“In the future, robots will be doing our jobs for us” is one of the most common sentences we hear from futurists, business people and technology leaders. Below Richard Acreman, Partner at WM Reply, discusses the overvalue of automated processes and the future of ‘robots’ on the front lines of business.
There are variations on the theme depending on your perspective, like “robots are stealing our jobs” or, at the other end of the spectrum, “robots will create a revolution in creative freedom.” But while all of these predictions will probably have a strong element of truth to them over the long term, they’re also the source of a dangerous misconception in the here and now: that businesses don’t need to worry so much about talent.
Broadly speaking, the exact opposite is true, but if it’s a misconception you share, you have some prestigious company. A major piece of opinion research recently revealed the difference between the value of human capital vs. physical capital to the economy now and in the future. As part the study, two thirds of CEOs and top leaders at global firms revealed that they believed technology would create greater value for their organisations than their workforces would. Almost half believed that automation, AI and robotics would make their workforce “largely irrelevant” in the near future.
In fact, the economic modelling that accompanied the research showed that human capital would be worth more than twice as much. The key distinction is having the right skills and the right people, who are valuable both in their own right, and as the people who are going to enable the technology to enhance their organisations’ value. That means engaging with, supporting and learning from the best workers to ensure that their knowledge and expertise remains within the business and can continue to unlock the business’s potential as the workplace changes.
A key battleground
Unsurprisingly, the first place that this issue is flaring up is on the front lines of business – among the customer facing or service delivering staff that form the grass roots of most organisations. It’s this audience who are often the most threatened by automation and it’s also this audience who are traditionally most neglected by their companies.
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As the above study shows, it’s all too easy for businesses who have never been particularly strong on engaging their front line workers to take technology as an excuse for inaction or to make the situation even worse, but overestimating the scale of the change or the speed of the transition means that those with this attitude will likely have years to regret their miscalculation before anything close to the future they’d imagined comes to pass.
Why front line workers continue to be so important
Looking at it from both sides helps to clarify how misleading it can be to think that technology is going to make staff less relevant.
If we assume that technologies that are good enough to fully replace staff are here already, or very close, then we might also make the assessment that the best staff will be needed to help inform the processes and approaches of that technology, look after it, and stand in for it when it goes wrong. Not to mention the cases where it doesn’t have the answer, or is dealing with a customer who insists on human interaction.
If we assume that the technology isn’t here yet, but is coming, then this group will remain essential to the work, but exist in a heightened state of anxiety about their future with automation seemingly in hot pursuit of them. They will therefore need not just a decent level of support and attention from the business (as should be standard), but also a certain amount or additional reassurance, the absence of which might well be seen as their death knell.
People and technology in perfect harmony
What then is the short-term answer? And how can companies ensure that they are not only engaging with, but also getting the most out of their front line workers, so that the technology will have to work even harder to offer a quantifiable advantage?
That’s probably something that’s best explained with some specifics. Bea Tartsanyi, enterprise innovation strategist at Sideways 6, talking at a recent event focused around Microsoft’s Yammer, pointed out that the value of grassroots innovation to a business is immense. With the analytics that her team is developing, they’re starting to get a handle on just how important that is. She’s proving that using tools like Yammer to access the knowledge and learnings of those on the front lines – those who ordinarily might not have much of a voice internally – is not only one of the most effective, but also cost efficient ways of driving innovation.
Bea also pointed out that companies are always looking at ways to bring the voice of the customer firmly into the business. To learn from the customer’s needs and to understand the best practice approaches to meeting them. What better way to do that than to directly connect front line workers to the centralised organisation through the engaging, non-hierarchical social tools like Yammer.
It works both ways: Front line workers can easily flag some of the everyday challenges they face for senior managers to tackle, while those at the top can offer up the challenges they face. Whether those challenges come from a loyalty, cost or another perspective entirely, allowing those at the coalface to share their experience of overcoming those challenges on an individual case basis will feed into an organisation-wide benefit.
Ultimately, automation will have an important role to play, but we’re a long way from that role superseding the role of front line workers. Giving those on the ground the tools to excel at their own jobs while also feeding into the wider strategy is an immediate answer to many of the challenges that companies face. Given how much front line workers – properly enabled – can contribute, ignoring the people-based solutions to those challenges in favour of the vague idea that up and coming technologies will fill in the gap is like saying you won’t buy an umbrella because at some point in the future it might not be raining.
From AI to all things IoT, Russell Bennett, Chief Technology Officer at Fraedom, discusses with Finance Monthly the top five technologies that are already making waves in the banking sector.
Over the past five years, technology has fundamentally changed how the financial services sector operates. Many retail banks already successfully cater to customers’ digital needs. Business banking is now beginning to follow retail’s lead – and here we outline five of the top technologies transforming commercial banking today.
- Biometrics and security
When adopting new payment methodologies, banks must strike a balance between ease-of-use, ease-of-access, and security. We’ve already seen that consumer payment methods using biometric authentication becoming mainstream and it won’t be long before corporate clients expect the same.
Extending this functionality into corporate cards has the potential to make commercial payments more seamless and secure. Mobile wallets that defer to personal attributes to make secure payments on cards offer a potential route forward.
