The last year has really pushed the Education sector into transforming both its teaching and learning practices. The urgency of the situation accelerated the use of networking to extend the reach and range of educational opportunities for remote learning.
Education technology has rushed to embrace opportunities to facilitate a new normal for Education. This new normal must enable and support education access, experiences, and outcomes as well as aid in developing strong relationships within Education ecosystems.
Education technology, commonly known as EdTech, focuses on leveraging emerging technologies like cloud and AI to deliver interactive and multimedia coursework over online platforms. This also requires a state-of-the-art network to support. 5G provides instantaneous access to cloud services. Use of 5G – as well as network function virtualisation (NFV), network slicing, and multi-access edge computing (MEC) – has the capability of delivering significant performance benefits across these emerging educational applications and use cases.
At present, many educational institutions are aware of the possibilities, but are not active users of 5G network infrastructure (Figure 1).
Educational institutions plan to do some near-term investments but are not clear in what areas to apply the enhanced capabilities (Figure 2).
Role of the Network in Adaptive Learning
In their recent whitepaper, network provider Ciena talks about “the concept of an adaptive learning strategy – a technology-based teaching method that replaces the traditional one-size-fits-all teaching style with one that is more personalised to individual students. This approach leverages next-generation learning technologies to analyse a student’s performance and reactions to digital content in real-time, and modifies the lesson based on that data.”
To create an adaptive learning strategy that can be individualised, these learners need to be enabled by technology to be immersed in a learning experience, complete with multimedia and access to a knowledge base for information. And this is where a solid 5G network implementation can create access and bandwidth to the resources required.
Example of 5G and Immersive Learning
An example of adaptive learning where the technology not only supports but challenges the learner can be found in a BT-led new immersive classroom developed within the Muirfield Centre in Cumbernauld, North Lanarkshire, using innovative technology to transform a classroom into an engaging and digital learning environment.
Pupils at Carbrain Primary School, Cumbernauld, were the first to dive into the new experience with an underwater lesson about the ocean. The 360-degree room creates a digital projection that uses all four classroom walls and the ceiling to bring the real-world into an immersive experience for students. The concept aims to push beyond traditional methods of teaching to create an inclusive digital experience that helps explain abstract and challenging concepts through a 3D model. It will also have the potential to support students with learning difficulties in developing imagination, creative and critical thinking, and problem-solving skills. BT has deployed its 5G Rapid Site solution to support 5G innovation and digital transformation of UK’s Education sector. The solution is made possible through the EE 5G network which brings ultrafast speeds and enhanced reliability to classrooms.
5G is expected to provide network improvement in the areas of latency, energy efficiency, the accuracy of terminal location, reliability, and availability – therefore creating the ability to better leverage cloud capacity.
With the greater bandwidth that 5G provides, learners and instructors, can connect virtually from any location with minimal disruption with more devices than on previous networks. This allows students to enjoy a rich learning experience and not be disadvantaged by their location for remote learning, or by the uncertainty of educational access. This also provides more possibilities of exploration and discovery beyond the physical confines of the classroom and puts those resources in the hands of eager learners.
As educational institutions reopen, institutions are looking at ways to redesign the education experience. Connected devices are helping schools and universities expand the boundaries of education. Explore what the IoT-enabled future of education would look like
Many opinions exist on how automation and machine learning will help our return to the office environment. Removing physical touchpoints and leveraging machine learning to trace employee behaviour can help with the transition back to the workplace. But will people trust the office’s automated suggestions on where to work in the building, or help themselves to alternative workspaces?
Processes & Trust for People Engagement
Organisations such as Disney and Amazon understand what kinds of processes and trust it takes to engage people. These organisations took their time to create a vision of the contactless trusted experience before developing an implementation plan. The RFID wristbands at Disney that open hotel doors and get you on to rides involve many elements of trust and privacy. The automated order and delivery tracking of Amazon, along with suggestions and buying patterns, require the person to opt-in and share information to make happen.
So for your company, once employees re-enter the workplace, how will your company create those processes, that level of trust and faith, that would allow movements and health status to be tracked by office automation? For example, how often should employees overtly be aware of their temperature being scanned?
Abilities of Buildings to Manage
Facilities management is trending towards intelligent building management systems (iBMS) which know about room occupancy, room hygiene and are tracking who has been where and with whom. Elevators will limit occupancy and direct users to the correct lift going to the correct location. I have already seen this in our city hospital where you get directed to the correct lift once you have entered information on your destination. This combines user interface devices such as touchless pads, system hardware, and access control management software.
The building can also possibly direct you via a building app to request a place to work. You could swipe your personnel card and then be shown several options based on your personal profile and job role, including private quiet rooms, communal areas, and outside meeting tables. Previous occupants can be noted to share hygiene tracing if necessary. Intelligent buildings already offer direct support to the employees who interact with them for HVAC, lighting control, and occupation sensor. They have the ability to reduce user friction while raising workplace experience metrics to create a measured environment.
User Trust & Participation
Users should be willing to participate to get access. To create the trust that is required for employees to be willing to participate in the process, companies need to share policies and demonstrate stewardship of the data accessed. Who is holding my locational data, for how long, and for what purpose?
Trust facilitates successful data sharing, which in turn reinforces trust. Trust is built when the purpose of data sharing is made clear, and when those involved in the process know each other, understand each other’s expectations, and carry out their commitments as agreed. Trust increases the likelihood of further collaboration and improves core surveillance capacity by supporting surveillance networks.
