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HARNESSING ANALYTICS IN THE FIGHT AGAINST FRAUD

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ANALYTICS

By Anna Lykourina, EMEA Fraud Analytics Expert at SAS

 

In the past, the fight against fraud has been a bit hit-and-miss. It has relied on auditors to identify patterns of behaviour that just didn’t quite fit. They often only detected problems months after the event. And then organisations had to claw back stolen funds through legal processes.

In a world where transactions happen in under a second, however, this is no longer acceptable. We need to be able to detect fraud immediately, if not before it happens. Customers want safe and protected data that is not vulnerable to identity theft through company systems. But they still want to be able to pay online and in seconds. The stakes are high, but fortunately new tools and techniques in fraud analytics are enabling companies to stay ahead of fraud.

 

Trusting machines to do the work

Machines are much better than humans at processing large data sets. They are able to examine large numbers of transactions and recognise thousands of fraud patterns instead of the few captured by creating rules. On the other hand, fraudsters have become adept at finding loopholes. Whatever rules you set, it is likely that they will be able to get ahead of them. But what if your system was able to think for itself, at least to a certain extent?

New approaches to fraud prevention combine rules-based systems with machine learning and artificial intelligence-based fraud detection systems. These hybrid systems are able to detect and recognise thousands of fraud patterns and learn from the data. Automated analytical-based fraud detection systems can reveal novel fraud patterns and identify organised crime more consistently, efficiently and quickly. This makes them a good investment for businesses across a wide range of sectors, including public sector, insurance, banking, and even healthcare or telecommunications.

How, though, can you harness analytics as a tool in your fight against fraud?

 

Identifying needs and solutions

The first step is to identify which options you need. Probably the best way to do this is through a series of company-wide workshops with the fraud analytics experts to determine what analytics you need, which data to include and techniques to use, and what results to report. They can also identify the ideal combination of rules-based and AI/ML approaches to detect fraud as early as possible.

Companies looking towards advanced analytics for fraud detection will need to make a number of decisions. They will need to optimise existing scenario threshold tuning, explore big data, develop and interpret machine learning models for fraud, discover relevant information in text data, and prioritise and auto-route alerts. There may be industry-specific decisions to make, too, such as automating damage analysis through image recognition in the insurance sector. By automating these areas, companies can both significantly reduce human effort – reducing costs – and improve their fraud detection and prevention.

 

Benefits of an analytical approach to fraud detection and prevention

Companies that are already using an analytical approach for fraud prevention have reported several important benefits. First, the quality of referrals for further investigation is better. Investigators also have a much clearer idea of why the referral has been made, which improves the efficiency of investigation. Analytics also improves investigation efficiency by reducing the number of both false positives (that is, alerts that turn out not to be fraud) and false negatives (failure to spot actual frauds). This improves customer experience and reduces risk to the company.

Analytics makes it possible to uncover complex or organised fraud that rules-based systems would miss. Companies can group together customers and accounts with similar behaviors, and then set risk-based thresholds appropriate for each scenario.

There are several sector-specific benefits too. For example, insurance firms can identify fraudulent claims faster to prevent improper payments from going out. Claims investigation is likely to be more consistent because claims are scored through technology, algorithms and analytics, rather than by people. Finally, it becomes possible to shorten the claims process through automated damage analysis. It is no wonder that organizations across a wide range of sectors are placing analytics at the heart of their anti-fraud strategy.

Business

How FS organisations can utilise data to boost customer experience

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Charles Southwood, Regional VP and GM – Northern Europe and Africa at Denodo

We’ve all heard the age-old adage “the customer is always right”. It insinuates that, in any sector, the needs and desires of those buying a brand’s product or services should be paramount. However, today’s customer has new standards and it is becoming harder than ever for businesses to meet and exceed them.

This is certainly the case in the financial services (FS) sector where getting customer experience right used to be relatively simple. The human touch was traditionally delivered as a bi-product of in-store, transactional interactions. Perhaps, as a result of this, few people ever considered changing their provider and the traditional, established banks ruled the space.

