment in these areas should provide substantial ROI with a reduction in fraud losses and growth in new customers.
Technology is driving change with innovative solutions
The pace at which AI and ML are being adopted is a good indicator of the impact of this relatively new technology. Just over half of the surveyed businesses (53%) have already invested in ML with nearly a third (31%) planning to invest in the next twelve months. AI has a similar level of adoption with 61% having already invested and 27% planning to invest in the next twelve months.
The top three use cases for AI and ML are data management, fraud risk decisioning and credit risk models. In each of these cases, both AI and ML are driving a step change in the capability of organisations to analyse and interpret data. This allows them to create, test and deploy new models in far less time than what was previously possible. This is particularly relevant in mitigating the threat of fraud where ML allows businesses to continually adapt to the latest fraud patterns without manual analysis from fraud teams.
The uptake of cloud computing shows that the integration of AI and ML requires considerable computing power. Cloud solutions enable businesses to scale more easily with 76% of the business respondents saying that the flexibility and scalability of cloud computing was an important reason for investing in this technology.
Using AI and ML to improve the accuracy of credit application decisions or online purchases allows businesses to increase automation and therefore streamline their customer experience. It means less customers are incorrectly rejected, whilst also lowering the number of cases sent for manual review – allowing for faster decisions for the customer.
An automated AI future
With annual fraud losses sharply increasing the use of ML is fast becoming an essential tool to combat fraud. By adopting the latest technology businesses can keep pace with a constantly evolving fraud threat while improving their customer experience at the same time.