Will we put our trust in buildings and facilities management on our return to the office? If communication is clear and policy well articulated, the building can play a role in engaging users to return to some standards of in-office participation. But if communication is muddy and policy not made clear, people will make their own way to safety – potentially impacting the environment of others.
Transform and be better prepared for future disruption, and the ever-changing competitive environment and customer, employee or partner demands in 2021. Download Ecosystm Predicts: The top 5 Future of Work Trends For 2021.
We are heading into the one-year anniversary of global COVID confinements. This confinement period has seen the Hospitality industry impacted strongly by the lack of mobility of populations and government regulations. Hotels had previously used a consistent flow of booking and revenue information using historical and current pricing data from distribution and revenue management tools. They adapted in the “new normal” and the evolution of hotel infrastructure during this period – forced by necessity – has led them to try to create a contactless, more automated interaction, both for efficiency and for the work-from-home status of many employees.
Ecosystm research shows the digital technology focus of the industry to address the necessary shifts, in 2021 (Figure 1).
Distribution Data in the New Normal
Hotels are still struggling to get a clear overview of demand forecasting. Their data infrastructure is evolving and will continue to evolve to tackle this problem. The reliance on distribution information had to shift as fluidity in bookings could not rely on historical norms.
Hotels use a complex structure of promotion via distribution channels. This included direct booking via websites or central call centres, and use of online travel agents (OTAs), bed banks and wholesalers. That mix of channels was monitored and managed by the properties to leverage across these channels to optimise room occupancy. Over the past decades there has been an increased reliance on OTAs. But in more recent years, many hotel players have pushed back, promoting direct bookings made through own website booking engines or other direct means.
The pandemic has disrupted this complex orchestration of data. Moving from 65-75% occupancy to 10-15% was not financially viable for hotels. Because the pandemic reduced demand, both direct booking and OTA bookings have grown their share at the expense of other channels such as bed banks and global distribution systems (GDS). Guests wanted confirmation of the status of the hotel and what services were available, so data with extra content from the hotel itself or frequently updated OTA services were reliable.
Building Better Bundles and Contact Points
The goals for many hotels were to create frictionless digital customer journey (preferably by brand), leveraging existing infrastructures and integrating them to mobile apps, more robust CRM, and a more flexible property management set of tools. Part of that integration was having newly launched hygiene initiatives and branding those as part of the offering.
New bundles and packages were created to deal with the hygiene constraints and the new form of guest stays (daycation, staycation, remote learning) that have developed from the pandemic conditions.
Workcations using the hotel facilities as a workplace became attractive for those stuck at home with many interruptions. InterContinental Hotels Group, Marriott and Accor are among the major names that have launched or are considering monthly payment plans, as the hotel industry tries to attract restless remote workers ready for a change of scene.
The disconnect in guest information is being addressed by rebuilding the infrastructure of the guest journey – tracking their pre-stay investigation and booking interaction, the kind of on-property engagement they have with the hotel and its staff, their in-room experience, and their sharing of feedback on social media post-stay are all part of their guest experience.
Multiple business priorities will guide the industry in 2021 (Figure 2).
For the hotels serving different customer segments, specific actions were initiated.
- For the economy hotel chains, the flow of customers was not that significantly different, but how they booked and how many rooms they needed changed. This was handled more at the individual hotel property level as different COVID constraints applied to different regions.
- Larger chains already had their property management systems (PMS) set up as tied to a centralised structure, but a chunk of their business (leisure, corporate and business events) was directly tied to the restrictions on the domestic population and inability to access international guests.
- For luxury brands, it was a bit of a challenge as the hygiene aspect impacted the use of several extras that luxury brands rely on, such as spas, one-to-one interaction and facilities.
- Independent hotels needed some guidance that they were not getting from historical norms. Many went to external infrastructure providers to try to create workflow processes that would help them stay afloat.
Technology investments: Some Examples
One of the first concerns of regional travellers was the operational status of the hotel. One example of a digital investment was the Louvre Hotels Group, Europe’s second-largest hotel group that used used its ‘Résa Pro’ dedicated reservation platform for working professionals. It showed the listing of available accommodation per city and region for business travellers to meet the accommodation and catering needs of retail and sales professionals. Using this digital platform, companies could locate the Group’s open hotels in the city or region of their choice and see what guest offering best suited their requirements.
This webcast of Radisson’s Remy Merckx and Managing Director Sally Richards from RaspberrySky is a great example of building a digital platform to restructure the guest experience. Radisson outsourced the building of a digital platform that linked their eight hotel brands under one platform for a consistent digital experience, leveraging mobile, social and cloud technologies. The higher engagement rate with the mobile app and the chatbot helped create the contactless experience the guests are now looking in their accommodation journeys.
Many brands are now focusing on app-centric approaches for the guests, adding the value of human engagement for the more complex tasks. The emphasis is on the brand and digitising the guest journey to make it more customer-centric. This has been a time of reflection for some of the more organised hotel chains to make the time investment into the digital journey, upskill and upscale their operations to be in line with customer engagement.
New Normal for Hotel Stays
But not every independent hotel or small hotel chain had that financial investment to make during this period. According to Ecosystm data, approximately 41% of hospitality firms put their digital transformation on hold in 2020 – higher than any other industry that we cover. Technologies that will see increased investments in 2021 included cloud collaboration (44%) and cloud enterprise solutions (23%).
What does cloud have to do with this? Cloud is part of the infrastructural investment that allows the Hospitality industry to connect and enable its participants throughout the ecosystem, enabling mobile and social as well. This enables service providers to engage with intermediary partners, travel agents and consolidators and consumers, hyperconnecting in ways that provide convenience, ease of use and seamless information retrieval to bed banks and timetables, from business rules to collaborative mapping of codes.
