We live in an age where instant gratification is now the rule, not the exception. With the advent of artificial intelligence (AI) like Siri and Alexa, we have instant answers and information at our fingertips. Ankush Singla, Senior Product Manager at DefenseStorm, explores six undeniable ways AI is creating transformational change in the finance sector.
New generations thrive on instant responses and the ability to complete tasks at the push of a button. As technology makes even the simplest tasks easier, we want more. Surprisingly, the banking sector followed this trend By providing latest technology to its customers for easy access and convenient banking. As financial institutions (FI) revolutionize the industry with the latest technology, cybercriminals are ready to exploit new vulnerabilities due to increased usage.
So, how can banks and credit unions stay competitive while offering superior security to their customers? Using AI for cybersecurity gives FIs a way to more effectively scale insights from data. By applying this technology, your financial institution can respond quickly to breaches, but, most importantly, stay ahead of cyberattacks. The use of AI can also significantly help FIs prepare for changes in risk and compliance.
Six Benefits of AI/ML for Financial Institutions
Consider six ways AI/ML can effectively help your financial institution to manage its own risk profile, Monitor Changes to internal key metrics, improve security posture and Manage consent
1. Spot the fraud Before The money will leave the account
In 2021, Javelin Strategy & Research Identified Identity fraud scam losses totaled $28 billion, victimizing 27 million US consumers. Financial institutions should stop fraudsters before they make transactions because it prevents financial losses and maintains a loyal client relationship. FIs usually bear the cost of losses, but in some cases, banks are not liable. Sometimes, customers bear the loss, which affects the fiduciary relationship between FIs and their clients. By implementing AI, especially products designed for banking,
FIs can close the gap in detecting and stopping violations before they occur. Sifting through millions of cyber events for an average client (and many more for large organizations) is virtually impossible, even for the most critical and skilled teams, and AI can create a baseline of transaction patterns and identify anomalies as a proactive approach.
2. Reduce false positives
As the overuse of technology and the threat of cyberattacks continue to be in constant neck-and-neck competition, enter another contender: false positives. When SOCs (Security Operations Centers) analyze millions of online events for threats, more than half are identified as “non-threat.” False positives can wreak havoc on a company’s SOC budget, reducing time and efficiency. By reducing false positives with AI, we rely less on staff and those valuable human resources can focus on investigating real and complex threats. The frequency and volume of false positives is steadily increasing, but smart implementation of cybersecurity technology can help reduce the barrage of alerts. ML helps decipher between a real threat and a benign one. According to Forbes, “It Accuracy translates to two higher levels of protection Real threats are immediately deterred and alerts generate only merit action, with greater efficiency.”
See also: Is cybersecurity the biggest challenge facing fintech companies today?
3. Effectively address control change management
Financial institutions are bombarded by ever-changing regulations, so the use of a manual system for forecasting and execution has become ineffective. FIs spend hours not only reading and understanding the new regulations, but also making the necessary changes. ML has paved a new way to address constant changes in regulation. As financial institutions are subject to penalties for non-compliance, it is critical to use a more expeditious approach.
Intelligent Process Automation (IPA) is used to assess large amounts of data quickly, accurately and in real time so your financial institution stays in compliance. According to Data Bricks, automating the control change management process is a A key use case of AI. Financial institutions’ challenges with successful AI implementation will be addressed, including heavy penalties for non-compliance. Combining this technology with the knowledge of people who understand the critical demands of the FI industry leads to superior results.
4. Increase unusual recognition
Regularly evaluating transactions for odd behavior is a difficult and time-consuming task. However, FIs must recognize any deviation from the norm as even the slightest can prove to be a detrimental threat. AI can analyze large amounts of data to establish common transaction patterns and help identify anomalies that may indicate a cyberattack threat. AI can scan large volumes of different types of data to detect irregularities in learned algorithms. Then, adjustments are applied after distinguishing between normal and abnormal behaviors to consistently detect and predict fraudulent activity. AI is also effective at finding anomalies that are missed by a one-size-fits-all rules-based approach to fraud detection. For example, customers who deviate from expected “normal” banking practices may be frustrated by having their accounts flagged or blocked. There is nothing more irritating than being locked out of your account for paying bills at 2am for not fitting into normal “banking hours”.
With AI, accounts are continuously and automatically monitored, enabling FIs to provide a higher level of protection while tailoring security to customers’ specific needs, ultimately avoiding these irritating red flags.
5. Reduce human error
Human error is a hurdle every financial institution faces. In one of the largest studies assessing breaches among 130 clients, the IBM Cyber Security Intelligence Index reported, “Human error is the primary cause of 95% of all breaches.” Whether it’s an error in data analysis or a mistaken click on a phishing email, every breach exposes your company to a breach. Financial institutions can use an AI system with a SOC team that monitors for alerts and analyzes threats for fraud, risk and compliance to reduce workload and become more efficient. Automated systems are the first line of defense with capabilities beyond the limits of human capabilities, reducing the incidence of errors..
6. Increase competitive advantage
FIs are always competing to provide the best and most efficient services in their industry. Fintechs are setting new standards with their use of technology to deliver a high-caliber customer experience. Ernst and Young Consumer Financial Research It shows that more consumers today consider a fintech firm than a bank as their most trusted financial brand. Traditional banks “keep up with the zones” by implementing the latest and greatest technology to provide faster and easier everyday banking. To remain competitive, FIs must also ensure that their customers protect their data and money using the highest level of security. Built specifically for banking, AI cybersecurity products that reduce risk, fraud and compliance provide tailored and industry-specific protection tailored to your FI’s unique needs.
The future of AI in financial institutions
As we continue to conduct businesses with more advanced technology, financial institutions are fighting against malicious activity. The future of FI is to use this new technology not only to facilitate day-to-day operations but also to provide a higher level of protection.
With the ever-changing world of security, risk, fraud and compliance, the financial sector needs FIs to stay current and competitive. Artificial intelligence is a way to revolutionize the way banks and credit unions provide security to keep their customer’s assets and data safe.
Which of the stated benefits of AI/ML have you been able to leverage? Share with us Facebook, TwitterAnd LinkedIn.
More on AI in Finance:
Image source: Shutterstock