- Artificial Intelligence
Automation is dramatically increasing the number of financial transactions in an organisation. However, while it can track and store more processes than humans can – and more accurately – it currently can’t provide the next level service many clients are coming to expect of their financial partners: planning and modelling.1
AI is rapidly establishing itself as the missing piece of the puzzle that takes the data flows created by automated transactions and knits them together to discover patterns. All this is important to commercial banks because patterns in spending and efficiency can potentially deliver valuable insights to help clients improve their financial health.
- APIs
Customers’ demands, and expectations are moving rapidly, so there is growing pressure on the banking industry to provide new, easy-to-use, frictionless digital services fast.
Application programming interfaces (APIs) provide the technology to exchange customer data with other parties in a simple and secure way2, facilitating rapid innovation in products and services. Creating new applications such as voice banking, P2P, loan processing and risk management and using APIs as building blocks, is now seen as the best way to keep up with the innovation challenges facing the financial industry.
Fintechs have dominated the API landscape by creating apps that have challenged and often surpassed solutions made by the banking industry.
To keep pace, banks now need to either invest heavily to develop this technology themselves or partner with fintechs in a bid to be more effective and efficient.3 By working together and taking advantage of APIs, banks and fintech firms can enhance the customer experience much more than either entity could do on its own.
- ePayables – Crossing over from the Consumer to the Commercial World
The use of different payment types is partly a response to the consumerisation of our financial experience. Corporate clients can’t understand why payments should still be a laborious process of raising invoices and purchase orders, requesting printed cheques or bank transfers and creating lengthy payment terms.
Instead, the immediacy of a card – real, virtual or embedded in an app – ties all the above elements together. It gives unsurpassed traceability and is easy to add to financial management software.
Historically, paying by using a card has been seen as a debt generator. However, using payment cards as a substitute for invoice terms makes them a useful tool both to enhance a company’s working capital positions and to improve traceability, security and the level of control that can be placed on business spend.
- Expense Management Systems (EMS)
An Expense Management Systems (EMS) is just one of many tools that can be brought together into a single financial view, helping businesses gain greater control over expenditure. Unlike written expense policies and separate transactional management software, an EMS embeds expense policies into the technology, allowing real-time reconciliation and approvals to take place.
Up to now, retail banking has been ahead of the game in embracing new technologies and digital disruption but corporate banks are now grasping the need to take advantage of the latest technologies to ensure commercial clients reap the same rewards - from workflow efficiencies through to intuitive, mobile first experiences, a trend that is only likely to accelerate in the future.
2017 was a busy year for regulatory compliance and technology across the globe. We witnessed countless mass data breaches, sexual misconduct claims, money laundering scandals, and of course, the Wild West that is the Blockchain. Alongside that, we continue to see significant advancements in Artificial Intelligence (AI) and Machine Learning (ML) technologies across all industries, being applied to automate business functions, gain insights into behavior patterns, and more.This year, the Banking Industry will adopt ML and AI-based automation for enhanced efficiency and data-driven decision making.
Banks were slow to adopt ML based automation in 2017, but to remain competitive in 2018 and onward, banks will have to consider how adding AI and ML fueled technologies will impact their growth and improve the efficiency of their business processes.
Many financial institutions have been quick to experiment with AI applications in the frontend of the business, for example, to streamline and improve customer service via chatbots. In general, the value proposition is that AI can automate manual and repetitive roles but now, we are seeing AI being applied towards broader data-driven analysis and decision making.
This not only reduces costs and saves time, it also eliminates the risk associated with human prone errors. The machine is well-situated to consume large data sets while also self-learning overtime. But before even considering the tremendous opportunities to implement this technology on the backend of the business, organization leaders will need to educate themselves on how the technology actually works.
AI in the Enterprise
While many AI-based solutions have advanced over years, the financial industry remains suspicious of the science behind the decisions made by such technologies. Now we are seeing a shift towards increased transparency in AI-based solutions, where the science behind machine learning (ML) based decisions can be justified, tracked, and verified. This should help move along industries on the cusp of adoption.
Artificial Intelligence and machine learning in the long term can be applied to reduce costs and time by automating a once manual process. However, on average, most AI algorithms are only about 80% accurate, which doesn’t live up to the business standards of accuracy. That leaves 20% flawed, which requires human input to bridge the gap. There is an inherent design flaw to any AI solution which does not utilize some human component in development. It is a general understanding that the most successful AI models use the 80:20 rule, where 80% is AI generated, and 20% is human input. This is implemented in the form of supervised learning or human-in-the-loop.
Human-in-the-loop Integration
A best practice in the successful development of AI includes a human component, typically referred to as “Human-in-the-loop” or supervised learning model. The way it works is that machine learning makes the first attempt to process the data and it assigns a confidence score on how sure the algorithm is at making that judgement. If the confidence value is low, then it is flagged for one or many humans to help with the decision. Once humans make the decision, their judgements are fed back into the machine learning algorithm to make it smarter. Through active learning, the intelligence of the machine is strengthened, but the quality of the training data is based on the human contributors.
(CrowdFlower Inc, n.d.)
Some data analysis is specific and complex, such as the case with Financial Regulation. The evolving and complex nature of regulation is a tough subject matter to master. AI in RegTech requires an in-depth knowledge and understanding of the regulatory framework and how to read and interpret the text. In these types of fields, expertise is far more critical than the tool. However, if a tool could incorporate subject matter experts into the machine learning model, then the tool becomes exponentially more viable.
