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DON’T LET SPREADSHEETS PUT YOUR FORECASTING AND PLANNING AT RISK

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James Kipling, Product Manger at Quantrix

Good planning and forecasting is not something that can be achieved overnight. The organizations which consistently succeed constantly iterate to improve their processes; they take the things that work and ditch the things which don’t work, offer limited value or are simply holding them back.

James Kipling, Product Manger at Quantrix

James Kipling, Product Manger at Quantrix

There are many best practices that every organization should follow, the most important of which I expand on later in this article.But first, we need to look at a systematic issue likely to be present in every organization in some form – including your own.

I am talking about spreadsheet risk.

Think outside the cell

Spreadsheets are used in almost all areas of business, in nearly every industry and every sector. The inherent flexibility of the two-dimensional table we have grown familiar with has ensured that whether you work in the front-office, advising clients or selling investment products, in the middle office analysing risk and compliance, or in the back office managing the plethora of services and products that today’s businesses utilize, you’re almost certainly going to be using a spreadsheet of some kind, often on a daily basis.

With the use of spreadsheets so widespread, risk officers should be fully aware of the damage an erroneous table, figure or calculation could cause to a business. But are they taking these concerns seriously enough?

Often small errors are shrugged off with little thought, and the framework which enable errors to propagate are frequently ignored, but we have seen – and will continue to see –how such errors can be catastrophic for businesses.

Perhaps the scariest thing about spreadsheet risk, is that you may not even know that your forecasts are based on bad assumptions. The error may not be in your spreadsheet, or the spreadsheet you got your assumptions from – but in the ad-hoc market forecast done by an anonymous intern, three years ago.Of course, no one bothered to audit and check the calculations. Why would they?No one ever saw the output of that model becoming one of the cornerstones of strategic decision making at the highest level – and yet it can, and does, happen.

Thankfully, there are some measures your organization can take to ensure you are doing all you can to provide accurate forecasts and plans.

Right question

First and foremost, you must ask the right questions. Instead of getting distracted by fancy calculations or complex methodology, which can lead to a cumbersome unwieldy model – try to stick to answering the questions which are most important for you and your organization.

Too often organizations get hung up on revenues, profits and dollars – are these really the core drivers of your business? Perhaps, perhaps not… Be sure to explore often forgotten metrics such as units, customers and conversions. It can be easy to get carried away once you start to build out a new plan, but ensuring you always ask yourself “do I need to answer this question” will go a long way to improving your capabilities.

Right data

With the questions decided, it’s time to start thinking about where you’re going to get your data from. With the rise of the ‘big data era’, the first thing in most people’s minds is “more data is good data”. This is simply not true. Sometimes you don’t need to use all the data as this can over complicate the model and increase the likelihood of errors being introduced.

Always make sure you make a direct connection to the underlying data (often called the ‘single source of truth’). The outdated method of copying and pasting data from source to input is a recipe for disaster as if the source data changes, not only are you now working from old data, but anyone who relies on the output of your forecast is also out-of-sync with the current situation. Investing early to create the single source of truth and then providing the right tools to use that data effectively, pays for itself multiple times over as your capabilities and ambitions grow.

Right structure

You’ve got the data and you know the questions you need to answer but how can you appropriately structure your model to be flexible and scalable yet robust? We live in a multidimensional world, with many organizations operating across multiple regions, selling a variety of products. Combining this with the need for your plan to allow for multiple scenarios through dynamic ‘what-if’ – this makes the model structure extremely important.

Businesses aren’t static, they’re evolving entities, constantly changing the products they offer and the ways in which they sell these products. Your model needs to be flexible enough to adapt to these changes as they happen, with minimal effort (ideally automatically)! Failure to address this early on often results in a huge amount of re-work to re-engineer the spreadsheet – giving even more chance for errors to creep in.

Right logic

Arguably one of the most important aspects to good planning and forecasting is allowing others in your organization to draw insights. For this reason, it is important to make sure the logic your model uses is both understandable and well documented.

Just as the intern had never anticipated the model they built during their summer placement would have ended up in the boardroom three years later, explaining the intention of your calculations in plain English goes a long way to ensuring that your model is future-proofed. We’ve all opened spreadsheets years later, where without context, the information on screen may as well be Hieroglyphics!

Right tools

Professionals are moving away from off-the-shelf tools. The tool of choice for graphic designers is unlikely to be Paint. Likewise, it is improbable that the professional software engineer uses notepad for their day-to-day coding.

It may sound simple, but whether its visualization tools such as Tableau, or a full enterprise level business modeling platform such as Quantrix, using the right tools for the right job will ensure that efficiency killers such as formula writing, error checking and auditing are all alleviated through the use of professional features such as natural language formula writing, built-in audit trail and a visual dependency inspector. Multi-dimensional modeling tools are on the forefront of financial planning and forecasting – the inherent nature of today’s global businesses means the questions asked of analysts often exist in a multi-dimensional problem space. Don’t let habit be the reason you put your forecasts at risk.

