By Carlos Somohano, Big Data Evangelist, WHISHWORKS
AI is not a new concept in the banking industry. Even as far back as the 1970s, trading floors have been using automated trading systems, which with the help of complex algorithms, were able to make millions of trades per day – what is known as ‘high-frequency trading’. Still, it took almost three decades to have the computing power and storage capacity to evolve the technology in a commercially viable way.
Fast-forward to today, a recent MarketsandMarkets report states that the market size of AI in Fintech is expected to grow from USD 1.3 billion in 2017 to USD 7.3 billion by 2022
This alone shows that increasingly, financial institutions are understanding the potential of AI technologies and the value it can bring not only to the organisation but also ourselves as their customers.
However, we don’t expect to see any radical change in the near future. At the moment, AI is being used to enhance existing back-end processes and non-AI automations that will provide significant efficiency gains for the operation of the banks with financial performance, risk and costs being the main drivers. In the front-end, we will experience these changes only incrementally, primarily in the form of improved customer experience and transaction security.
Times are changing
Fraud prevention is one of the main areas that banks are investing in. Machine Learning (ML) and Deep Learning (DL), both offsprings of Artificial Intelligence, are being used to improve security by using algorithms to compare vast amounts of data from many different sources and assess the likelihood of a transaction being fraudulent. The difference with the non-AI solutions currently used, is that ML and DL programmes learn and adjust their algorithms according to past outcomes as well as the changing habits of the account owner, achieving higher levels of accuracy.
Graph Analytics is another very important development achieved thanks to AI and increasingly used for fraud prevention. With Graph Analytics banks can analyse data networks and identify activity or relations that may signify the existence of organised crime groups.
AI is also gaining momentum within risk and compliance. With the ever-tightening regulatory environment and directives like MiFID II and Dodd Frank that aim to increase market transparency and investor protection, banks are facing significant fines and reputational damages if they fail to provide evidence. In 2017 alone, these fines amounted to £230 million. AI-based solutions are being used to search and compare both historical and real time data to identify abnormal behaviours and transactions. This way AI solutions act as a prevention mechanism rather than their non-AI counterparts that search only through historical data to produce results after the fact.
Another area where we see increased application of AI solutions by banks is in customer service. Chat bots and conversational interfaces are increasingly used to facilitate the communication process and address simple customer enquiries, reducing customer waiting time to be served, whilst allowing more time for human advisors to deal with complex problems. Even when not used in the front-end of customer service, AI solutions can help financial advisors to make better, more personalised recommendations to customers by weighing previous account activities against current data, significantly reducing the risk of mis-selling.
There are many other tactical processes, where banks are introducing AI-based solutions to optimise processes and reduce risk. Some of the projects we have seen being implemented include Emotion Analytics for Claims Management, Prescriptive Analytics within Management Information Systems, Satellite Analytics for Construction and Property Finance, Document Summarisation for Legal Departments and many more.
Financial fraud last year exceeded £1 billion in the UK, with online banking fraud increasing by 226% and telephone banking fraud by 178% year-on-year. Security and fraud prevention are the areas where we expect to see the biggest positive effects not just for the banks but most importantly the general public. In addition to the anomaly-detection AI-based applications currently used to detect fraud, we start seeing added security measures on the user side, including facial recognition, voice recognition, or other biometric data.
A controversial area for AI has been cyber-crime. Many cyber criminals already use AI thereby having an ongoing advantage as their bots become more sophisticated with every instance making them one of the highest priority threats globally. The cost of cyber-attacks to UK businesses last year was over £40 billion and banks represent a prime target. The cost of cyber-attacks to banks however is much more than the reported figures if one considers the cost of having to shut down operations until the attack is addressed and then get the services back up and running, the cost of upgrading their security measures hurriedly and, perhaps the biggest of all, the reputational cost. To protect their assets against cyber-attacks, banks are now deploying AI to monitor and detect anomalies within their systems and networks and block any abnormal behaviour before it causes any damage. Taking it a step further, today we are also seeing the uptake of Generative adversarial networks (GANs), a class of AI algorithms that use unsupervised machine learning to train two different networks one against the other, an attacking one simulating cyber-attacks and a defending one to protect the bank. The two networks try to outsmart each other and in doing so continuously becoming smarter and more efficient. This way the defending network will be more effective in battling real cyber-attacks.
