Dave Excell, Founder & CTO, Featurespace
Artificial intelligence (AI) is fast becoming the defining technology of our age. As with any new technology however, bad actors are equally adept at harnessing its power for their own nefarious ends.
The power of AI has seen fraudsters increasingly able to penetrate banking and payment systems. As in any conflict, there is an arms race between the defenders and attackers developing. In the case of card fraud, fortunately the defenders are winning.
Financial Fraud Action UK figures for 2017 published last month have shown the defenders are valiantly winning the fight, with the total value of unauthorised fraudulent payments on cards, remote banking and cheques falling by 5% to £731.8m – despite the gross number of attempts rising 3%.
So the arms race is on. The only way for us to beat the crooks is to continue to develop our own smart AI weapons to continue to stay one step ahead and begin to turn the tide on fraud.
AI is the new weapon of choice
Algorithms have long been used by fraudsters and hackers to even the odds against defender’s systems. By using AI, the time required to test large quantities of data and probe defences has reduced significantly.
AI is used by fraudsters in a variety of ways but two of the most common are Credit Master and Authorisation Manipulation attacks.
Credit Master attacks
One way in which fraudsters use AI is in so-called ‘Credit Master’ attacks. Algorithms are deployed which automatically generate credit card account numbers from an existing correct number as well as pairs of expiration dates. The criminal software then automatically tests these combinations, working sequentially through number combinations to see which match genuine cards by attempting a transaction. It’s simple trial and error.
Sequential number Credit Master attacks have existed for a long time but increasingly fraudsters can use AI to automate the process of testing mind-boggling amounts of numbers at the speed of computer processors. This fully automated process allows fraudsters to test thousands upon thousands of prospective number combinations at a far greater rate than would be possible with methods that require human input.
Fraudster’s attacks are becoming more nuanced, using AI to test many account numbers in random, rather than sequential configurations (sequential is more easily detected by existing fraud solutions). AI technology can also vary the rate at which numbers are attempted, either hard and fast, overwhelming detection or slow and steady, so the attempts do not seem like the same attack.
When one of the tested combinations proves to match an existing card, the fraudster can then use the details in further attacks to steal money from customers.
As fraudster’s technology improves its efficiency and speed, there is increasing load placed on bank systems to detect these fraudulent transactions.
In an Authorisation Manipulation attack, a fraudster presents themselves as a valid merchant through access to a payment terminal, either with a physical chip and pin/swipe machine or online terminal. Payment terminals can be obtained in a variety of ways, for example through taking over an existing account that has access to a terminal, via collusive merchants or by applying for one fraudulently.
When a transaction is put through a payment terminal, various different pieces of information are sent to the bank which, when validated, authorises money to move from a bank account to the merchant (or in this case fraudster).
The fraudster aims to force payments through this authorisation process by providing information to the bank which fits enough criteria for the bank to authorise the payment.
AI is now being used to test many different iterations and combinations of card numbers, customer information and purchase details through a bank’s authorisation process, learning which details have to be valid for a fraudulent transaction to be authorised.
AI allows fraudsters to test many more different combinations at a much higher rate than would otherwise be possible and to learn and adjust methods automatically based on which attempts are successful.
Much like an invader testing a wall’s defences, Authorisation Manipulation attacks find out exactly where weak points are and through a process of elimination will find the gaps in a bank or payment provider’s defences. The fewer valid details an attacker needs to successfully authorise a payment the more efficient fraudsters can be in their attempts.
A new weapon in the war against fraudsters
Using cutting edge technology, banking and payment providers are now able to foresee fraudulent transactions and stop them in their tracks. Rather than relying on static rules or models to detect fraud (that fraudsters can test and learn to defeat), advanced AI solutions are now analysing customer behaviour to provide a real time dynamic defence.
Existing rules or static model based systems are getting out-classed by fraudsters because they aren’t able to learn. When a static fraud system is being exploited, it isn’t able to detect whether or how fraudsters are getting through and isn’t able to seal the gap in its defences.
The subtle art of spotting a fraudster in the act
Fortunately, while AI is becoming more commonplace amongst fraudsters, banks and payment providers are employing ever more advanced AI to protect customers.