This use of technology transforms the elements of inventory and availability into experiences and destinations.
- Messaging tools help harmonise communication across the network.
- Monitoring apps manage factors that impact distribution health, including rate integrity, availability, and visibility.
- AI – for example in the form of voice assistants – helps guide consumers and partners to timely information and decision making.
But it will still be a blend of digital solutions and human interaction, where humans add the core competency and collective knowledge, and technology provides the seamless data exchange and network connectivity.
- Sally Richards at RaspberrySky
- Anders Johansson at Hospitality Visions
- Mark Haywood and Ankit Chaturvedi at RateGain
New Normal for The Hospitality Industry
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There is a lot of hope on AI and automation to create intellectual wealth, efficiency, and support for some level of process stability. After all, can’t we just ask Siri or Alexa and get answers so we can make a decision and carry on?
Automation has been touted as the wonder formula for workplace process optimisation. In reality it’s not the quick fix that many business leaders desire. But we keep raising the bar on expectations from automation. Investments in voice technologies, intelligent assistants, augmented reality and touchscreens are changing customer experience (Figure 1). Chatbots are ubiquitous, and everything has the potential to be personalised. But will they solve our problems?
100 percent automation is not effective
Let’s first consider using automation to replace face-to-face interactions. There was a time when people were raving about the check-in experience at some of the hotels in Japan where robots and automated systems would take care of the check-in, in-stay and check-out processes. Sounds simple and good? Till 2019, if you checked into the Henn-na Hotel in Japan, you would be served and taken care of by 243 robots. It was viewed by many as a template for what a fully automated hotel could look like in the future.
The hotel had an in-room voice assistant called Churi. It could cope with basic commands, such as turning the lights on and off, but it was found to be deficient when guests started asking questions about places to visit or other more sophisticated queries. It was not surprising that the hotel decided to retire their robots. In the end it created more work for the hotel staff on-site.
People love the personal touch when they are in a hotel; and talking to someone at the front desk, requesting assistance from hotel staff, or even just a short chat over breakfast are some of the small nuances of why the emotional connection matters. Many quarantine hotels today use robots for food delivery, but the hotel staff is still widely available for questions. That automation is good, but you need the human intervention. So, getting the balance right is key.
Empathy plays a big role in delivering great Customer Experience
Similarly, there was a time when many industry observers and technology providers said that a contact centre will be fully automated, reducing the number of agents. While technologies such as Conversational AI have come along where you can now automate common or repetitive questions and with higher accuracy levels, the human agent still plays a critical role in answering the more complex queries. When the customer has a complicated question or request, then they will WANT to speak to an agent.
When it reaches a point where the conversation with the chatbot starts getting complicated and the customers need more help there should be the option – within the app, website or any other channel – to escalate the call seamlessly to a human agent. Sometimes, a chat is where the good experience happens – the emotional side of the conversation, the laughter, the detailed explanation. This human touch cannot be replaced by machines. Disgruntled customers are happier when an agent shows empathy. Front line staff and human agents act as the face of a company’s brand. Complete automation will not allow the individual to understand the culture of the company. These can be attained through conversations.
Humans as supervisors for AI – The New Workplace
Empathy, intuitiveness, and creativity are all human elements in the intelligence equation. Workers in the future will need to make their niche in a fluid and unpredictable environment; and translating data into action in a non-replicable way is one of the values of human input. The essence of engineering is the capacity to design around human limitations. This requires an understanding of how humans behave and what they want. We call that empathy. It is the difference between the engineer who designs a product, and the engineer who delivers a solution. We don’t teach our computer scientists and engineering students a formula for empathy. But we do try to teach them respect for both the people and the process.
For efficiency, we turn to automation of processes, such as RPA. This is designed to try to eradicate human error and assist us in doing our job better, faster and at a lower cost by automating routine processes. If we design it right, humans take the role of monitoring or supervisory controlling, rather than active participation.
At present, AI is not seen as a replacement for our ingenuity and knowledge, but as a support tool. The value in AI is in understanding and translating human preferences. Humans-in-the-loop AI system building puts humans in the decision loop. They also shift pressure away from building “perfect” algorithms. Having humans involved in the ethical norms of the decision allows the backstop of overly orchestrated algorithms.
That being said, the astute use of AI can deepen insights into what truly makes us human and can humanise experiences by setting a better tone and a more trusted engagement. Using things like sentiment analysis can de-escalate customer service encounters to regain customer loyalty.
The next transformational activity for renovating work is to advance interactions with customers by interpreting what they are asking for and humanising the experience of acquiring it which may include actually dealing with a human contact centre agent – decisions that are supported at the edge by automation, but at the core by a human being.
Ecosystm research shows that process automation will be a key priority for technology investments in 2021 (Figure 2).
With AI and automation, a priority in 2021, it will be important to keep these considerations in mind:
- Making empathy and the human connection the core of customer experiences will bring success.
- Rigorous, outcome-based testing will be required when process automation solutions are being evaluated. In areas where there are unsatisfactory results, human interactions cannot – and should not – be replaced.
- It may be easy to achieve 90% automation for dealing with common, repetitive questions and processes. But there should always be room for human intervention in the event of an issue – and it should be immediate and not 24 hours later!
- Employees can drive greater value by working alongside the chatbot, robot or machine.