The robots are coming
As with most technologies, AI is not a revolution; it has been evolving over many decades and it continues to do so as we speak. Today, AI is creating new job opportunities, as new skills are required to develop and manage different AI-based applications. In parallel, as the adoption of AI has been happening gradually, other positions are up-skilling or morphing to include AI components within their particular domain. In the end however, it is inevitable for the need for certain skills to start diminishing and for new roles to emerge.
Having said that, with organisations trying to optimise their operation to remain competitive and profitable, it is important for every one of us to make sure that we too refresh our skills in line with the prevalent trends and technologies within our area of expertise, so we too remain competitive within our organisation and the job market in general.
Iron Mountain releases 7-steps to ensure digitisation delivers long-term benefits
Iron Mountain has released practical guidance to help businesses future-proof their digital journeys. The guidance is part of new research that found that 57% of European enterprise plan to revert new digital processes back to manual solutions post-pandemic.
The research revealed that 93% of respondents have accelerated digitisation during COVID-19 and 86% believe this gives them a competitive edge. However, the majority (57%) fear these changes will be short-lived and their companies will revert to original means of access post-pandemic.
“With 80% still reliant on physical data to do their job, now is a critical time to implement more robust, digital methods of accessing physical storage,” said Stuart Bernard, VP of Digital Solutions at Iron Mountain. “Doing so can enhance efficiency and deliver ROI by unlocking new value in stored data through the use of technology to mine, review and extract insight.”
When COVID-19 hit, companies had to think fast and adapt. Digital solutions were often taken as off-the-shelf, quick fixes – rarely the most economical or effective. But they are delivering benefits – those surveyed reported productivity gains (27%), saving time (20%), enhancing data quality (13%) and cutting costs (12%).
So what now?
The Iron Mountain study includes guidance for how to turn quick-fixes into sustained, long-term solutions. The seven-steps are designed to help businesses future-proof their digital journeys and maximize value from physical storage:
1) Gather insights: The COVID-19 pandemic allowed organisations to test and learn. Companies should ensure these insights are fed into developing more robust solutions.
2) Use governance as intelligence: Information governance and compliance are fundamental to data handling. But frameworks aren’t just a set of rules, they hold valuable insights that can be turned into actionable intelligence. Explore your framework to extract learnings.
3) Understand your risk profile: A key early step is to analyse where you are most vulnerable. With data in motion and people working remotely, which records are at risk? What could be moved into the cloud? Are your vendors resilient?
4) Focus where you will achieve greatest impact: To prioritise successfully, you need to know where you will achieve the largest impact. This involves looking beyond initial set-up costs towards the holistic benefits of digitisation, including reducing time spent on manual scanning, and the risk of compliance violations.
5) Reach out and collaborate: We are all in this together. Your IT, security, compliance and facility management teams are all facing the same challenges. Ensure you collaborate across functions to develop robust, integrated solutions.
6) Find a provider who can relate to your digital journey: For companies that still rely heavily on analogue solutions, digitisation can be daunting and risky. It pays to find a vendor who has been on the same journey, understands your paper processes and can guide you through the digital world.
7) Prioritise and evolve communication and training programmes: To reap the full rewards from any digitisation initiative, thorough and continuous communication and training is critical. Encouragingly, our survey found that 81% of data handlers have received training to work digitally which is an excellent step in the right direction, but consider teams beyond data handling to truly succeed.
The research was commissioned by Iron Mountain in collaboration with Censuswide. It surveyed 1,000 data handlers among the EMEA region. It found that the departments that have digitised more due to COVID-19 include IT support (40%), customer relationship management (36%), and team resource planning (34%).
3D Secure: Why are fraudsters still slipping through the net?
