In line with our risk management framework, today we published our Q4 2019 performance update.
The AI finance revolution
The rise of Artificial Intelligence (AI) is an inexorable one, which has already permeated into our lives. It presents a number of social challenges, which politicians and society will need to get a handle on. And it isn’t always everyone’s cup of tea. For example, next time you go to a supermarket, note the number of people who would rather stand in a longer queue at checkout so as to have their basket items scanned by a real person, rather than breeze in and out through the self-checkout lanes.
Yet the value of AI, and the wider good it can do for the economy, is not in dispute. McKinsey Global Institute forecasts a £10tn boost to global economic activity by 2030 as a direct result of AI, contributing additional annual GDP growth of 1.2 per cent by 2028. This is backed up by a separate PwC study, which predicts a £232bn windfall to the UK economy by 2030 as a direct result of AI, and the boost it will bring to productivity, efficiency, consumer demand and personalisation of goods and services.
What has AI got to do with retail?
Any number of sectors are set to reap a share of this hefty dividend, but, chief among them is the UK’s retail sector. Industry experts agree that automation will touch all parts of UK retail – even brick-and-mortar stores with a limited online presence – in the near future. Indeed, retailers in the UK have already begun to integrate significant elements of machine learning (ML) into their digital offering.
One example of this is the algorithms online retailers have in place for product recommendation. On this front, Amazon is leading the way, with more than 34 per cent of its total sales derived from its product recommendations. Underpinning this is a focus on data, which is the lifeblood of the technology that drives AI and ML development.
How does AI collaborate with data?
We live in an age where data is king, but also one where customers are trusting companies with their data less and less. A further conundrum is that, despite clinging ever tighter to their own personal data, customers still expect a completely personalised process when it comes to the various facets of ecommerce.
For retailers, who are often dealing with insufficient, inaccurate or obsolete data, it becomes enormously difficult to not only personalise customer experiences, but also optimise price points, stock levels and more. This is where AI and ML technologies are beginning to step in. The predictive capabilities of SaaS-delivered solutions can amalgamate past sales data with external data trends and movements, captured through edge technologies, and provide continuous insights.
These insights can then be linked to systems across the business as a whole, perpetuating a cycle of automation, and providing the basis upon which vital strategic decisions regarding inventory, pricing and demand forecasts can be made. Aside from increasing revenue growth, such intelligence also delivers an efficiency which drives down operating costs.
How does AI help with personalisation?
The concept of personalisation, particularly within retail, has always been an ever-present. Product recommendations, suggested accessories for a purchased item, advocating paint colours to complement furniture – these are all ways in which retailers seek to add a human touch to a customer’s shopping experience.
The challenge for retailers is that the level of personalisation customers now expect has soared. They expect it wherever they are, at any time, through whichever medium they shop, and with a deep understanding of their individual preferences. We’ve already alluded to the level of machine-learning ingenuity within Amazon’s product recommendations, and the proportion of revenue this accounts for. But there is a whole lot more to personalisation than this, and the role of AI begins much earlier in the customer journey.
For starters, a study by Emarsys and Forrester found that over 50 per cent of retail marketers already use AI to personalise customer experiences across touchpoints, understand customer behaviour and manage customer interactions in real-time.
The primary advantage of bringing ML into retail marketing is the extent to which personalisation can be scaled. But there are other benefits too. A data-driven approach excludes human bias, thus providing a sturdier foundation for decision-making. It also allows retailers to identify high-value customers, and further optimise loyalty experiences for them. Additionally, AI brings with it more versatility. For example, messaging can be customised depending on where the customer fits within the journey (eg: personalised push notifications), or based on information that can be mined from customer behaviour in real-time.
And then there is customer service. While many customers value the sound of an informative, reassuring voice at the end of the phone, chat bots and the likes are becoming increasingly popular with the young. Recent research by Zebra Technologies found that 55% of 20 to 36-year-olds prefer to use a store app to find information rather than speak with an employee. This isn’t merely cause for retailers to ensure their app is optimised (although that is still vital) – it’s a golden opportunity to weave further personalisation into the customer journey, and the only way to do so efficiently, and at scale, is through AI and ML.
Has AI had an impact on payments?
Contactless credit cards and self-checkouts are just the tip of the iceberg when it comes to transforming payments within retail, and the capabilities of AI. One of the more impressive working examples is that of Amazon Go. There are currently only a handful of these stores in operation (all US-based), but the remarkable thing about them is that they do not have any cashiers, cash registers or self-checkouts. You simply download the app, grab what you want in store (recorded by a series of sensors and cameras), and Amazon automatically charges the cost of the items to your card as you walk through a turnstile on your way out.
The technology behind such a seamless experience centres upon AI and some cutting-edge image recognition software, and many believe it to be the future of retail. If an unconfirmed Bloomberg report is anything to go by, Amazon has plans to open 3,000 such stores around the world by 2021, and competitors will surely follow suit.
Voice technology is another feature of AI and payments. Alexa, Google Home and Amazon Echo are a few of the more well-known media, but a number of stores have begun collaborating with Google Assistant-enabled devices. So tailored to retailers has this form of AI become that even stores like Starbucks now have their own virtual assistant called ‘My Starbucks barista’, whereby a customer’s order can be conducted from start to finish using just their voice.
What does AI hold for the future of payments?
Many anticipate the demise of cash in the not-too-distant future. But, despite accounting for three quarters of online payments in the UK at present, the future of plastic is highly uncertain too, and many expect that paying through our bodies will soon become the norm.
Jewellery/watches is one method which is increasingly commonplace, while iris reading, fingertip microchips, facial recognition and other biometrics are set to be incorporated into standard payment methods in the UK.