Expert-in-the-Loop takes Human-in-the-Loop to another level. It makes use of subject matter experts to train the machine and flag the machine’s errors. For example, a well trained machine in the RegTech industry could eliminate countless hours a compliance officer takes in researching, reading, and interpreting regulations, by automatically classifying documents into topic-specific categories or by summarizing the aspects of a document that have changed from a previous version.
The Expert-in-the-Loop model differs from Human-in-the-Loop in one major way: Human-in-the-Loop doesn’t differentiate between the aptitude level of the various participants to judge the particular question correctly. Human-in-the-Loop takes advantage of the Law of Averages which states that if many people participate, the average response will yield the correct result. So the response from a college student and a PHd student would be weighed the same. On the other hand, Expert-in-the-Loop , specifically looks at the experience level of the participant to determine how their result will be weighed. With Expert-in-the-Loop, a human is essentially supervising another human’s qualifications. While the cost is higher than both the unsupervised and the Human-in-the-Loop models, the results of Expert-in-the-Loop models are proportionally more accurate, making them suitable for highly specialized and industry specific topics.
Nearly every industry is exploring how to use AI and machine learning as tools to increase efficiency and streamline data analysis, among other things. The future holds endless possibilities for this emerging technology. It serves as a bridge to close the gap between information and the time it takes to compile results. The speed of data can bring about a new era of understanding and increased reaction time in the Financial Services industry. There are a lot of unknowns still left to address, but the technology is becoming more intelligent and its applications more advanced. Early adopters will have the benefit of experience on their side once the inevitable industry-wide adoption finally falls in place. Until then, organizations can pilot new applications and evaluate their impact and success. Ultimately, the financial industry will need to educate themselves on the pros and cons, while considering the implementation of this new technology.
For an insight into recent trends within the Internet of Things, this month Finance Monthly spoke to Alex Sutherland, innovator and CEO of UK-based Artificial Minds - a company dedicated to the advancement of technology for the connected world with a vision to create computers that interact with people. The company currently specialises within the Internet of Things (IoT), providing a secure and simple way to give households and industrial devices intelligence. Below, Alex tells us about the hottest topics being discusses in connection to IoT, as well as the potential implications of the further development of this technology.
Can you tell us a bit about the services that Artificial Minds provides and the clients that you work with?
Artificial Minds created an IoT operating system called Cortex, which is designed with plug and play connectivity, efficient data management and intelligent automation. This system can be installed on to any device, it will automatically configure itself to a network, allowing it to transfer data to a user, and thus - allowing a user to monitor information. Cortex will learn how best to make use of the connected devices within its environment by learning from the data they provide.
For example, one of our client is a hydroelectric company Derwent Hydro, which has used Cortex to monitor water presser, water flow and voltage information from its turbines. They have also been able to use Cortex to intelligently control a robotic arm to clear any debris from turbines. Cortex is currently being used by over 40 hydroelectric sites across the United Kingdom.
What are currently the hottest topics being discussed in relation to the IoT?
The hottest topics within IoT currently are security, voice assistants, cars and fifth generation wireless systems (5G). Security is a big issue with anything connected to the internet, due to hacking. This is an issue IoT will overcome in the coming years, maybe with the help of Blockchain or with offline methods. Voice assistants such as Alexa, Google and now even Cortana are entering the home. In the consumer sector of IoT, there seems to be an enjoyment controlling things with your voice - if you look at this year’s CES, a toilet that can be flushed with the aid of Alexa. Additionally, vehicles are becoming fully autonomous sooner than it was predicted with the assistance of AI.
And last but not least, it is of course worth mentioning 5G, which is set to transform the IoT landscape in terms of more secure networks and allowing devices to be connected without the need of Wi-Fi.
Looking into the near future, what do you anticipate for the development of the IoT?
I anticipate that once IoT would have solved its security issues. This will allow the healthcare industry to adopt IoT for hospitals for efficient operations and in hospital monitoring. Prisons could use IoT to monitor Inmates, identify contraband and alert for any behavioural or health issues. I also anticipate that there will be a lot more consumer adoption of IoT outside of wearables, so that more homes will in fact be ‘smarter’. For example, one will be able to interact with every room and object in your home or style your rooms based on your mood.
The world as a whole will be adopting IoT, so that the concept of Smart cities will be in full function and will begin to make an impact in society by providing greater benefits to it, such as safety. There will be more cars on the road that will encompass IoT for traffic management, fuel control and of course - self-driving. I believe that what is to come from the second generation of IoT is immeasurable.
What do you hope to achieve in the future with Artificial Minds?
Artificial Minds is growing the Cortex ecosystem into a fully capable AI for the world. We have started by implementing machine learning, which is designed to give your devices intelligence by learning, predicting, identifying and questioning the actions of devices and the environment around it. By the end of 2018, we would have Augmented Reality (AR) built into the platform and will grow it to see how we can evolve this with holography and further immerse the world into a full IoT experience. We’re taking steps to revolutionize IoT for the next generation. Within the next few years, Cortex will be the ecosystem of choice for IoT.
The world of banking and financial services is still seen as one of the more conservative sectors of the economy today but if organisations operating across these marketplaces want to drive competitive edge and business advantage in the future, they can no longer afford to ignore the consumer-driven pull towards the use of artificial intelligence (AI). Finance Monthly hears from Russell Bennett, chief technology officer at Fraedom, on the past and future of |AIs journey from consumer to the commercial world.