By Tim Ayling, VP EMEA, buguroo
There is a constant tension between keeping online payments secure, and offering an easy and frictionless user experience. Digital transformation – especially accelerated by the global pandemic – leaves consumers expecting online services to be seamless. Customers are even liable to abandon a process altogether if they encounter a hurdle.
Financial regulation and security protocols exist to help ensure that a balance is maintained between offering customers this frictionless experience, and keeping them and their funds safe from fraud attacks.
What is 3D Secure?
3D Secure is one such protocol. This payer authentication system is designed to keep card-not-present (CNP) ecommerce payments secure against online fraud. The card issuer uses 3D Secure when a card is used to pay for something online, authenticating the customer’s identity based on personal identifiers, such as the three-digit CVV code on the back of a card, as well as the device they’re using to make the payment and their geolocation or IP address.
3D Secure is important because although transactions can be accepted or denied based on the level of risk, it’s not always as clear as ‘risky’ or ‘not risky’. A small number of transactions will have an undetermined or questionable level of risk attached to them. For example, if a legitimate customer appears to be using a new device to buy goods online, or appears to be attempting to make the transaction from an irregular location. In these instances, 3D Secure provides a step-up authentication, such as asking for a one-time password (OTP).
Getting the right balance
3D Secure is a helpful protocol for card issuers, as it allows banks to comply with Strong Customer Authentication as required by EU financial regulation PSD2 as well as increase security for transactions with a higher level of risk – thereby better filtering the genuine cardholders from fraudsters.
This means that the customers themselves are better protected against fraud, and the extra security helps preserve their trust in the bank to be able to keep their money safe. At the same time, the number of legitimate customers who have their transactions denied is minimised, improving the customer’s online experience.
So why are fraudsters still slipping through the net?
Fraudsters are used to adapting to security protocols designed to stop them, and 3D Secure is no exception. The step-up authentication that is required by 3D Secure in the instance of a questionable transaction often takes the form of an OTP, a password or secret answer known only by the bank and the customer. However, there are various ways that fraudsters have devised to steal this information.
The most common way to steal passwords is through phishing attacks, where fraudsters pretend to be legitimate brands, such as banks themselves, in order to dupe customers into giving away sensitive information. Fraudsters can even replace the pop-up windows that appear to legitimate customers in the case of stepped-up authentication with their own browser windows disguised as the bank’s. Unwitting customers then enter the password or OTP and effectively hand it straight over to the fraudsters.
Even when an OTP is sent directly to a customer’s phone, fraudsters have found a way to intercept this information. They do this through something called a ‘SIM swap scam’, where they impersonate their victim and manage to get the legitimate cardholder’s number switched onto a different SIM card that they own, thereby receiving the genuine OTP in the cardholder’s place.
This is especially an issue for card issuers when taking into account the liability shift that is attached to using 3D Secure. When a transaction is authenticated using 3D Secure, the liability moves to lie with the card issuer, not the vendor or retailer. If money leaves a customer’s account and the transaction was verified by 3D Secure, but the customer says they did not authorise the transaction, the card provider becomes liable for any refunds.
How AI and Behavioral Biometrics can be used to plug the gap
Banks need to find a way to accurately block fraudsters while allowing genuine customers to complete online payments. AI can be used alongside behavioural biometrics as an additional layer of security to cover the gaps in security through continuous authentication of the customer.
Behavioural biometrics can collect and analyse data from thousands of parameters around user behaviour such as their typing speed and dynamics, or the trajectory on which they move the mouse, throughout the entire online session. AI processes are used to dynamically compare this analysis against the user’s usual online profile to identify even the smallest of anomalies, as well as against profiles of known fraudsters and typical fraudster behaviour. AI then delivers a risk score based on this information to banks in real time, enabling them to root out and block the fraudulent transactions.
As this authentication occurs invisibly, the AI technology can recognise if the customer is who they say they are – and that it isn’t a fraudster trying to input a genuine OTP they have managed to steal through phishing or SIM swapping – without adding any additional friction.