Using the very latest in machine learning technologies, the defenders are trying to spot the fraudsters in the act. Instead of trying to notice things that might be ‘wrong’, smart tech can now intuitively ‘know’ a real customer from a crook.
Featurespace’s real time machine learning platform is able to understand the behavioural traits of real customers, learning each individual’s characteristic traits. This is done by spotting the variance from the individual’s normal behaviour. This can be as subtle as the rhythm in which a customer typically enters their password, their preference for key strokes, or how they use a mouse.
It can also be learning where a person is likely to go and what they might spend. This kind of intuitive learning means fraudsters with stolen card information can be picked off in real time.
In the perpetual arms race between financial criminals and the defenders of customers, AI provides tools for both sides, but by using the latest machine learning technologies the defenders are winning the race.
What does cybersecurity look like for the financial sector in 2021?
By Neill Lawson-Smith, managing director at CIS
The landscape is changing incredibly fast, with cybercriminals using the most up-to-date technology to hack systems. Here are the six areas those in finance should be watching out for…
The finance and insurance sector is increasingly becoming a notable target for cyber attacks. Many of these breaches happening are believed to be due to inadequate security measures when teams or businesses are using cloud services.
The financial industry is also being affected by changes in processes with more fintech, virtual banks, and other digital disruptors impacting the market. The landscape is changing incredibly fast, with cybercriminals using the most up-to-date technology to hack systems, so it is therefore up to the financial sector to keep up to avoid security breaches.
What does this look like for the year ahead in the financial sector? Here are the Six areas those in finance should be watching out for:
- AI securityand cyber defence
Both Cybercriminals and cyber defence are commonly using Artificial Intelligence (AI). In cybersecurity, it is used to identify new threats, as well as assess the effectiveness of the responses to threats, enabling them to foresee and essentially block attacks before they happen. It is also used to spot behavioural patterns and can quickly identify possible infiltrations.
Hackers have also started to use AI to make it easier for them to get past security systems in place. This year, it is likely that AI will be increasingly used as a means of gaining personal details (i.e. credit card details) as well as optimising spam phishing campaigns.
- Mobile cybersecurity in banking
With the number of consumers using their mobile devices for banking and financial transactions increasing, especially since the COVID-19 pandemic has rendered society predominantly cashless, cybercriminals have been heavily targeting mobile systems. For example, mobile malware only targets mobile phone operating systems. The most common forms of mobile malware are virus and trojans, spyware and madware (mobile adware), phishing campaigns, and browser exploits.
This means it is now more important than ever to protect mobile devices to the same extent as traditional hardware.
The same protocols that are in place to ensure your staff PCs and laptops are secure now, need to also be applied to their mobile devices as well, such as:
- Ensuring the latest versions of the operating system and other applications are installed.
- Installing a firewall.
- Enabling mobile security software to protect against malware and viruses.
- Using password protected lock screens.
- Ensuring apps are only downloaded from official sites like Apple App store and Google Play.
- Multi-factor authentication
Multi-factor authentication adds an extra layer of security to all your business networks by ensuring every transaction or login is supported by at least two security measures for access. It is one of the easiest security measures to implement within your business and is becoming more common within the financial sector for many transactions. The traditional username and password are becoming increasingly easy for cybercriminals to acquire, whereas adding an extra identification method, that is not easily accessible to the hackers, ensures an extra layer of protection.
The most commonly used multi-factor authentication methods are:
- Passwords – They should be complex and comprise at least eight characters and be a combination of upper- and lower-case letters, numbers, and special characters.
- One-time use code – A randomly generated code sent via SMS or email which is used only once. With weaknesses in mobile networks and email accounts, these can however be intercepted by hackers.
- App generated codes – a code generated by an app on a mobile phone often created by scanning a QR code that contains a ‘key’. As the key is stored on the phone itself this is less likely to be intercepted by a third party.
- Physical authentication keys – this is a USB which the user inserts every time they login from a new computer. Unfortunately, they don’t work on all devices without adapters (such as iPhone, MacBook or Android).