Ecosystm Predicts: The Top 5 Customer Experience Trends for 2021
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The disruption that we faced in 2020 has created a new appetite for adoption of technology and digital in a shorter period. Crises often present opportunities – and the FinTech and Financial Services industries benefitted from the high adoption of digital financial services and eCommerce. In 2021, there will be several drivers to the transformation of the Financial Services industry – the rise of the gig economy will give access to a larger talent pool; the challenges of government aid disbursement will be mitigated through tech adoption; compliance will come sharply back into focus after a year of ad-hoc technology deployments; and social and environmental awareness will create a greater appetite for green financing. However, the overarching driver will be the heightened focus on the individual consumer (Figure 1).
2021 will finally see consumers at the core of the digital financial ecosystem.
Ecosystm Advisors Dr. Alea Fairchild, Amit Gupta and Dheeraj Chowdhry present the top 5 Ecosystm predictions for FinTech in 2021 – written in collaboration with the Singapore FinTech Festival. This is a summary of the predictions; the full report (including the implications) is available to download for free on the Ecosystm platform.
The Top 5 FinTech Trends for 2021
#1 The New Decade of the ‘Empowered’ Consumer Will Propel Green Finance and Sustainability Considerations Beyond Regulators and Corporates
We have seen multiple countries set regulations and implement Emissions Trading Systems (ETS) and 2021 will see Environmental, Social and Governance (ESG) considerations growing in importance in the investment decisions for asset managers and hedge funds. Efforts for ESG standards for risk measurement will benefit and support that effort.
The primary driver will not only be regulatory frameworks – rather it will be further propelled by consumer preferences. The increased interest in climate change, sustainable business investments and ESG metrics will be an integral part of the reaction of the society to assist in the global transition to a greener and more humane economy in the post-COVID era. Individuals and consumers will demand FinTech solutions that empower them to be more environmentally and socially responsible. The performance of companies on their ESG ratings will become a key consideration for consumers making investment decisions. We will see corporate focus on ESG become a mainstay as a result – driven by regulatory frameworks and the consumer’s desire to place significant important on ESG as an investment criterion.
#2 Consumers Will Truly Be ‘Front and Centre’ in Reshaping the Financial Services Digital Ecosystems
Consumers will also shape the market because of the way they exercise their choices when it comes to transactional finance. They will opt for more discrete solutions – like microfinance, micro-insurances, multiple digital wallets and so on. Even long-standing customers will no longer be completely loyal to their main financial institutions. This will in effect take away traditional business from established financial institutions. Digital transformation will need to go beyond just a digital Customer Experience and will go hand-in-hand with digital offerings driven by consumer choice.
As a result, we will see the emergence of stronger digital ecosystems and partnerships between traditional financial institutions and like-minded FinTechs. As an example, platforms such as the API Exchange (APIX) will get a significant boost and play a crucial role in this emerging collaborative ecosystem. APIX was launched by AFIN, a non-profit organisation established in 2018 by the ASEAN Bankers Association (ABA), International Finance Corporation (IFC), a member of the World Bank Group, and the Monetary Authority of Singapore (MAS). Such platforms will create a level playing field across all tiers of the Financial Services innovation ecosystem by allowing industry participants to Discover, Design and rapidly Deploy innovative digital solutions and offerings.
#3 APIfication of Banking Will Become Mainstream
2020 was the year when banks accepted FinTechs into their product and services offerings – 2021 will see FinTech more established and their technology offerings becoming more sophisticated and consumer-led. These cutting-edge apps will have financial institutions seeking to establish partnerships with them, licensing their technologies and leveraging them to benefit and expand their customer base. This is already being called the “APIficiation” of banking. There will be more emphasis on the partnerships with regulated licensed banking entities in 2021, to gain access to the underlying financial products and services for a seamless customer experience.
This will see the growth of financial institutions’ dependence on third-party developers that have access to – and knowledge of – the financial institutions’ business models and data. But this also gives them an opportunity to leverage the existent Fintech innovations especially for enhanced customer engagement capabilities (Prediction #2).
#4 AI & Automation Will Proliferate in Back-Office Operations
From quicker loan origination to heightened surveillance against fraud and money laundering, financial institutions will push their focus on back-office automation using machine learning, AI and RPA tools (Figure 3). This is not only to improve efficiency and lower risks, but to further enhance the customer experience. AI is already being rolled out in customer-facing operations, but banks will actively be consolidating and automating their mid and back-office procedures for efficiency and automation transition in the post COVID-19 environment. This includes using AI for automating credit operations, policy making and data audits and using RPA for reducing the introduction of errors in datasets and processes.
There is enormous economic pressure to deliver cost savings and reduce risks through the adoption of technology. Financial Services leaders believe that insights gathered from compliance should help other areas of the business, and this requires a completely different mindset. Given the manual and semi-automated nature of current AML compliance, human-only efforts slow down processing timelines and impact business productivity. KYC will leverage AI and real-time environmental data (current accounts, mortgage payment status) and integration of third-party data to make the knowledge richer and timelier in this adaptive economic environment. This will make lending risk assessment more relevant.
#5 Driven by Post Pandemic Recovery, Collaboration Will Shape FinTech Regulation
Travel corridors across border controls have started to push the boundaries. Just as countries develop new processes and policies based on shared learning from other countries, FinTech regulators will collaborate to harmonise regulations that are similar in nature. These collaborative regulators will accelerate FinTech proliferation and osmosis i.e. proliferation of FinTechs into geographies with lower digital adoption.