People are used to these technologies in their everyday lives. They are used to smart software telling them what they want to buy next even before they realise it themselves.
Today, it’s increasingly vital that banks, financial services organisations and financial departments within enterprises are all in touch with these trends. They need to start looking at the benefits that analytics and other predictive technologies can bring them. Their employees and customers will expect them to do so.
The good news is we are starting to see the use of AI growing in the commercial finance environment now. So far, use cases have mainly been around streamlining operational processes.
Take the introduction of digital expenses platforms and integrated payments tools, both of which have the potential to significantly improve a business’s approach to how it manages cash flow. By having an immediate oversight, through live reporting of all spending from business cards and invoice payments, as well as balances and credit limits across departments and individuals, businesses can foresee potential problems more quickly and react accordingly – and they can go beyond this too. All these services become even more powerful when combined with technologies like machine learning, data analytics and task automation.
We are also seeing growing instances of AI and automation being used to streamline payment processes in banks. Cards can be cancelled, or at least suspended, quickly and easily and without the need to contact the issuing bank, while invoices can also be automated, to streamline business payments. This means businesses can effectively keep hold of money longer and at the same time pay creditors more quickly. Moving beyond straightforward invoice processing, intelligent payments systems can be deployed to maximise this use of company credit lines automatically.
Looking ahead, we see a raft of applications for AI in the payments management field around analysing data with the end objective of spotting anomalies in it. With the short and frequent batches of payments data used within most enterprises today, it is unlikely that even the best trained administrator would be able to spot transactions that were out of the normal pattern. The latest AI technology could be used here to tease out anomalies and pinpoint unusual patterns or trends in spending that could then be investigated and addressed.
They also have the potential to shape the way that payments are made in the future. One of the hottest topics currently under discussion across the commercial payments sector is the thorny issue of integrated intelligent payments. How can enterprises use the latest available artificial intelligence technology to work out the best possible payment option for each individual transaction?
Accounts payable teams will soon need to be able use payments platforms to assess not only how much working capital they have on their corporate cards and what rates they have on their purchasing cards but also what the most sensible choice for payment method would be for each every payment, be it BACs, wire, cheques or even just old-fashioned accounts payable.
Indeed, there is likely to soon be a case for this kind of technology to effectively ‘fit in’, in process terms, between the accounts payable department, and the payment itself, helping the business decide what makes best sense for them as a payment methodology based on the business rules and existing deals that they have in place today.
Future Prospects
We also see a raft of applications for AI in the payments management field around analysing data with the end objective of spotting anomalies in it. With the short and frequent batches of payments data used within most enterprises today, it is unlikely that even the best trained administrator would be able to spot transactions that were out of the normal pattern. The latest AI technology could be used here to tease out anomalies and pinpoint unusual patterns or trends in spending that could then be investigated and addressed.
While this area remains in its infancy within the banking and financial services sector, with technology advancing, financial services organisations and the enterprise customers they deal with will in the future will be well placed to make active use of AI that will help clients track not just what they have been spending historically but also to predict what they are likely to spend in the future.
AI will ultimately enable businesses to move from reactive historical reporting to proactive anticipation of likely future trends. We are entering an exciting new age.
Far from taking human jobs in future, Artificial Intelligence (AI) and Machine Learning (ML) technologies are going to free up finance professionals from spending too much time on monotonous tasks and allow them to focus on more strategic tasks of higher value to the business. Does this mean that finance roles will mostly be driven by robots? Below Tim Wakeford, VP of financials product strategy EMEA at Workday, discusses with Finance Monthly.
A recent EY study revealed that the majority (65%) of finance leaders said that having standardised and automated processes—with agility and quality built into those processes—was a significant priority when it came to investing in emerging AI and other technologies. And, following on from this, 67% of finance leaders said that improving the relationship between finance and the wider business strategy was also a key priority.
Again, this is an area where automation and AI technologies are helping free up time for finance to spend more time working with other teams within the business. This enables them to figure out where to go next as opposed to looking backwards and dealing with unproductive and time-consuming legacy finance systems.
Freeing up talent to focus on high-value tasks
Freeing people up from repetitive jobs to enable them to focus on high-value tasks is the opposite of the oft-cited “robots putting people out of work” narrative.
Indeed, automation is a huge opportunity to reduce the unnecessary burden and pressure that’s put on finance professionals, particularly around traditional tasks such as transaction processing, and audit and compliance.
The adoption of AI applications within finance enables forward-thinking executives to move info far more strategic business advisory roles. This means that they can focus less on number crunching and more on financial analytics and forecasting, strategic risk and resilience, and compliance and control. This shift to data-driven financial management delivers a much wider benefit across the business.
The Rise of the robots: AI in finance
Computer systems performing tasks that previously required human intelligence is the definition of AI, with experts viewing AI and automation as viable solutions to efficiently deal with compliance and risk challenges across different sectors.
With the rise of the ‘big data’ era comes a parallel growth in the need to analyse data for financial executives to be able to properly manage compliance and risk.
This is another reason why finance teams cannot ignore the opportunities that embracing AI technologies offers them. It allows them to process vast amounts of data faster and easier than large teams of humans can.
