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BANKING: MAKING AI IN CUSTOMER SERVICE A REALITY

Dale Kim senior director of technical solutions at Hazelcast discusses how in-memory computing and AI are the key to up-selling at scale in the financial services sector

Banks are constantly looking for opportunities to up- or cross-sell products to customers. Increasing product penetration from 2.5 products to 4 products per customer can add millions to the bottom line and it is estimated to be 5 – 10 times cheaper to up- or cross-sell to an existing customer than to acquire a new one. Combining in-memory computing with AI opens up new opportunities to do so.

 

The need for real-time insight

When it comes to engaging customers in up- or cross-selling conversations, timing is everything. Customers are far more likely to be receptive to an approach when they are already interacting with the bank – online, via the telephone, or in branch. But for this to happen, the bank needs a real-time, comprehensive and contextualised view of each customer, including the accounts they hold, their transaction history and much more.

That’s where things get challenging. At any given moment millions of customers might be interacting with different parts of the bank’s systems via different devices in different locations. New data will be streaming in from computers, smartphones, customer support lines and other sources.

In the past, transactional data was managed as a batch process and analysed periodically – often hourly or daily depending on the data involved, the bank’s own policies and any regulatory and compliance requirements. For real-time insight, transactional data needs to be executed in less than the time it takes to blink. Fortunately that’s become possible through stream processing and in-memory computing.

Stream processing refers to real-time management of data entering a banking system at high speed and volume, usually from a broad range of sources. The data is wholly or partially processed and contextualised before entering an in-memory data grid where historical context can be applied in microseconds to improve the probability of a successful up- or cross-sell.

 

Combining AI with in-memory computing enables upselling at scale

Where this gets interesting is when all this real-time data is used to power machine learning (ML) and artificial intelligence (AI) systems – whereby the customer thinks they are talking to a human being but are in fact speaking to a machine. As well as improving the probability of a successful up- or cross-sell, the machine may arguably be able to provide a better, more ‘intuitive’, customer experience than a human could. The main advantage of tying an in-memory solution to an AI solution, however, is volume; millions of simultaneous customers calling in can strain even the most significant call centre, but not be noticeable to an AI-powered chatbots.

It should come as little surprise therefore that industry analyst Gartner predicts that by 2022, a massive 70 per cent of customer interactions (in banking and otherwise) will involve emerging technologies such as ML applications, chatbots and mobile messaging – up from 15 per cent in 2018.

The above use case along with others such as more accurate fraud detection in payment processing and a reduced risk of false positives undermining customer experience are what has driven the success of combined AI and in-memory computing technologies within the financial services community to date.  There is little doubt that it will continue to do so.

 

Business

THE EFFECTS AUTONOMOUS DRIVING WILL HAVE ON THE TRANSPORTATION AND LOGISTICS INDUSTRY

Stefan Spendrup, Vice President of Sales Northern and Western Europe at SOTI 

 

‘Big thinking’ articles on how to disrupt industries from retail to healthcare have been so prolific in recent years that you would be remiss in assuming we have moved forward from the digital transformation era. Rather, it is important to think of these transformations as the natural extension of a technologically driven world, in which companies are constantly adapting to meet ever-evolving market demands and customer needs. As the pace of development in technological capabilities has increased, so too has companies’ access to technology. With this comes an expectation that companies remain current with the latest advancements.

 

Following the mobile-first era, the next stage in the evolution of digital disruption is the move toward robotics through the Internet of Things (IoT) and Artificial Intelligence (AI.) Once companies have integrated a comprehensive mobility strategy within their operations, we find them increasingly turning to “what’s next”; solutions that will give them an even greater advantage against competitors and help them stay ahead of the field. Machine learning is poised to meet that market demand.

 

The transportation and logistics (T&L) industry is at the forefront of this trend. An industry that may seem at first to be traditional and unchanged by technology over the past half century, has been among the earliest adopters of disruptive technology.

 

Autonomous trucking is the next frontier for the transportation industry. As larger enterprises move away from traditional practices, smaller organisations can follow and benefit from the mainstream acceptance of autonomous technology. This can be seen in areas such as:

  • Monitoring, information sharing and exchange across remote devices
  • Management of mobile devices, remotely, which can eventually be applied to powering and controlling autonomous devices
  • Remote support
  • Performance data and analysis

 

The numbers make the case. In the UK, 1.44 billion tonnes of goods were shipped via heavy goods vehicles (HGVs) in 2019, which is an increase of 2% when compared to the year before. Global e-commerce sales are set to reach $5 trillion (£3.8 trillion) by 2021, driven largely by lowered consumer costs for online shopping and the ease of ordering online for everything from fruit to furniture. This trend is not likely to decline, especially as many are looking to limit in-store interactions in the wake of the COVID-19 pandemic. It will be difficult for transportation and logistics companies to ignore the financial benefits of automation alone.

 

Evidential benefits of automation within the supply chain and operational practices already exist. This can be explicitly seen in Amazon’s famous robot warehouses. These IoT-enabled robotic devices can sift through packages faster than humans can. They can work anywhere and under pretty much any condition, which is why they have been employed within the supply chain to speed up delivery and enhance the end-customer experience. The Amazon example indicates that as technology advances, adoption is likely to surge.