However, with the dawn of online banking and the introduction of new, exciting challenger banks as well as the UK’s unique Current Account Switching Service, the balance of power between the consumer and the bank is changing. Consumers no longer feel locked in. If their needs aren’t being met, they aren’t afraid to look elsewhere and switch their allegiance to other companies. In other words, loyalty is far from guaranteed and customer acquisition is only half the battle.

Retention relies upon delivering strong, unique customer experiences that beat down the competition. In order to achieve this, FS organisations will need to be able to leverage data. Its insights could be the differentiator that enables them to stand out. The positive news is that, in our online world, there is a constant stream of data being produced. However, having access to all this data doesn’t necessarily mean that a brand knows how to effectively analyse and utilise it.

Ensuring data provides insight

The rapid growth in digital technologies and services across the sector has left many FS organisations juggling an unimaginable amount of data. This data is both complex and much of it is lacking in quality. Structured, semi-structured and unstructured, it is stored in many different places – whether that’s in data lakes, on premise or in multi-cloud environments. Before FS organisations can even think about using it to inform customer experience strategies, they need to be able to find it and understand it.

This is where modern technologies – such as data virtualization – can help. Through a single, logical view data virtualization boosts visibility and real-time availability of all data across an organisation.  Unlike traditional extract, transform and load (ETL) solutions, it does not move and copy data. Instead it leaves it in the source systems. In other words, instead of just replicating data, data virtualization reveals an integrated view to those trying to find it.

For FS organisations this provides several important benefits. For example, it helps when data sovereignty issues arise and the movement and replication of data outside certain countries is illegal. Data virtualization solutions can also assist in terms of financial reporting by fetching data in real time from underlying source systems – applying the necessary security and obfuscation whilst delivering the performance, the agility and the accuracy needed through the seamless connection of data.

FS organisations that adopt data virtualization, are likely to see an improvement in the overall performance and efficiencies of their business operations. Overheads will be reduced, as will the length of project times. Above all, data virtualization will rapidly strengthen the customer experience by supporting business leaders to think strategically and make decisions based on real-time insights. But don’t just take my word for it.

The proof is in the pudding: How Landsbankinn is delivering on the CX promise

Landsbankinn is just one of the many financial services institutions that has already successfully embraced data virtualization and its benefits. Despite being the largest financial institution in Iceland – with around 40% of the retail and 33% of the corporate banking market share – Landsbankinn used to face several issues when it came to data sharing and analytics.

Over 45 siloed data sources – including Oracle databases, data warehouses and APIs from internal and external sources – made finding and accessing the right data at the right time extremely difficult. Without real-time data to fuel informed decision making, customer experience and operational efficiency were suffering. As a result, Landsbankinn was in need of a data overhaul to streamline and integrate its infrastructure.

To bring together its complex data landscape and collect data in real-time, Landsbankinn implemented the Denodo Platform – a data integration and data management solution built on data virtualization – to build a logical data warehouse. As a result, the team can now aggregate data from multiple data sources, transform that data based on the applied business rules, and then make it available to consuming applications. Ultimately, this means that, throughout the organisation, the data can be utilised by a wealth of employees, even those who are not particularly IT savvy. It also means that the business leaders can use data insights to make well-versed decisions and provide a plethora of services to Landsbankinn customers both quickly and efficiently.

In recent years, customer retention has become the key to successfully growing a business. This cannot happen without an effective customer experience strategy. The ability to convert data into insight is priceless in an economic landscape where the line between a business thriving, surviving and failing is so thin. Those operating in financial services must harness modern technologies – like data virtualization – to stay at the top of their game and ahead of the competition.