Individuals are then able to make better strategic decisions based on the information that AI is able to rapidly extract from what were previously time-consuming and repetitive and monotonous tasks such as transaction processing.
Jobs least likely to go to robots
Forward-thinking and highly-skilled financial executives are happily embracing AI, as they see the clear opportunity it presents to play a more valuable and strategic role within their organisation.
“The challenge for managers will be to identify where automation could transform their organisations, and then figure out where to unlock value, given the cost of replacing human labour with machines and the complexity of adapting business processes to a changed workplace.” This is how writers James Manyika, Michael Chui and Mehdi Miremadi so fittingly describe the process in their book These Are the Jobs Least Likely to Go to Robots.
“Most benefits may come not from reducing labour costs but from raising productivity through fewer errors, higher output, and improved quality, safety, and speed.”
AI and automation in finance has to be about reducing repetitive manual tasks and raising overall productivity through data-driven business strategy. The bottom line is this: any technology that can reduce manual input and the associated human errors for transaction processing and governance, risk, and control (GRC) will free up finance professionals for more strategic work.
Any organisation’s most important asset is its people. And finding out which emergent AI technologies and applications are the best for a business and its people is going to be key for the future of finance.
Giving skilled finance staff the autonomy and opportunity to move into far more strategic data interpretation roles and letting the machines take on the grunt work is a necessary shift in the finance function.
As well as automating a large part of the finance function, AI technology will also help skilled finance executives to make a far more sophisticated analysis of complex data sets and to provide genuinely valuable insight to drive the business forward.
There is very little doubt that the future of finance will be one that embraces technological innovations to improve effectiveness, increase efficiency, and enhance insight.
Headquartered in Montreal, Canada, Interfacing Technologies Corporation (Interfacing) has been developing award-winning software solutions for over two decades, serving both large & small organisations across the world. Recognised as not only a pioneer, but also a leader in the field (within Gartner® Enterprise Business Process Analysis, Business Operating Systems & Operational Intelligence reports), the company provides quality management technological solutions to document, analyse, improve, and govern process, risk and performance data.
This month we caught up with Scott Armstrong, Managing Partner and one of four owners of Interfacing, who discussed the company’s commitment to continuously innovate and redefine the future of business software solutions.
Interfacing Technologies dates back to the early 80s – can you tell us more about the history of the company and its commitment to process? How have Interfacing’s solutions evolved? What are the company’s mission and values today?
Originally, Interfacing was a small IT consulting company. In the early 90s, the company was part of a large research and development MRP project which was funded by the National Research Council of Canada and included some big players such as Nortel at the time. As a result of the company’s participation in the project, in 1994 Interfacing released one of the first process modelling and simulation tools.
With the advancement of the World Wide Web and as Business Process Reengineering (BPR) evolved into Business Process Management (BPM) in the early 2000s, Interfacing launched one of the first web-based collaborative centralised repository solutions – the Enterprise Process Center® (EPC). To date, this is our flagship product and we are currently on version 10 (a.k.a. EPC X) – the revolutionised next generation of the platform - fully cloud-based, mobile ready and architected utilizing the latest & greatest highly scalable technology stack. Interfacing has been a player for many years, however, the change of ownership and management team four years ago is what catapulted the company forward and continues to fuel the growth today. Interfacing’s mission is to empower organisations to efficiently govern business complexity and transformation through process based quality, continuous improvement and compliance management solutions. I’m proud to share that the vision, team, and technology are stronger now than ever before!
What is the current state of the market and how does your solution align?
The need for automation is now well beyond to increase productivity, the digital age has forced companies to re-evaluate their core product and service offerings. The need to reassess what their company does as a business and apply changes to adapt to the digitisation of their industry is a big driver for our growth. Every industry is undergoing massive changes connected to digitisation, so with such large-scale digital transformation projects comes the need for major business transformation.
Our repository based knowledge management platform is designed to assist with requirements gathering, system configuration and deployment training. The platform provides the organisation with a blueprint of the current and future state and a tool to support the ongoing change management – every user can see the previous process versus the current process, what has changed, why it has changed, where they do their new work and how to do it. In effect, offering searchable mobile Digital Standard Operating Procedures (SOPs) with video work instructions.
With digitization and the fast pace of technologies’ ongoing evolution came the need for increased agility. The Enterprise Process Center®’s Rapid Application Development (RAD) module supports low-code development and workflow automation. The EPC RAD platform is unique in the BPMS market because it supports not only process and case management event based automation but transactional and data driven application types as well! With graphical editors for data modelling, web forms design, process mapping, rules configuration, and dashboard creation, the EPC RAD solution helps companies create and continuously improve an application with relatively low amount of time and effort.
What trends do you expect in digital transformation in 2018 and how will these affect the products that Interfacing offers?
The main trend that we’re seeing is the role of Artificial Intelligence (AI) and Robotics in automation. The way we're planning to leverage AI in terms of our technology base depends on the module. Our KPI module for example could leverage AI by providing predictive analytical insight to help our customers foresee issues before they arise. Within automation, the software could provide more information at the point of decision making based on the trends of historical actions and with the addition of robotics even remove the need for any human intervention within certain use cases.
