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AI for Cyber Security: How Do Banks Cope With Financial Frauds & Cyber Attacks
- By Elite CIO
Oct 10, 2019
10
AI for Cyber security: How Do Banks Cope With Financial Frauds & Cyber Attacks
Hackers are cyberattackers who use radical approaches to break into the digital networks; theyhave also begun employing techniques of artificial intelligence to bypass detectionsystems.
Cyber threats can nowjeopardize business networks at a tremendous rate than ever done before, and cyber security analysts alone may find it challenging to react moreexpeditiously to such widespread threats. As such, banks may require to upgradetheir safety arrangements to keep up with the landscape shift.
Banks will loseboth cash and their banking permits if they accidentally promote fraud andmoney laundering or if a cyber attack endangers their digital infrastructure.Most importantly, banks stand to lose their reliability in the market, thushampering future customer acquisition and retention.
The Global Banking &Finance Review asserts that cyber attacks account for nearly $360 billion inlosses annually or over the previous three years. Global ransomware attackslike WannaCry have been continuously putting financial institutions on theverge in the latest few years. No wonder, many banks are now investing inartificial intelligence to fight hackers.
Why Financial Institutions Do not Permit AI Firms To Market TheirAI-based Banking Solutions With Bank Case Studies
Cheating and cyber security as a category scored just one on its Average Evidence of AdoptionScore, showing that banks and monetary institutions are unlikely to permit vendorsto address fraud and cyber security in case studies and press releases. It ismajorly so because of the following reasons:
- It could jeopardize their safety. If a hacker knows what cyber security software a bank is using, they may find it easier to figure out how to crack it and access control.
- When a bank discusses its efforts in the field of cyber security, it indicates that the bank needs to invest in cyber security, meaning that they are under attack— This might scare customers who don't want to hear that hackers are continually threatening to steal their information.
That said, AIvendors endeavoring cyber security programs to the financial institutions raiseda collective $760 million, the highest among all functionalities and nearly$300 million higher than the total funds raised by the field occupying thesecond position, i.e., compliance.
What this impliesis that even though big banks don't promote their cyber security AI schemes asmuch, financial institutions and venture capitalists see it necessary to deployAI-based cyber security.
Some of the mostpopular applications for AI in cyber security processes being used at financialinstitution are based on the following AI approaches:
- Anomaly Detection
- Natural Language Processing
Anomaly Detection for Cyber security in Banking
Anomaly detectionis an AI strategy that can help classify variations in real-time from theregular activity of a system, making it a highly useful cyber security approach.
Some cyber attacks,such as attempts at phishing on corporate operations, may endanger theorganization's specific user accounts. Such assaults are often hard to identifyand counter, largely because the hackers get valid access to the companynetwork once a user account is compromised.
In such circumstances,AI software can be programmed to identify behavioral patterns in the system foreach user account or device. If hackers manage to breach a user's account, theway they use that account is likely to differ significantly from thatparticular user's normal behavior.
Some of the popularAI-based programs working on Anomaly Detection strategy are listed asunder.
- Darktrace
- Versive
- Feedzai
Natural Language Processing forCybersecurity in Banking
Phishing is a typeof cyber attack where fraudsters could compromise user accounts in an enterprisenetwork through email communication. Thus, it becomes crucial for enterprisefirms to monitor the entry and exit of every email communication.
The volume ofemails exchanged every day through an enterprise network could be enormous, andit could be challenging to scour through each of these emails manually in anattempt to find potential threats.
Natural languageprocessing (NLP) could assist financial institution's cyber security teamsautomatically read through large volumes of emails and distinguish the sectionsof the text in emails that could intimate attempts at phishing. AI is suitablefor this task and can increase banks ' ability to manage data examination on alarge scale.
AI software can be instructedto flag emails that seem questionable for further evaluation using inputs from cyber security specialists. The AI algorithms can learn to recognize thesewarnings over time better, allowing human experts to concentrate on fewer, moresevere cases that might require more involvement.
Some of the NLPbased AI systems include:
Cyber security Future In Banking Sector
The industryexperts we spoke to for our report agreed almost collectively that in thefuture of fraud and cyber security, AI would play a significant role.Traditional rules-based systems are unable to account for new cheating methods,and even the enemies are beginning to use AI to hack into systems. As such, theuse of machine learning may be necessary for banks to battle fast evolvingcyber menaces.
AI approaches such as NLP and Anomaly detectionare perfect for large-scale data handling, which humans certainly can't managealone through manual approach— This makes AI a vital tool for banks ' cyber security teams to consider seriously in the near future.