Most organizations and financial institutions (FIs) have been impacted by the growth of fraud, and many are striving to find solutions to the more sophisticated criminal attacks.
While the poll showed that FIs using AI-powered anti-fraud and anti-crime solutions saw reduced levels of loss from fraud and crime, it also showed that 66% of executive respondents find it difficult to comply with complicated regulatory requirements. Although 85% of anti-money laundering (AML) executives find it challenging to integrate new solutions into their current systems, 95% of AML executives place a high priority on innovation.
“The State of Fraud And Financial Crime In The U.S.” investigates how FIs are affected by fraud and other financial crimes and how they defend themselves from more complex attacks. The study was performed between April 29 and June 3 and involved 200 executives who work for financial institutions with at least $5 billion in assets.
Innovation is constrained by a fear of complex solutions.
According to research, financial institutions (FIs) adopting current anti-fraud and anti-crime solutions evade the greater financial loss suffered by those using older techniques. However, several FIs are unwilling to update their strategy. Worse, because criminals are ramping up the intensity and scale of their financial attacks and, in some cases targeting customers directly, many FIs, even those with comprehensive anti-fraud and AML strategies, may struggle to avoid pervasive losses without a modern tech solution.
Although the need for modernization would appear to push FIs to immediately change their strategy for protecting their company, many still favor using outdated technology despite the danger.
According to the survey, the most contemporary types of financial crime, such as scams posing as approved payments or new money-laundering techniques, frequently defy traditional defenses. This is why many executives are delaying the implementation of solutions due to the growing flood of fraud. However, research demonstrates that businesses may effectively counter these attacks by utilizing real-time data and analytics powered by machine learning (ML).
Smaller FIs are more severely harmed.
According to the research, fraud and other financial crime assaults frequently target smaller FIs. Because of this, they are not only more vulnerable to losses but also more likely to sustain a financial injury, which they are less equipped to handle due to their small.
We discovered that financial crime increased for 62% of all FIs, and for an even higher percentage of smaller FIs—those with between $5 billion and $25 billion in assets—as well. Additionally, it was more probable for smaller FIs to have seen a rise in the dollar amount of fraudulent transactions.
According to the research, fraud and other financial crime assaults frequently target smaller FIs. Because of this, they are not only more vulnerable to losses but also more likely to sustain a financial injury, which they are less equipped to handle due to their small.
We discovered that financial crime increased for 62% of all FIs, and for an even higher percentage of smaller FIs—those with between $5 billion and $25 billion in assets—as well. Additionally, it was more probable for smaller FIs to have seen a rise in the dollar amount of fraudulent transactions.
