Fraud detection is growing exponentially, and with such large sums of money at stake, the reason is apparent. Cyber crime now costs the world almost $600 billion, or 0.8% of global GDP, according to a new report by the Center for Strategic and International Studies (CSIS) and McAfee. It's ironic how cyber criminals are leveraging technology to get smarter and use it for their benefit. Banks and financial institutions must aid their data with technology that will help them secure their data and help them develop their capabilities faster. In 2017, According to Statista, the global FDP (fraud detection and prevention) market was estimated to be worth $16.6 billion.
Why does AI matter?
Digital disruption is redefining the banking industry and challenging the way of conducting business operations. The banking sector is witnessing ground-breaking changes, foremost being the rise in customer-centricity.
However, technology like artificial intelligence and machine learning continue to grow tremendous interest in the banking industry. AI is all about algorithms that can learn new information from the data it collects. The more data you provide to AI, the more it learns, the better it gets and makes life easy for the banking industry. Eighty-five percent of business decision-makers believe AI will add value and advantages to businesses in the future.
Nevertheless, many banks are planning to deploy solutions enabled by AI: 75% of respondents at banks with over $100 billion in assets say they're currently implementing AI strategies, compared with 46% at banks with less than $100 billion in assets, per a UBS Evidence Lab report seen by Business Insider Intelligence.
AI and ML's role in banking industry
AI fraud detection for transactions:
One of the obstacles financial institutions face is the fact that fraud can take any shape and form. Suppose cyber criminals steal a person's credit card information and identity and engage in fraudulent spending. In that case, they may fly under the radar because they're using legitimate card numbers and personal details. Many banks have several false positives per day that typically go under a manual review process. Still, in doing so, the bank risks inconveniencing a customer who is trying to conduct authentic transactions.
ML is being used as a solution to detect transaction fraud before it occurs. This protects customers from fraudulent effects and reduces or eliminates friction for customers whose transactions are erroneously flagged.
AI fraud detection for applications:
Any applications, such as payday advance loans, credit cards and opening a direct deposit account only need a few pieces of personal information. This alone makes it simple to commit application fraud. If a cyber criminal obtains such sensitive data, it becomes easy to create a devastating result for the victim. Research shows that loan fraud is the costliest form of identity theft, averaging about $4 687 per instance.
AI can easily oppose and defeat application fraud by detecting illicit activity early in the process. Algorithms can scan for connections between applications for credit cards and loan applications and monitor newly opened accounts to stop financial damage before it occurs.
AI fraud detection for anti-money laundering:
Money laundering isn't always easy to detect, AI's ability to monitor spending and deposit patterns over time can alert staff to anomalies and block payments before they can be completed. Algorithms can pull from various data points, from transaction origination to the end destination and more, to identify deviations from standard patterns.
Firstly, AI can help ensure that payments are being made willingly by the individual. And secondly, AI can help reduce false positives that could occur with traditional fraud detection methods.
How is Winjit bringing AI to banking?
AI not only empowers banks by automating its knowledge workforce, but it also addresses the whole process of automation intelligence sufficient to do away with cyber risks. AI is an integral part of the bank's processes and operations and continues evolving and innovating with time without considerable manual intervention. AI enables banks to leverage human and machine abilities optimally to handle operational and cost efficiencies and deliver personalised services. By adopting AI, leaders in the banking sector have already practiced actions with due diligence to reap these benefits.
At Winjit, we help business leaders and organisations learn to re-envision the future by embracing and capitalising on emerging technologies. Book a demo to learn how PredictSense works and how it can help you transform your business.
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