How Financial Services Companies are Tackling Cyber-Fraud

Blog

Posted on November 4, 2018

Cyber-criminals continue to evolve with tricks and turns aimed especially at financial transactions. Incidents, like the WannaCry and Petya ransomware scams, also indicated continuous vulnerabilities in worldwide financial online security, costing banks and FIs about USD 360 billion yearly in the last three years, the Global Banking and Finance Review states.

The first half of 2018 saw 81 million cyberattacks launched at FIs, 27 million of those attacks were targeted at mobile channels. Device spoofing and attacks from mule networks were found to be the major global threats. In addition, increase in mobile device usage across the globe saw 170 million bot attacks, a new report shows. It has become important for FIs to continue to enhance their capabilities to keep pace with the ever-changing threat landscape.

Strong Authentication is known to safeguard against Fraud. Bank customers can utilize two-factor authentication systems, like JETHRO’s jPRIVACY.

Strong Authentication is known to safeguard against Fraud. Bank customers can utilize two-factor authentication systems, like JETHRO’s jPRIVACY. A recent survey indicated that more than 70 percent of banking customers prefer authentication methods that are easy to use, while 45 percent say they prefer strong authentication method for data security. FIs would need to strike a balance between simplicity and security. jPRIVACY is an effective and easy to use two-factor authentication system for your enterprise.

Security In Payment Card

Mastercard recently introduced digital commerce solution suite to protect stored card credentials via advanced authentication that enhances customer experience. The payment multinational is working with its financial partners to convert cards on file into tokens that will ensure simple, seamless and secure online transactions. Tokenization provides a layer of security that enables card credentials to be stored with merchants or retailers without revealing the card account details. Mastercard plans to enable tokenization on all cards by 2020.

Similarly, VISA, multinational payment company revamped its online fraud mitigation strategies that include:-

Incidence analysis:-VISA, together with its affected merchants and banks, immediately examine the impact of the attack and lessons are learnt.
Online Tracking:- It tracks the criminal online to identify susceptibility points and measures that will ensure the situation does not happen in the future.
Collaboration:- The payment multinational also work with law enforcement agencies to ensure threat mitigation.

In an instance, VISA utilized digital fingerprints to locate cyber-criminals at their hideouts. However, an ideal situation would be to intercept fraudulent transactions before they occur.

Two Bank’s Fraud Tackling Strategy

Silicon Valley Bank is using Artificial Intelligence and Machine Learning to swiftly analyse enormous amount of data to detect fraudulent transactions and activities of fraudsters. Customer conduct and profiles are consistently analysed to identify suspicious patterns. Strong firewall is also being used by the bank to safeguard customer and bank records from cyber-criminals.

Similarly, Royal Bank of Canada invested in AI and ML to build online customer profiles to fight fraud. Its approach is to utilize AI, ML, neural networks and other innovations to secure customer data to swiftly analyse enormous amount of data to detect fraudulent transactions and activities of fraudsters. Customer conduct and profile are consistently analysed to identify suspicious patterns. Strong firewalls is also used by the bank to safeguard customer and combat fraud. Emerging technologies also enable RBC to offer customized solutions and suggestions to customers.

AI and ML use cases can be employed by banks to prevent fraud and ensure risk reduction. The GARRP survey found that 88 percent of FIs executives agree that AI and ML acquisition can ensure innovative change in risk management as it is able to identify suspicious transaction, a new PYMT report states. Synchronizing Mobile location with credit card data to confirm if the right customer is making a transaction and customer creditworthiness analysis are some instances of AI and ML use cases that can combat fraud.

However, collaboration between FIs will enhance the effectiveness of AI and ML security systems that rely on information aimed at detecting suspicious attacks in real-time. Collating customer data from multiple interactions and transaction channels will expand the capacity of intelligent security systems. New attack would require corresponding new security solution layer to be in place together with efforts of cyber-security professionals.

Security In Payment Card

Two Bank’s Fraud Tackling Strategy

Industries

Solutions

Contact Us