- Biometrics – Using a fingerprint, voice, or an eye dent is an effective identifier. They are extremely difficult to hack but if they are, they cannot be used ever again for anything.
- Information – this could be something that only the user would know – either a password or a piece of information.
Most of these methods are free or relatively cheap to implement and don’t require anything other than a mobile phone for the user. The added security of multi-factor authentication means even if a hacker has acquired a username/password combination there is still an extra security barrier preventing access.
- Refined testing
As the finance industry is constantly changing, then so too are the security threats. Financial cybersecurity is an ongoing commitment, so installing new anti-virus software and implementing MFA, and stopping there is not going to keep you protected for long. It requires ensuring software and firewalls are up to date as well as ensuring access is regularly updated. In addition to this constant maintenance regular testing of the systems is essential. All systems have vulnerabilities, and as these change, cybercriminals learn to overcome them, and therefore software develops.
One thing to remember is that it is not possible to be over-cautious when it comes to cybersecurity. Regular penetration testing essentially identifies any weaknesses in your systems before the cyber criminals do. It is essential to schedule penetration testing or vulnerability scans at least once a quarter unless compliance dictates otherwise. They can be carried out using a vulnerability scanner.
- Hiring the right people
It is crucial to have the right team on hand to ensure your systems are up to date, regularly tested and maintained is essential.
Your IT team should have the following skills and knowledge:
- Knowledge and understanding of the company’s IT infrastructure
- Knowledge of cybersecurity best practices
- Understanding of company processes and data flows
- Up to date knowledge of cybersecurity solutions
- Plan a Defence, Prepare for Attack…
Although businesses can take many precautions, there are limitations on skills, investment and timescales in implementing a comprehensive cybersecurity infrastructure, it is essential that appropriate procedures, policies and processes are established to ensure that an appropriate response is carried out in the event of a detection – whether manual or ideally automated – so that whenever an attack occurs, the appropriate and proportionate response is carried out immediately to limit any further damage or intrusion.
Data protection: it’s time to reassess your security strategy
By Tony Pepper, CEO of Egress
It’s no secret that the Covid-19 pandemic has created a perfect storm of cybersecurity risk. External threats are heightened, but there’s also a higher level of internal risk too, exacerbated by home working. With most financial services organisations planning to continue with mass remote working for the foreseeable future, it’s important for security teams to review their strategy and assess whether it still works in this new landscape. When it comes to insider threat, there are three key areas that IT leaders should focus on: building a positive culture around security, understanding their organisation’s level of risk and protecting their people.
- Build a security-positive culture
Many organisations have unknowingly instilled a security-negative culture among their employees, where people are punished or shamed if they cause a security incident. While they might think that this would discourage employees from causing data breaches for fear of repercussions, this actually makes your organisation less secure. Our Outbound Email Security Report found that 62% of organisations rely on their people to report email data breach incidents – and if employees are too afraid to come forward, that means your business is at risk of developing a security blind spot.
A security negative culture won’t actually prevent data breaches caused by human error, something which organisations need to recognize as largely unavoidable without technological intervention; it just delays remediation, which makes every incident worse. By creating a security-positive culture, you can better engage and educate employees, as well as ensure you’re able to rapidly triage any incidents if they occur.
- Understand your risk
When mapping out your risk, you’ll likely find that the picture looks very different to how it did even a year ago. In the past, organisations have focused on their networks and their devices when it came to security strategy. While these are vital areas for consideration, what hasn’t been as well-addressed to date is the human aspect of risk, particularly human error. You need to look closely at the tools that your employees are using daily to facilitate digital communication with clients and colleagues, including when sending sensitive information.
Employees are specifically using email more than ever before – our recent research found that 94% of organisations are sending more emails due to Covid-19, with one-in-two IT leaders reporting an increase of more than 50%. With this expansion of email volumes comes an increase in the risk that an email containing sensitive data might be misdirected. Remote working has also heightened the threat – our research found that 35% of organisations’ serious email data breaches were caused by remote working. Why? The causes lie in their behavior and the environments in which they operate. Some individuals may feel they’re able to take more risks away from the “watchful eyes” of their Security team, and every employee is faced with a myriad of distractions that make them more likely to make a mistake.