 

When turning our focus onto delivery services, we are seeing incredible interest in autonomous trucking, which has the potential to deliver faster, more predictable and more reliable service. These benefits do not negate the valuable role humans will need to play in overseeing quality control, providing support and conducting data analytics functions to aid in further innovation.

 

Prior to implementing full-scale autonomous trucking, shippers will need to ensure that the management and assessment of a connected fleet meets jurisdictional and federal legislation in addition to minimising cybersecurity risks. High levels of connectivity often translate into greater security risks, and companies will need to prioritise security to ensure systems are built with cyber resilience capabilities and can respond quickly in the event of a cyber breach.

 

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Business

ACCOUNTANTS HAVE BECOME CRITICAL TO THE SURVIVAL OF BUSINESSES AND THEIR REPUTATIONS DURING COVID-19

Stuart Cobbe, Director of Growth, Europe, MindBridge

 

The opportunity for fraudulent activity to flourish as finance departments operate remotely with less oversight in these extraordinary Covid-19 times is inevitable. Government loans and financial support have been given out with little or no accountability to businesses that are struggling with the change in their trading environment and as a consequence businesses find themselves in financial need.

There is already evidence of corporations handing back furlough grants as HMRC offers a 90-day amnesty, but without rapid data-driven insight and risk stratification, businesses may not know the extent of their exposure. Indeed many businesses face the daunting prospect of repaying loans at the same time as paying deferred VAT early next year in a far from certain trading environment. Stuart Cobbe, Director of Growth, Europe, MindBridge explains that the role of the accountant has now become critical to businesses and their reputations.

 

Unlocking transparency

The Covid-19 landscape is fluid and ever-changing, and businesses require accurate visibility of all aspects of their business in order to plan effectively for the future and to understand their financial position. As the economy continues to recover to a new ‘normal’, companies need to focus on the next 6 months. How many ‘zombie’ businesses are only operating due to deferred VAT payments? How many companies will fail when they cannot repay loans? The role of the accountant is vital in unlocking this transparency to provide data-driven, actionable insights.

After all, there are many questions around how government financing has been used, from grants to loans, furlough payments to VAT deferments. As of the 20th September, the total cost of furlough claims has reached a staggering almost £40 billion, despite 30,000 applications being rejected, with many likely to have been attempts to defraud the taxpayer. Research by economists from Cambridge, Oxford and Zurich universities found that as many as two thirds of furloughed workers continued to work.

For businesses that do not understand the extent of their exposure, they risk facing a HMRC-imposed tax charge equivalent of up to 100% of the grant to which any recipient was not entitled and was not repaid. It is, therefore, interesting to see the number of large organisations now publicly revealing plans to repay all furlough payments. For many, this is an opportunity to boost corporate reputation and demonstrate a commitment to rediscovering business as usual. However, given the huge pressures businesses have been under in recent months, many CFOs and FDs may not have the full visibility they require to effectively manage this without the power of audit.

 

Financial Risks

This is about far more than reputational damage, the potential misuse of furlough is far from the only financial risk. The extraordinary shift in every business’ modus operandi over the past few months has opened the door for opportunistic fraud. New sources of income; staff working from home with limited oversight; the financial pressures – both business and personal – created by the recession. The misappropriation of assets should be a very real concern for businesses of every size.

For organisations that have relied upon grants and loans to survive, an employee exploiting the lack of oversight to syphon funds for personal use could tip the company into failure. Companies must determine how – or whether – deferred VAT payments and loan repayments can be made. Is the company truly solvent or no more than a ‘zombie’ business operating with a balance sheet propped up by short term government finance?

 

Actionable data

Business resilience and reputation is a priority in this era, and CFOs or FDs may be struggling to establish trust across businesses now operating under a whole new range of pressures, from slimmer margins to a disjointed, remote workforce. There is an obvious need for complete visualisation of financial risks, and accountants play a crucial role in unlocking this data.

The rapid identification of mistakes in government support applications, potential fraud and the analysis of which deferred payments and loan repayments can be made and when – whilst ensuring other risk factors do not jeopardise business stability – is essential to futureproof the business, and accountants can assess data to provide this information in a complete and actionable format to lead smarter company decisions. This is the data insight CFOs and FDs need today.

Traditional financial risk assessment models will not be adequate. At best, problems will be revealed months after the fact. Companies need rapid identification of areas of unexpected activity today. This is where accountants and finance departments using sophisticated machine learning and artificial intelligence techniques can deliver real business value by rapidly assessing financial data and surfacing unexpected activity. Armed with this information, finance teams will know where to focus activities, the questions to ask and the remedial action to take. This information will drive departments and remedial action to ensure business success and growth as the nation gets back to its feet.

In short, accountants and finance professionals can provide the answers businesses need today, whilst helping managers to plan for the future effectively, despite the changes in policies and protocols as the pandemic continues to throw curveballs. An audit can quickly identify problems including but not limited to, cash flow, fraud, misuse of grants, loan repayment issues – all whilst offering the guidance and steps to safeguard the business to promote resilience and protect the solvency and reputation.

 

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