Card issuers cannot decline all questionable transactions without losing customers, while approving them without additional checks poses security issues that can result in financial losses as well as losses in customer trust. Behavioural biometrics is a foundational technology that can work simultaneously to 3D Secure to keep customers’ online payments safe from fraud while maintaining a frictionless experience and minimising the risk of chargeback liability for banks.
Track and Trace and Other Lost Data
By Ian Smith, General Manager and Finance Director at Invu
You, like me, were probably amazed by the now infamous loss of the over 16,000 positive test results in the track and trace system due to an Excel spreadsheet error.
You, like me, probably wondered how the Government could get something so important so wrong?
But perhaps we should ask are we standing in a greenhouse launching stones?
Data risks from software
Today we are spoilt with software offerings that help us with both our personal and our work lives.
Microsoft Excel is a powerful application and offers many functions now that required moderately complex macro writing in the past, seducing all of us into submitting more data for it to analyse. In finance, we tend to solve all those problems our applications cannot address using Excel.
In finance, we also know the risks of formula errors, and if we have relied on it enough, we will have our own war stories to go with these risks. Yet, we often continue to use the tool for operations that make those folks with an information technology background shake their heads.
These Excel files nowadays may find themselves resident on a local file server or one of the many file servers in the cloud (like those from the big three, DropBox, Google Drive and Microsoft OneDrive or other less well-known file sharing applications). Many of us use these in multiple ways.
Beyond finance and Excel, there are now many applications that we run our data through and leave data stored in the form of documents, comments and notes.
The long-standing example is email. We today receive many documents via email, with content in the body often providing context. Email systems then become the store for that data. While this works from a personal point of view, for a business working at scale, the information stored this way can be lost to the rest of the business. Just like data falling off a spreadsheet when there are not enough rows to capture the results.
More recently, we have seen easy to consume applications develop in many areas like chat and productivity. Take for example task management apps, my own preference being Monday.com (I am sparing you the long list of these). The result of the task and how we got there, in the form of attachments or comments, are often stored in the application. Each application we touch encourages us to leave a bit of data behind in its store.
Many of these applications can have a personal use and an initial personal dalliance is what sparks up the motivation to apply the application to a business purpose. Just like the “Track and Trace System”, they can often find themselves being used in an environment where the scale of the operation overwhelms their intended use.
In our business lives, combining the use of applications in this way by liberally sprinkling our data across multiple systems often stored in documents (be they Microsoft Word, email, scans or comments and notes) puts us on the pathway to trouble.
Imagine how Matt Hancock felt explaining to Parliament that the world-class track and trace system depended on a spreadsheet.
Can you imagine a similar situation in your business life? Say, for example, that documents or data in some form was lost because of the use of disparate systems and/or applications that were not really designed for the task you assigned to them.
Who would be your Parliament?
Now you can see yourself in the greenhouse, you may not want to reach for that metaphorical stone.
If these observations create some concerns for you, you may want to consider the information management strategy at your business. You have a strategy, even if it is not addressed specifically in documents, plans or thought processes.
These steps may help figure out where you are and where you want to go.
- Assess your current environment.
Are you a centraliser, with all the information collected in one place? Or is all your data spread across multiple stores, as identified above? Are you storing your key business information on paper documents, or digitally or a mix of both.
- Assess your current processes.
Do your processes run on a limited number of software applications? Or do you enable staff to pick their own tools to get things done? The answer to this question is often a mix of both where staff bridge the gaps in those applications using tools like MS excel. A key application to think about is how the data in email, particularly the attachments, is made available to the business.
- Design a pathway for change and implement it.
Start with the end in mind. I suggest the goal is to enable the right people to have the right access to the information they require to do their job in real-time. I believe the way to effectively do this is to go digital. The fork in the road is then whether to centralise your information store or adopt a decentralised approach.
My own preferred route is to centralise using document management software that enables all your documents to be stored in one place. Applications like email can be integrated with it, significantly reducing the workload required to file and store the data. The data can then be used in business applications using workflows. Thinking these workflows through will help you assess the gaps between your key business applications and consider whether tools like excel are being stretched too far.
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