It’s time for organisations to take stock of their risk by looking at where gaps in their security might exist – and provide safety nets for their employees that can automatically detect and mitigate inadvertent data breaches and risky behaviour.
- Protect your people
It goes without saying that not all data breaches are caused by malicious activity. An overwhelming amount of data breaches are caused by hardworking employees making honest mistakes, from sending an email to the wrong person to responding to a phishing attack. Unfortunately, human error is an unavoidable part of life, and mistakes will happen. In the past, many organisations have taken the approach that employee error can be ‘trained away’, embarking on comprehensive security training programs in the hope that security incidents might decrease.
Unfortunately, if that were the case, then employee activated data breaches would be a thing of the past! Organisations need to employ a multifaceted approach when it comes to avoiding accidental insider data breaches – education and training remain an important element, but ultimately businesses need to implement the right technology to provide a safety net for their people. Many organisations have legacy DLP solutions in place that cannot mitigate the risk as they fail to fully understand employees’ behaviour.
Often, these tools stand in the way of productivity, prompting users even when there isn’t a legitimate risk. When click fatigue sets in, these solutions become ineffective, with users ignoring prompts whenever they appear. Luckily, advances in machine learning mean that there’s technology available to prevent insider data breaches such as misdirected email, by deeply understanding the way that users behave and the context in which they share data, to ensure emails are sent to the right recipients with the right level of security.
The vast majority of organizations will never go back to every employee working full time within the office environment, instead post-pandemic we will see a myriad of different approaches – with some based in the office, while others work at home part or full-time, and as the world opens up again, their locations may change throughout the day. To mitigate risks from inadvertent errors to intentional data exfiltration, CISOs must address their security culture and protect their human layer with intelligent controls that mitigate employees’ behaviors and stop breaches before they happen.
Sumitomo Life Insurance Selects Talend to Build Company’s Data Infrastructure
Leading life insurer uses Talend in data lake environment for data analytics
Talend (NASDAQ: TLND), a global leader in data integration and data integrity, announced today that Sumitomo Life Insurance Company, one of the Japan’s leading life insurance companies, has selected Talend Data Fabric for its data analytics infrastructure.
Sumitomo Life aims to become the most trusted and supported company by its stakeholders, including its customers, and to grow sustainably and stably. Sumitomo Life’s vision is to offer advanced products to enable customers to live vigorously. To respond to that, the company is developing and delivering cutting-edge products that respond to its customers’ current and expected futures needs in areas focusing on nursing care, medical insurance and retirement planning.
“With the trust from our customers as the starting point of all our activities, Sumitomo Life is providing optimal life insurance services to every person through the sound management of the insurance business,” said Mr. Masakazu Ohta, General Manager in Charge of Information System Department at Sumitomo Life. “As a new approach, it was necessary to build a common foundation for big data management, and Talend is the driver. Talend’s superiority in cloud implementation, development productivity, features, and licensing model convinced us to be part of this journey together.”
To meet the needs of its customers and offer them innovative products and services, Sumitomo Life has decided to build a foundation for data analysis (Sumisei Data Platform) in the cloud for the promotion of new insurance products. The company evolved its legacy data environment to the new environment where they can store the data extracted from various systems both on-premises and effectively in the cloud.
In order to meet the needs of each individual customer and provide the best insurance for them, Sumitomo Life uses Talend Data Fabric as the hub of its data infrastructure. This manages data across the organization and integrates data into a data lake, which makes them able to utilize data across the company.
“We have been able to release projects with the continuous support of Talend, even amid the changing business environment in the Covid-19 crisis. We will continue to collaborate with Talend in order to actively promote company-wide data analysis projects,” added Mr. Ohta.
“The insurance market is one of the most competitive sectors. By facing tight regulations and complex customer needs, companies must be at the forefront of innovation to offer even more services and new products to its customers,” said Kenji Tsunoda, Country Manager Japan, at Talend. “Talend helped Sumitomo Life reinvent its data-driven infrastructure to provide a data management platform that enables the development of advanced products for its customers. We are delighted to support Sumitomo Life in the pursuit of their vision.”
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