Data corridors between countries will be the other outcome of this collaboration of FinTech regulators. Sharing of data in a regulated environment will advance data science and machine learning to new heights assisting credit models, AI, and innovations in general. The resulting ‘borderless nature’ of FinTech and the acceleration of policy convergence across several previously siloed regulators will result in new digital innovations. These Trusted Data Corridors between economies will be further driven by the desire for progressive governments to boost the Digital Economy in order to help the post-pandemic recovery.
Ecosystm Predicts: The Top 5 FinTech Trends for 2021
The full findings and implications of the Top 5 FinTech Trends for 2021 are available for download from the Ecosystm platform. Create your free account to access more from the Ecosystm Predicts Series, and many other reports, on the Ecosystm platform
Environmental, social, and governance (ESG) ratings towards investment criteria have become popular for potential investors to evaluate companies in which they might want to invest. As younger investors and others have shown an interest in investing based on their personal values, brokerage firms and mutual fund companies have begun to offer exchange-traded funds (ETFs) and other financial products that follow specifically stated ESG criteria. Passive investing with robo-advisors such as Betterment and Wealthfront have also used ESG criteria to appeal to this group.
The disruption caused by the pandemic has highlighted for many of us the importance of building sustainable and resilient business models based on multi-stakeholder considerations. It has also created growing investor interest in ESG.
ESG signalling for institutional investors
The increased interest in climate change, sustainable business investments and ESG metrics is partly a reaction of the society to assist in the global transition to a greener and more humane economy in the post-COVID era. Efforts for ESG standards for risk measurement will benefit and support that effort.
A recent study of asset managers by the investment arm of Institutional Shareholder Services (ISS) showed that more than 12% of respondents reported heightened importance of ESG considerations in their investment decisions or stewardship activities compared to before the pandemic.
In the area of hedge funds, there has been an increased demand for ESG-integrated investments since the start of COVID-19, according to 50% of all respondents of a hedge fund survey conducted by BNP Paribas Corporate and Institutional Banking of 53 firms with combined assets under management (AUM) of at least USD 500B.
ESG criteria may have a practical purpose beyond any ethical concerns, as these criteria may be able to help avoidance of companies whose practices could signal risk. As ESG gets more traction, investment firms such as JPMorgan Chase, Wells Fargo, and Goldman Sachs have published annual reports that highlight and review their ESG approaches and the bottom-line results.
But even with more options, the need for clarity and standards on ESG has never been so important. In my opinion, there must be an enhanced effort to standardise and harmonise ESG rating metrics.
How are ESG ratings made?
ESG ratings need both quantitative and qualitative/narrative disclosures by companies in order to be calculated. And if no data is disclosed or available, companies then move to estimations.
No global standard has been defined for what is included in a given company’s ESG rating. Attempts at standardising the list of ESG topics to consider include the materiality map developed by the Sustainable Accounting Standard Board (SASB) or the reporting standards created by the Global Reporting Initiative (GRI). But most ESG rating providers have been defining their own materiality matrices to calculate their scores.
Can ESG scoring be automatically integrated?
Just this month, Morningstar equity research analysts announced they will employ a globally consistent framework to capture ESG risk across over 1,500 stocks. Analysts will identify valuation-relevant risks for each company using Sustainalytics’ ESG Risk Ratings, which measure a company’s exposure to material ESG risks, then evaluate the probability those risks materialise and the associated valuation impact. ESG rating firms such as MSCI, Sustainalytics, RepRisk, and ISS use a rules-based methodology to identify industry leaders and laggards according to their exposure to ESG risks, as well as how well they manage those risks relative to peers.
Their ESG Risk Ratings measure a company’s exposure to industry-specific material ESG risks and how well a company is managing those risks. This approach to measuring ESG risk combines the concepts of management and exposure to arrive at an assessment of ESG risk – the ESG Risk Rating – which should be comparable across all industries. But some critics of this form of approach feel it is still too subjective and too industry-specific to be relevant. This criticism is relevant when you understand that the use of the ESG ratings and underlying scores may in future inform asset allocation. How might this better automated and controlled? Perhaps adding some AI might be useful to address this?
In one example, Deutsche Börse has recently led a USD 15 million funding round in Clarity AI, a Spanish FinTech firm that uses machine learning and big data to help investors understand the societal impact of their investment portfolios. Clarity AI’s proprietary tech platform performs sustainability assessments covering more than 30,000 companies,198 countries,187 local governments and over 200,000 funds. Where companies like Cooler Future are working on an impact investment app for everyday individual users, Clarity AI has attracted a client network representing over $3 trillion of assets and funding from investors such as Kibo Ventures, Founders Fund, Seaya Ventures and Matthew Freud.
What about ESG Indices? What do they tell us about risk?
Core ESG indexing is the use of indices designed to apply ESG screening and ESG scores to recognised indices such as the S&P 500®, S&P/ASX 200, or S&P/TSX Composite. SAM, part of S&P Global, annually conducts a Corporate Sustainability Assessment, an ESG analysis of over 7,300 companies. Core ESG indices can then become actionable components of asset allocation when a fund or separately managed accounts (SMAs) provider tracks the index.
Back in 2017, the Swiss Federal Office for the Environment (FOEN) and the State Secretariat for International Finance (SIF) made it possible for all Swiss pension funds and insurance firms to measure the environmental impact of their stocks and portfolios for free. Currently, these federal bodies are testing use case with banks and asset managers. Its initial activities will be recorded in an action plan, which is due to be published in Spring 2021.
How can having a body of sustainable firms help create ESG metrics?