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The Evolution of SoftPoS in 2023

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By Brad Hyett, CEO of phos

Contactless payments and digital wallets have surged in popularity in recent years. Part of this stems from the digital boom that occurred during COVID-19 but it’s also thanks to the ease of use that contactless offers customers. This has helped accelerate Software Point of Sale or ‘SoftPoS’ adoption amongst SMEs and enterprise retailers, with a total of 6 million merchants taking advantage of the technology in 2022 according to Juniper Research.

SoftPoS or ‘Tap to Pay’ technology – is a software solution that allows vendors to turn their phones or mobile devices into contactless payment points. This has made life for small businesses easier, as they no longer have to fork out large sums of money for traditional Point of Sale (POS) terminals, i.e. card readers, or ‘make do’ with outdated payment software.

In light of Apple’s announcement to allow third-party SoftPoS providers to deploy their technology on iPhone last year, adoption is expected to increase further. By 2027, it’s forecast that there will be up to 34.5 million merchants by 2027 – nearly a 500% increase from today. With more payment giants like Paypal and Venmo announcing they will support contactless transactions through their iOS apps in the months ahead, what else is in store for SoftPoS in 2023?

Apple’s role in market consolidation within SoftPoS

Apple’s move to integrate the technology with iOS devices will expand SoftPoS’ usability across mobile operating systems – significantly boosting the size of the addressable market for vendors. For the first time, Apple users will be able to offer Tap-to-Pay solutions which have traditionally been limited to Android devices only.

This will ultimately bring greater awareness and adoption of SoftPoS as we see increased familiarity with Tap-to-Pay solutions among businesses and consumers alike – as they’re no longer bound by the constraints of the type of phone they use.

While the SoftPoS on iPhone rollout currently only applies to the US market, it’s fair to assume this will expand internationally at some point – aiding the normalisation of ‘Tap to Pay’ solutions en masse in the months and years ahead.

The next wave of solopreneurs

The events of the last year will also continue to have a ripple effect over the next 12 months. For example, we’ve seen the tech industry undergo mass layoffs due to a challenging economic environment and rising global inflation.

With large numbers of highly skilled talent out of work, the phenomenon of solo entrepreneurship is likely to see an uplift – as it did during the pandemic – over the next 12 months. Born in a digital-native environment, individuals from this released workforce can now set up their own businesses and run them on mobile devices, as opposed to legacy infrastructures.

This could prove another sizable opportunity for SoftPoS vendors in the coming year, as we predict to see more small businesses sprout as a result of ongoing redundancies.

The growing importance of SoftPoS orchestration

As the market rapidly develops, so too does the choice and ease of onboarding. Financial institutions and retail technology providers can now use a SoftPoS orchestrator to help them deploy Tap-to-Pay solutions quickly and easily for their merchant customers, instead of having to create their own mobile solutions. This saves them time and money – both crucial resources for any business and especially in a challenging economy.

Partnering with a SoftPoS orchestrator is a cost-effective way of providing mobile payment solutions without having to worry about waiting on new software and security updates. With an orchestrator, this is done automatically – making this a much lighter lift with no requirement for technological know-how.

As SoftPos orchestrators are acquirer agnostic, this means they can help businesses provide a SoftPos solution to their own retail customers, regardless of the existing acquirer that they’re already using.

An additional benefit here is that a wider pool of merchants are able to benefit from the technology – growing the overall size of the SoftPoS market. Orchestrators, then, have the ability to drive wider adoption of the technology globally, reaching a bigger audience of end users and advancing the mobile payments industry in emerging markets across the world.

Conclusion

The increased popularity of digital and contactless payment options has driven exponential growth in the SoftPoS market in recent years. The next 12 months will see the technology enter the mainstream, as Apple starts to allow more third-party SoftPoS providers to deploy their solutions on iPhones.

The timing coincides with several emerging opportunities for the technology, including a potential uptick in the number of solopreneurs and mobile-first businesses. This combination of factors will see more financial institutions and legacy technology players work with SoftPoS orchestrators to bring Tap-to-Pay solutions to market in 2023 if they want to stay ahead of the competition and keep up with ever evolving customer demands.

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