A progressive trend in the process analysis is space is customer journey mapping. Before the internet and social media, customer experience didn’t have such a direct impact and influence on a customer’s buying patterns. In today’s digital age, the customer is spoilt for options when it comes to finding a specific service or product and can easily compare these options by doing quick research online. Fuel this with the fact that a customer is more probable to make the effort to post a review about a negative experience than a positive one and hence the heightened importance of mapping your customers’ journey. Historically, businesses were focused on trying to improve their internal process to reduce things like cost, duration, delay, without paying much attention to how this impacts the customers’ experience. What is truly remarkable about our tool is that it not only allows businesses to map their customers’ journey, but they can connect the customers’ touch points to their internal operations to visualize the handoffs within a single diagram. This transparency provides clarity in relation to the areas that need to be evaluated, revised and improved in real-time, in turn increasing corporate agility. It’s important that we continue to invest in this area, as intelligence will be increasingly more available to consumers and more and more services will become online-only.
A big portion of our readers are in finance, can you please tell us a bit about Interfacing’s Governance, Risk Management and Compliance (GRC) solution?
Interfacing’s Enterprise Process Center® has evolved beyond process analysis and automation to offer a comprehensive solution for GRC Management. The ability to bridge the gap between risk, compliance, audit and the continuous improvement teams is another major differentiator of the EPC. With constant new legislation forcing organizations to regularly adapt their policies and rules to ensure compliance, professionals are looking for a way to better understand downstream impacts and manage change. To achieve this, corporations and other organizations must leverage technology to minimize the impact and amount of manual work needed to comply. Companies’ focus on vision, objectives and performance should always be their number one priority, not compliance!
Our tool offers policy, rule and requirement management that simplifies companies’ effort to adapt. Thus, if a law changes, users can immediately see all the potential implications – and how the law change will impact specific policies, rules, processes, risks, controls, roles and systems. Additionally, customers can break down their corporate high-level risks (ERM - enterprise risk management) down to the operational level and asses them against the controls that mitigate them. All risks and controls are reusable allowing customers to reassess each risk by process as well. Our platform not only documents risks and controls, but it also monitors key risk and control indicators – something that a lot of other products don’t do. This provides companies with the ability to track their risk mitigation strategies on an ongoing basis and react before going into the red, instead of having to wait until the end of the quarter once an audit is carried out to understand what went wrong. The EPC does support auditors as well though – from planning, to scheduling, to executing, through to reporting, the EPC offers a complete audit management solution. Finally, governance is at the core of our system, the EPC manages versions, tracks all audit trails, enforces security and ensures all stakeholders’ approvals are received before publishing a change.
Interfacing has been labelled a “Game Changer” by our team of analysts, what makes Interfacing stand apart from the rest?
Beyond our deep roots and understanding of the market, what differentiates Interfacing’s Enterprise Process Center® from its competitors is the value it brings to a diverse number of groups within an organization and the high level of adoption by end-user employees. We noticed a big gap in the market whereby processes were being used by multiple teams within an organization but usually not consolidated into one solution and never truly rolling out to every employee across the entire organization. For example, within a company, you may have business analysts leveraging such a tool for process improvement, audit department mapping for compliance and risk assessment or IT documenting requirements for a system deployment and automation project, however, the reach tended to be confined and limited. At the end of the day, it becomes difficult to gain the real value out of the effort of documenting processes, procedures, roles, risks, rules, controls, KPIs, etc. if they’re not rolled out to the people that require this knowledge to complete their daily tasks. Thus, our entire focus when redesigning our flagship platform was the end-user. Today, we offer truly a corporate-wide software that provides transparency at all levels of the organization and gives every employee a voice. Within the current digital landscape and fast pace of technological change, agility is a must to remain competitive. The need to collect feedback and continuously improve one’s processes, products & services on an ongoing basis is more important now than ever before.
For more information, please go to: https://www.interfacing.com/ or https://www.linkedin.com/in/solution/
By Jan Hoffmeister, Managing Partner at Drooms
Q, the first cinema robot appeared in The Master Mystery in 1919. Ever since then we have seen fictional automatons of various shapes and sizes wreak havoc on the human race.
It’s perhaps not surprising that deep suspicion of the role of robots in business and their impact on the way we work has developed over time. But the truth is that robotics and artificial intelligence (AI) are set to introduce huge benefits to the finance sector in particular.
AI research was founded in a workshop at Dartmouth College in 1956 and those who attended became the leaders of AI research for decades. Their ambitious predictions for a machine that would be as intelligent as a human being attracted generous funding, which led to the development of a robot by the AI centre of Stanford Research Institute called ‘Shakey’ (1966-1972) controlled by a large computer.
By the early 1970s it was clear that AI was in trouble, largely because of hardware limitations. But the doubling of processing power every year under Moore’s Law meant that by 1996 IBM was able to build Deep Blue, a chess-playing computer that famously beat world champion Garry Kasparov.
Fast forward to 2014, and Google invested US$400 million in artificial intelligence start-up DeepMind. While the media discussion about AI has gravitated towards the idea that machines will replace humans and leave them with nothing to do, the fact is that AI is not about to automate most financial professions. Rather, it aims to complement human intelligence.
Recently, Google founded the People + AI Research Initiative (PAIR) to better explore these interactions with the support of researchers from MIT. The financial industry has also understood the potential hidden in the application of AI. Of the 5,000 FinTech start-ups identified by a 2016 report by Ernst & Young, a large number are set to bring intelligence to the banking world.