Creating ESG standard metrics and methodologies will be aided when there is a network of sustainable companies to analyse, which leads us to green fintech networks (GFN) of companies interested in exploring how their own technology investments can be supportive of ESG objectives. Switzerland is setting up a Green Fintech Network to help the country take advantage of the “great opportunity” presented by sustainable finance. The network has been launched by SIF alongside industry players, including green FinTech companies, universities, and consulting and law firms. Stockholm also has a Green Fintech Network that allows collaboration towards sustainability goals.
We should be curious about how ESG can provide decision-oriented information about intangible assets and non-financial risks and opportunities. More information and data from ESG data providers like SAM, combined with automation or AI tools can potentially provide a more complete picture of how to measure the long-term sustainable performance of equity and fixed income asset classes.
Singapore FinTech Festival 2020: Investor Summit
For more insights, attend the Singapore FinTech Festival 2020: Investor Summit which will cover topics tied to 2021 Investor Priorities, and Fundraising and exit strategies
Artificial Intelligence (AI) is becoming embedded in financial services across consumer interactions and core business processes, including the use of chatbots and natural language processing (NLP) for KYC/AML risk assessment.
But what does AI mean for financial regulators? They are also consuming increasing amounts of data and are now using AI to gain new insights and inform policy decisions.
The efficiencies that AI offers can be harnessed in support of compliance within both financial regulation (RegTech) and financial supervision (SupTech). Authorities and regulated institutions have both turned to AI to help them manage the increased regulatory requirements that were put in place after the 2008 financial crisis. Ecosystm research finds that compliance is key to financial institutions (Figure 1).
SupTech is maturing with more robust safeguards and frameworks, enabling the necessary advancements in technology implementation for AI and Machine Learning (ML) to be used for regulatory supervision. The Bank of England and the UK Financial Conduct Authority surveyed the industry in March 2019 to understand how and where AI and ML are being used, and their results indicated 80% of survey respondents were using ML. The most common application of SupTech is ML techniques, and more specifically NLP to create more efficient and effective supervisory processes.
Let us focus on the use of NLP, specifically on how it has been used by banking authorities for policy decision making during the COVID-19 crisis. AI has the potential to read and comprehend significant details from text. NLP, which is an important subset of AI, can be seen to have supported operations to stay updated with the compliance and regulatory policy shifts during this challenging period.
Use of NLP in Policy Making During COVID-19
The Financial Stability Board (FSB) coordinates at the international level, the work of national financial authorities and international standard-setting bodies in order to develop and promote the implementation of effective regulatory, supervisory and other financial sector policies. A recent FSB report delivered to G20 Finance Ministers and Central Bank Governors for their virtual meeting in October 2020 highlighted a number of AI use cases in national institutions.
We illustrate several use cases from their October report to show how NLP has been deployed specifically for the COVID-19 situation. These cases demonstrate AI aiding supervisory team in banks and in automating information extraction from regulatory documents using NLP.
De Nederlandsche Bank (DNB)
The DNB is developing an interactive reporting dashboard to provide insight for supervisors on COVID-19 related risks. The dashboard that is in development, enables supervisors to have different data views as needed (e.g. over time, by bank). Planned SupTech improvements include incorporating public COVID-19 information and/or analysing comment fields with text analysis.
Monetary Authority of Singapore (MAS)
MAS deployed automation tools using NLP to gather international news and stay abreast of COVID-19 related developments. MAS also used NLP to analyse consumer feedback on COVID-19 issues, and monitor vulnerabilities in the different customer and product segments. MAS also collected weekly data from regulated institutions to track the take-up of credit relief measures as the pandemic unfolded. Data aggregation and transformation were automated and visualised for monitoring.
US Federal Reserve Bank Board of Governors
One of the Federal Reserve Banks in the US is currently working on a project to develop an NLP tool used to analyse public websites of supervised regulated institutions to identify information on “work with your customer” programs, in response to the COVID-19 crisis.
Bank of England
The Bank developed a Policy Response Tracker using web scraping (targeted at the English versions of each authority/government website) and NLP for the extraction of key words, topics and actions taken in each jurisdiction. The tracker pulls information daily from the official COVID-19 response pages then runs it through specific criteria (e.g. user-defined keywords, metrics and risks) to sift and present a summary of the information to supervisors.
Even with its enhanced efficiencies, NLP in SupTech is still an aid to decision making and cannot replace the need for human judgement. NLP in policy decision is performing clearly defined information gathering tasks with greater efficiency and speed. But NLP cannot change the quality of the data provided, so data selection and choice are still critical to effective policy making.
For authorities, the use of SupTech could improve oversight, surveillance, and analytical capabilities. These efficiency gains and possible improvement in quality arising from automation of previously manual processes could be consideration for adoption.
Attention will be paid in 2021 to focusing on automation of processes using AI (Figure 2).
Based on a survey done by the FSB of its members (Figure 3), the majority of their respondents had a SupTech innovation or data strategy in place, with the use of such strategies growing significantly since 2016.
For more mainstream adoption, data standards and use of effective governance frameworks will be important. As seen from the FSB survey, SupTech applications are now used in reporting, data management and virtual assistance. But institutions still send the transaction data history in different reporting formats which results in a slower process of data analysing and data gathering. AI, using NLP, can help with this by streamlining data collection and data analytics. While time and cost savings are obvious benefits, the ability to identify key information (the proverbial needle in the haystack) can be a significant efficiency advantage.
Singapore FinTech Festival 2020: Infrastructure Summit
For more insights, attend the Singapore FinTech Festival 2020: Infrastructure Summit which will cover topics tied to creating infrastructure for a digital economy; and RegTech and SupTech policies to drive innovation and efficiencies in a co-Covid-19 world.