It is highly likely that the payments industry will be almost entirely driven by AI and ML before the end of the next decade. Intelligent systems will endlessly scan millions of transactions, and, having integrated things like KYC, be able to identify new trends and growth opportunities. Such AI-powered technologies will reach levels of sophistication far beyond any human capabilities.
How safe is relying on AI for payments?
As the scope of AI’s involvement within payments increases, so too does the variety of ways in which customers become vulnerable to fraud. There were nearly 175,000 cases of fraud investigated in 2017 in the UK, and almost all of these (roughly 95 per cent) involved identity theft. Indeed, the UK loses more than £190bn each year to fraud, according to Experian. Little wonder then that there is some trepidation when it comes to online payments.
Yet it should not be forgotten that the power of AI can also be leveraged against fraudsters. Machine learning of rich data is already enabling credit reference agencies to identify criminals - which is particularly beneficial for those who provide retail finance, for example. Other AI-powered applications such as Zonos and pipl are also supporting the fight against fraud.
PayPal is one major provider which has put great emphasis on using fraud detection algorithms to make digital transactions safer. The automated analysis of purchasing patterns is now so in-depth that the technology can distinguish between friends paying for concert tickets at the same time as a fraudster making the same type of purchases with a collection of stolen accounts. As a result, PayPal’s fraud rate sits at just 0.32 per cent of revenue, according to LexisNexis.
In terms of protecting data, digital identity apps such as Yoti use complex algorithms to encrypt and store personal information on their database (superimposed from passports, drivers licences or national IDs), which can only be retrieved by the individual through a series of unique cryptographic keys.
Should retailers be worried about AI?
At a time when retailers in the UK are facing considerable headwinds – particularly brick-and-mortar stores, who must contend with the rise of online retailers – AI presents a tremendous opportunity to turn the tide. Rather than precipitating a race to the bottom, automation has the power to grow the size of the retail market, and boost growth across the board.
The challenge, of course, is scaling AI, and integrating it effectively and cost-efficiently. In this regard, retailers seem to be maintaining a degree of caution. In fact, a recent Microsoft survey found that 56 per cent of UK retailers have yet to incorporate AI in any way. This will need to change if retailers are to come to terms with rapid shifts in consumer behaviour, and the way they interact with retailers.
Encouragingly, a separate study by Rackspace found that a quarter of IT decision-makers within UK retail companies intend to onboard new AI technology before the end of 2019 in a bid to seize the opportunities of automation. The research also predicts that 7.5 per cent of IT budget within UK retail will be allocated towards AI this year, typifying the urgency with which retailers are beginning to respond.
At an employee level, there is no doubting the threat automation poses to jobs. The British Retail Consortium estimates that 60 per cent of retail jobs will be at risk due to AI over the next two decades. In particular, inventory management and supply chain roles will be in the firing line. But automation’s track record suggests that it is as much a job creator as it is a job absorber, and retailers can benefit both themselves and staff members by transforming old positions into new roles, and up-skilling existing employees to adequately fulfil them.
AI brings with it a number of challenges to all sectors in the UK, including retail. But its rise is an inevitable one nevertheless, and what is not in dispute is the tremendous benefits it can bring. If these can be harnessed, and help drive new levels of innovation, then the future of retail in the UK may well be a whole lot brighter than today’s media would have you believe.
Our website offers information about saving, investing, tax and other financial matters, but not personal advice. If you're not sure whether peer-to-peer lending is right for you, please seek independent financial advice, and if you decide to invest with Lending Works, please read our Key Lender Information PDF first.
Since opening our doors back in 2014, we’ve always prided ourselves on living and breathing two key principles at Lending Works: innovation, and putting the customer first in everything we do.
With the retail sector enduring its fair share of challenges, companies are looking at new ways to attract customers, and drive conversion. In an overcrowded, dog-eat-dog marketplace, with behemoths such as Amazon flexing their muscle, it’s easier said than done.
On 4 June 2019, the Financial Conduct Authority (FCA) released its new regulatory framework for peer-to-peer lending (P2P); a Policy Statement known as PS19/14. As you might imagine, it's a document which, following a three-month consultation, is a hefty read of no fewer than 102 pages.
In a difficult climate, customer acquisition and lead generation present stern challenges for UK retailers, and a great deal of marketing spend invariably gets directed towards getting feet through the door.
Over the last decade, there can be little dispute that the reputation of mainstream banks – and particularly the so-called ‘Big Four’ (HSBC, Barclays, Lloyds and RBS) – is at its lowest ebb.
The peer-to-peer (P2P) lending industry is now regulated by the Financial Conduct Authority (FCA). The regulatory framework has been designed to protect customers and promote effective competition.
In a decade of slow recovery, the rapid rise in asset prices has been the standout. But how sustainable has price growth been, and could we be in the midst of a bubble?
Most people consider income tax to be a given, but in the UK it is barely two centuries old. In this article, we look at how this tax has developed over the years, and also why it is set to remain at the core of our tax system for many decades to come.
Open banking celebrated its second birthday last month, but has the ‘revolution for financial services’ that was promised actually come to pass? In this article, we look at the progress the initiative has made so far, and what the future holds in the face of high levels of scepticism.
On the face of it, a 'broken' energy market needed fixing, and the price caps introduced in early 2019 were heralded as the solution. But, one year later, have they actually helped consumers save?
Last week, the Office for National Statistics surprised economists by announcing that the Consumer Price Index (CPI) had sunk to 1.3 per cent for December – a full 20 basis points lower than City expectations, and also the November equivalent.