Fields where AI is particularly relevant include client servicing, trading, post-trade operations such as reconciliations, transaction reporting, tax operation and enterprise risk management.
A study released in 2017 by PwC points to a similar trend: ‘AI will gradually replace humans in some functions like personal assistants, digital labour, and machine learning. But challenges will persist because of bias, privacy, trust, lack of trained staff, and regulatory concerns. Augmented intelligence, in which machines assist humans, could be the near term answer.’ Future decision-making processes in banking, for instance, will be 34% informed by machine algorithms and 66% by human judgment.
A sub-field of AI is a particularly strong example of applications of augmented intelligence – Natural Language Processing. NLP is the development of systems capable of reading and understanding the languages that humans speak.
At the heart of this technology is the ability to interpret a large amount of so-called ‘unstructured data’ (i.e. data that cannot be read by machines yet, such as PDF files, images and audio material). The FinTech sector is leveraging this technology because it significantly improves customer interactions, and not only by implementing chatbots.
The finance industry is a knowledge-intensive sector and key tasks require the reading and understanding of large amounts of information that are only partly structured. NLP is making processes much easier, faster and more precise with less effort than ever from humans.
Start-ups such as MonkeyLearn are already leveraging NLP to automate business intelligence information, whereas leading Japanese asset manager Nomura Asset Management (NAM) are investing to understand whether this technology can improve the decision-making processes of portfolio management’s investors. Even providers of legal services are turning towards NLP, automated document analytics and law case reporting within due diligence processes.
Putting users at the heart of the software was our goal in developing the new virtual data room, Drooms NXG. Aware of the fact that the biggest issue for data room users was to keep up with time-consuming and demanding document analysis, the implementation of the most effective technology was required. As NLP enables the reading and understanding of language, we saw a huge opportunity to apply this new technology to the content of data room documentation.
Today, the data room of Drooms NXG can present information to users thanks to smart pre-set categories, suggested red flags, lists of documents by relevance and recommendations for smarter risk management. When users search their VDR for terms in order to find potential red flags chosen from the categories listed by Drooms NXG Findings Manager, the system returns a ‘Suggested Findings’ list which can be categorised as very low, medium or high level risk or opportunity. Professionals can add their own categories or edit existing keywords to make their searches as focused as possible. Individual calls to action can be assigned to each one; adding an individual note to highlight specific insight, incorporating a link to a document, page or even a paragraph or single word; or using a colour coding system by selecting one of the built-in colour tags. Similarly, we wanted to address language barriers between users. Now, documents can be instantly translated within the data room, thereby facilitating cross-border deals.
These solutions were not developed with the goal of replacing manpower with automated data analysis. On the contrary, our goal is to empower deal experts by developing intuitive tools that don’t feel like a burden, but make their decision-making more accurate and their business lives more successful.
According to McKinsey’s 2017 survey, early AI adopters that combine strong digital capability with proactive strategies have higher profit margins and expect the performance gap with other firms to widen in the next three years. Financial firms should no longer be concerned that the robots are coming, only that they harness the power of robotics and AI to improve the service that they provide to customers.
Website: https://drooms.com
The AI technology has been picking up steam in the past couple of years. It’s no longer a gimmick or a faraway fiction. Scientists from all around the world are slowly but surely cracking this riddle. Sure, they are still a long journey away from creating a true Artificial Intelligence, but each year we see significant breakthroughs in this field.
Today, you can find some form of AI in many everyday places. For example, Alexa and Siri are world famous AI assistants. They will create appointments, answer your questions, set alarms, shop, and a million other things. Another great example is the Tesla car. Thanks to Tesla’s AI, self-driving cars are no longer a work of fiction.
But what about the poker industry? Surely there must be an AI capable of playing poker at high levels. The answer is yes, there is. This infographic will show you how the poker’s AI developed throughout the history, as well as where it is now. You can find a lot of interesting stats and information in this infographic, but if you are interested in reading more about poker related stuff, visit our website.
Below Mark Boulton, Insurance Sector Lead at Fujitsu UK&I, delves into the introduction of automation and AI in the insurance sphere, touching on the future prospects of the insurance sector throughout 2018.
Insurance has always been a grudge purchase, often seen as a necessity or safety net, but not something that immediate benefit is felt from.
It will have been frustrating for many, therefore, to see that car insurance premiums have risen by 11% on average in the last year alone, according to the Association of British Insurers (ABI).
Many of us may even start to question the value we’re getting for our insurance purchases in light of such news.
The price – which is the most important factor in choosing an insurance package (A New Pace of Change, Fujitsu) – is just one element, however. Compounding this situation is the fact that people often find insurers difficult to deal with, particularly when trying to make a claim.
It’s this group of factors that demonstrate the opportunity the insurance industry has to transform itself into a more value-driven service for customers.
At the heart of any change will be technology, and two of the leading areas here are Artificial Intelligence (AI) and automation. How is technology impacting insurance for the better? There are three main areas to consider - customer experience, assessments and risk mitigation.
Personalisation
Think of going through a process for a life insurance policy. Multiple in-depth questions to taken into account age, lifestyle, and health, with an existing model applied to the answers provided.
Such models have been used for decades at some companies, resulting in off-the-shelf packages for people that do not necessarily reflect them as individuals.