Ecosystm had predicted that in 2020, AI and analytics would be a top priority for organisations as they embarked or continued on their Digital Transformation journeys. What we saw instead was organisations collecting the right data – but handling more pressing matters this year. They focused more on cybersecurity frameworks, enabling remote employees and the shifts in product and service delivery. In 2021, as organisations work their way to recovery, they will re-evaluate their AI and automation roadmaps, more actively. Ecosystm Advisors Alea Fairchild, Andrew Milroy and Tim Sheedy present the top 5 Ecosystm predictions for AI & Automation in 2021.
This is a summary of the AI & Automation predictions, the full report (including the implications) is available to download for free on the Ecosystm platform here.
The Top 5 AI & Automation Trends for 2021
- AI Will Move from a Competitive Advantage to a Must-Have
The best practices and leading-edge technology-centric implementations, over the years gives a very good indication of market trends. In 2018 and 2019 AI-centric engagements were few and far between – they were still in the “innovation stage” as trials and small projects. In 2020, AI was mentioned in most applications, showcased as best practices. AI is currently a competitive advantage for businesses. CIOs and their businesses are using AI to get ahead of their competitors and highlighting these practices for external recognition.
That also means that it is a matter of time before AI becomes a standard practice – processes are smart “out-of-the-box”; intelligent applications are an expectation, not the exception; systems learn because that is how they were designed, not as an overlay. If your competitors are using AI today to get ahead of you, then you need to also use AI to catch up and keep up. In 2021, having a smart business will not get you ahead of the pack – it will move you into it.
- AI Will Thrive in Areas where the Cost of Failure is Low
While organisations will be forced to adopt AI to remain competitive, initial exploration of AI solutions will be in areas that they consider low risk. The Financial Services, Retail, and other transaction-oriented industries will use AI to drive improved personalisation, increase customer retention, and improve their ability to lower risk and combat fraud. These are process-driven areas, where manual processes are being enhanced and enriched by AI. Although machine learning and other AI technologies will help improve the speed and quality of services, they will not be a replacement for many of the more complex business practices that companies and their employees frequently overlook to automate. The ‘low hanging fruit’ to add AI to will come first, with various degrees of success.
There will be industries and processes where organisations will be more skeptical about adopting AI. If Google finds a wrong translation or gives a wrong link, it is not a big concern, unlike a wrong diagnosis or wrong medication. In areas that are crucial to our well-being – such as healthcare – AI does not yet have the trust for acceptance of society. There are still questions around ethics and algorithm concerns.
- Technology Providers Will Stop Talking about AI
Technology vendors highlight what they consider their key differentiators, that show that they are ahead of the game. When every piece of software and hardware is intelligent, vendors will stop talking about the fact that they are intelligent. This may not fully happen in 2021 – but ENOUGH technology will be intelligent for those who have not yet made their software smart to understand that they cannot talk about its intelligent capabilities as that just shows they are behind the market.
The good news is that the less we hear about AI, the more intelligent applications will become. AI is quickly becoming a core capability and a base expectation. Systems that learn and adapt will be standard very soon – but be wary, as significant market changes can break these systems! Many companies learned that the pandemic broke their algorithms as times were no longer “normal”.
- Enterprises Will Seek Hyperautomation Solutions
RPA will increasingly become part of large enterprise application implementations. Technology vendors are adding RPA functionality either organically or through acquisitions to their enterprise application suites. RPA often works in conjunction with major software products provided by companies such as Salesforce, SAP, Microsoft, and IBM. Rather than having an operative enter data into multiple systems, a bot can be created to do this. Large software vendors are taking advantage of this opportunity by trying to own entire workflows. They are increasingly integrating RPA into their offerings as well as competing directly in the RPA market with pureplay RPA vendors.
As the RPA offerings continue to mature, enterprises seek to scale implementations and to automate non-repetitive processes, which require more intelligence. They will seek to automate more processes at scale. They will demand solutions that process unstructured data, handle exceptions, and continuously learn, further increasing productivity. Intelligent automation typically incorporates AI, particularly voice and vision capabilities and uses machine learning to optimise processes. Hyperautomation turbo charges intelligent automation by automating multiple processes at scale – and will become core to digital transformation initiatives in 2021.
- Businesses Will Put “Automation Targets” in Place
2020 was the year that many businesses started seeing some broad and tangible benefits from their automation initiatives. Automation was one of the big winners of the year, as many businesses took extra steps to take humans out of processes – particularly those humans that had to be in a specific location, such as a warehouse, the finance team, the front desk and so on (because of the pandemic, they were often working at home instead). Senior management is seeing the benefits of automation, and they will start to ask their teams why more processes are not automated Therefore we will start to see managers put targets around a certain percentage of tasks automated in an area – e.g. 70% of contact centre processes will be automated, 90% of the digital customer experience for a certain outcome will be automated and so on. Achieving these numbers may not be easy, but the targets will change the mindset of people designing, implementing, and improving processes.
Download Ecosystm Predicts: The Top 5 AI & Automation Trends for 2021
The full findings and implications of The Top 5 AI & Automation Trends for 2021 are available for download from the Ecosystm platform. Signup for Free to download the report.
The Retail industry has had to do a sharp re-think of its digital roadmap and transformation journey – Ecosystm research shows that about 75% of retail organisations had to start, accelerate, or re-focus their digital transformation initiatives. However, that will not be enough as organisations move beyond survival to recovery – and future successes. While retailers will focus on the shift in customer expectations, a mere focus on customer experience will not be enough in 2021. Ecosystm Principal Advisors, Alan Hesketh and Alea Fairchild present the top 5 Ecosystm predictions for Retail & eCommerce in 2021.
This is a summary of the predictions, the full report (including the implications) is available to download for free on the Ecosystm platform here.
The Top 5 Retail & eCommerce Trends for 2021
- There Will Only be Omnichannel Retailers
The value of an omnichannel offer in Retail has become much clearer during the COVID-19 pandemic. Retailers that do not have the ability to deliver using the channel customers prefer will find it hard to compete. As the physical channel becomes less important new revenue opportunities will open up for businesses operating in adjacent market sectors – companies such as food and grocery wholesalers will increasingly sell direct to consumers, leveraging their existing online and distribution capabilities.
Most customers transact on mobile device – either a mobile phone or tablet. New capabilities will remove some of the barriers to using these mobile devices. For one, technologies such as Progressive Web Apps (PWA) and Accelerated Mobile Pages (AMP) will provide a better customer experience on mobile platforms than existing websites, while delivering a user experience at par or better than mobile apps. Also, as retailers become AI-enabled, machine learning engines will provide purchase recommendations through smartwatches or in-home, voice-enabled, smart devices.
- COVID-19 Will Continue to be an Influence Forcing Radical Shifts
In driving the economic recovery in 2021, we will see ‘glocal’ consumption – emphasis on local retailers and global players taking local actions to win the hearts and minds of local consumers. There will be significant actions within local communities to drive consumers to support local retailers. Location-based services (LBS) will be used extensively as consumers on the high street carry more LBS-enabled devices than ever before. Bluetooth beacon technology and proximity marketing will drive these efforts. Consumers will have to opt-in for this to work, so privacy and relationship management are also important to consider.
But people still want to “physically” browse, and design aesthetics of a store are still part of the attraction. In the next 18 months, the concept of virtual stores that are digital twins will take off, particularly in the holiday and Spring clearance sales. Innovators like Matterport can help local retailers gain a more global audience with a digital twin with a limited technological investment. At a minimum, Shopify or other intermediaries will be necessary for a digital shop window.
- The Industry will See Artificial Intelligence in Everything
AI will increase its impact on Retail with an uptake in two key areas.
- Customer interactions. Retail AI will use customer data to deliver much richer and targeted experiences. This may include the ability to get to a ‘segment of one’. Tools will include chatbots that are more functional and support for voice-based commerce using mobile and in-home edge devices. Also, in-store recognition of customers will become easier through enhanced device or facial recognition. Markets where privacy is less respected will lead in this area – other markets will also innovate to achieve the same outcomes without compromising privacy but will lag in their delivery. This mismatch of capability may allow early adopters to enter other geographic markets with competitive offers while meeting the privacy requirements of these markets.
- Supply chain and pricing capabilities. AI-based machine learning engines using both internal and increased sources of external data will replace traditional math-based forecasting and replenishment models. These engines will enable the identification of unexpected and unusual demand influencing factors, particularly from new sources of external data. Modelling of price elasticity using machine learning will be able to handle more complex models. Retailers using this capability will be in a better position to optimise their customer offers based on their pricing strategies. Supply chains will be re-engineered so products with high demand volatility are manufactured close to markets, and the procurement of products with stable demands will be cost-based.
- Distribution Woes Will Continue
Third party delivery platforms such as Wish and RoseGal are recruiting additional international non-Asian suppliers to expand their portfolios. Amazon and AliExpress are leaders here, but there are many niche eCommerce platforms taking up the slack due to the uneven distribution patterns from the ongoing economic situation. Expect to see a number of new entrants taking up niche spaces in the second half of 2021, sponsored by major retail product brands, to give Amazon a run for their money on a more local basis.
As the USPS continues to be under strain, delivery companies like FedEx in the US who partner with the USPS are already suffering from the USPS’s operational slowdown, in both their customer reputation and delivery speed. In 2021, COVID-19 – and workers’ unions – will continue to impact distribution activities. Increased spending in warehouse automation and new retail footprints such as dark stores will be seen to make up for worker shortfalls.
- China’s Retail Models Will Expand into Other Markets
China’s online businesses operate in a large domestic market that is comparatively free of international competitors. Given the scale of the domestic market, these online companies have been able to grow to become substantial businesses using advanced technologies. All the Chinese tech giants – among them Alibaba, ByteDance, DiDi Chuxing, and Tencent – are expanding internationally.
China’s rapidly recovering economy puts those businesses in a strong position to fund a competitive expansion into international markets using their domestic base, particularly with their Government’s promotion of the country’s tech sector. It is harder to impose restrictions on software-based businesses, unlike the approach that we have witnessed the US Government take for hardware companies such as Huawei – placing constraints on mobile phone components and operating systems.
These tech giants also have significant experience in a Big Data environment that provides little privacy protection, as well as leading-edge AI capabilities. While they will not be able to operate with the same freedom in global markets, and there will be other large challenges in translating Chinese experience to other markets – these tech players will be able to compete very effectively with incumbent global companies. Chinese companies also continue to raise capital from US stock exchanges with The Economist reporting Chinese listings have raised close to USD 17 billion since January 2020.
Download Ecosystm Predicts: The Top 5 Retail & eCommerce Trends for 2021
The full findings and implications of The Top 5 Retail & eCommerce Trends for 2021 are available for download from the Ecosystm platform. Signup for Free to download the report.