Technology is helping change this. Based on any assessment and wider data analytics, automation can quickly produce more personalised experiences for the customer. This might be a payment model that suits their lifestyle or financial situation or a more nuanced insurance package to reflect their needs.
Such personalisation sit at the heart of the transformation. We’ve seen this across other industries, and it is one crucial way insurers can start to move from transactional-based relationships to value-based relationships with their customers.
Convenience and speed
It’s not just adding value of course, it’s getting the basics right. Services like Amazon Prime and Netflix have totally transformed the expectations we have of all companies when it comes to speed and convenience. We want things served to us exactly how we want them, and quickly.
Insurers have certainly made progress in recent years – for example, it is standard now for policies to be quoted and purchased online. More interestingly, however, is the use of apps and chatbots.
These give a holiday maker who may have lost their camera easy access to their policy, but also the chance to ask questions to the chatbot. Powered by AI, we can expect chatbots to play an increasingly important role in the relationship between insurers and policy holders.
Given the often complex nature of insurance policies, chatbots can be a simple way for people to get the answers they need. No need to phone customer services or wait an hour in a call queue; just direct answers delivered instantaneously.
Of course, there is still progress to be made with chatbots, but these will only get better in the years to come.
Apps and chatbots are also interesting because they both rely on and deliver vast amounts of data. The more these are used, the more they can be refined to give people services that suit them better. They fuel the personalised services.
Working together
It’s all very well talking about the benefits and transformative powers of technology, but making these a reality is something many organisations are grappling with.
Something I’ve observed in the financial services industry is the existence of distinct groups of employees. On the one hand, there are those innovation-focused, digital savvy experts who want agility, speed and flexibility. On the other hand, there are those who want to focus on the central facets of their areas products - keeping those long-standing traditions working in good order for the customer.
These two groups are naturally at odds. They often speak in different terms, work in different ways, and approach problems completely differently. Imagine the kinds of conversations that might come up with discussing emerging trends like AI and automation. It’s not easy for them to get to the place they need to.
To be able to respond to the concerns being voiced by consumers, and to harness the business agility needed to respond to market trends, insurance businesses from the c-suite down need to make a culture shift. Driving change from the top is the only way to future proof the business in a digital world that has already changed the state of play for good. We simply cannot afford to rely on the same rules.
Find your digital path now
Our ‘Fit for Digital’ survey found 98% of insurers believed their organisation had been affected by digital. A further 72% said their sector would fundamentally change in the next four years.
Change is inevitable. And the technology that will enable that change - including AI and automation – is here today. Insurers must find the cultural harmony to embrace new digital services and products, without losing the heart of what they already do well.
The next few years will see some insurers thrive and others struggle. To be a thriver, it’s vital to the right digital path now.
Anticipation, scepticism and fear are holding more Brits than Americans back from embracing Artificial Intelligence (AI) in the workplace, according to a new study by CITE Research for SugarCRM.
The research on business executives in the US and UK reveals that that Brits are lagging behind when it comes to adopting Artificial Intelligence (AI) technologies into their work and personal lives. The survey reveals that 47% of Brits are currently using technology powered by AI in the workplace, compared with 55% of Americans. This trend transcends into people’s personal lives, with 62% of Brits and 64% of American’s using AI for non-work-related tasks, such as Amazon Alexa or Google Home.
The research also highlighted that when looking ahead, Brits are less open to embracing AI in the future. 69% of American respondents plan to deploy AI in the next two years, compared to 57% in the UK. Brits were twice as likely not to ever want to use AI, with one in five respondents (20%) opposing the technology, compared with 1 in 10 Americans.
Top concerns about AI on both sides of the Atlantic revolve around trusting the technology. More than half of respondents (52%) worry about data security, with 30% saying it is their top concern. Another 40% said they fear AI technology will make errors, and 41% fear losing control over the data. While 30% said they fear job loss because of AI, only 12% list it as their top concern.
When it came to the applications for AI in the world of work, US participants were more likely than Brits to say they would want AI to help with communication with customers (54% vs. 42% of Brits) or planning their day (46% vs. 35%). Automating data entry was the most popular task across the board for AI, with more than half (53%) believing it would help in their organisation, followed by gathering information on the internet (51%).
“The results of CITE Research’s survey reflect the industry's view on “the cloud” “big data” and other disruptive technologies over the years, said Clint Oram, CMO and co-founder at SugarCRM.
“You have a group that is ready to jump in with both feet and a group of naysayers who are absolutely against the technology. The rest of us are in the middle. Many have heard all the hype and are intrigued, but they would like some assurances that the positives will outweigh the negatives before they are ready to start spending money on AI tools.
“It’s interesting to see how attitudes differ across the Atlantic and that there is more reluctance from Brits in how AI can be used in their work. The technology offers the potential to reduce monotonous aspects of our working lives but there is a need to be realistic on its capabilities. It won’t replace people entirely and there is still a need for human interaction.”
In general, the survey showed that younger participants, those 34 or younger, were more excited and less fearful of AI. Younger participants were more likely to say their organisation will utilise it in the future (70%). Those 55 or older were more likely to worry about being overwhelmed with features they do not need (55% list this as a concern compared to 24% of those aged 18-54).
For the complete survey report, please visit here.
(Source: SugarCRM)
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