By James Kipling, Product Manager at Quantrix
James joined Quantrix in 2015 as Product Manager and initially worked with the team on the successful Quantrix version 6 project. He now leads the development effort for the Quantrix Modeler product working on the product roadmap and strategy, as well as coordinating marketing and sales activities.

Technology

AI: Do the Right Thing

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AI: Do the Right Thing 1

By Alix Melchy, Jumio VP of AI

The application of emerging technologies such as AI, cloud, blockchain and IoT in financial services has altered the traditional operating models of financial institutions, the competitive dynamics of the industry, the role of people in those institutions and the landscape of the financial system as a whole. In fact, AI is positioned as an essential investment, with the World Economic Forum arguing how it is set to become central to the fabric of financial institutions.

While the adoption of AI in financial services may be in its infancy, the use cases are ever growing. From recommending loan and credit offerings to detecting fraud, 94% of financial services in European and Middle Eastern markets believe that AI will disrupt their business. The direction and the awareness of AI is clear but it is essential that companies invest now, as if done too hastily, the process is marred by pitfalls.

Despite the transformative promise of AI and machine learning algorithms, we have seen its application come under scrutiny in other industries. Take the UK A-Level exam grading debacle that dominated headlines back in August. Exam grades of students living in certain UK postcodes were disproportionately and negatively impacted, while other students saw their results inflated. This was down to an algorithm implemented by Ofqual that was set to predict grades using historical data including grades obtained at exams in previous years.

The incident raises the question as to what would happen if the algorithm used in this instance was applied to a financial decision. The same biases could negatively impact the way millions of consumers and businesses borrow, save and manage their money.

It is therefore imperative that financial institutions learn from this scenario, ensuring that when implemented in financial decision-making, AI is nothing short of a success.

AI is no fairy godmother

While many tout the game-changing effects of the looming AI revolution, it’s fundamentally important to understand that AI is not magic. Instead, we need to learn to set reasonable expectations with AI so not to paint an unrealistic picture of its power.

In order to start out on the right track, businesses must first define and align on the task they want the algorithm to perform before it can be developed and implemented. Articulating the problem to be solved is the prerequisite for a solid framework of development and evaluation of your algorithms.

Removing bias in AI

AI is the tool, not the hand that wields it or the eye that guides it. It is a type of learning system that requires data, training integration, and course correction. Just as we would train a young engineer to use a tool correctly, we are training AI systems to become expert learning systems through the data, process and people.

Therefore, in order to solve a problem using AI, the task must be expressed in a form which a machine can understand and the machine must be supplied with the necessary data to perform or otherwise learn to generate predictions that enable it to accomplish its objective. Without strong and relevant data underpinning an AI model, it will never be able to produce strong and relevant results.

To design a fair algorithm, the key is to collect a sufficient amount of data so that the algorithm can be trained to represent an entire community. While it is possible to buy datasets to speed up the process, when doing so, it is essential that the data meets your required criteria rather than simply being a large data set. For the financial services sector, this enables employees to treat customers fairly and, when combined with appropriate modelling and processes, allows them to maintain transparency and accountability in their decision-making processes to avoid legal claims or fines from regulators which can cause deep reputational damage.

Building back better

As the Ofqual issue revealed, a preliminary, small-scale algorithm test is an essential step before applying it into a real-world scenario. A pilot testing phase will help a business to amend the design to identify unnecessary costs and time expenditures, while also better understanding the data. As this was not sufficiently done in the Ofqual case, the algorithm simply did not provide the right answer to the problem it was trying to solve.

Championing ethical AI

More than ever, companies are realising one simple truth: failing to operationalise data and AI ethics is a threat to the bottom line. Missing the mark can expose companies to reputational, regulatory and legal risks. Here are some key areas that businesses should consider when leveraging AI models:

  • Usage consent: make sure that all the data you are using has been acquired with the proper consent
  • Diversity and representativity: AI practitioners should consider how diverse their programming teams are and whether or not they undertake relevant anti-bias and discrimination training. This will draw upon perspectives of individuals from different genders, backgrounds and faiths which will increase the likelihood that decisions made on purchasing and operating AI solutions are inclusive and not biased
  • Transparency and trust building: accurate and robust record keeping is important to assure that those impacted by it know how the model works

The ways AI can be utilised in the financial services industry is increasingly growing. An example is the use of document-centric identity proofing space whereby an identification document, such as a passport, is matched with a selfie of the user to confirm real and virtual identities. This will be an essential area of focus for financial services companies as they look to confirm that users are who they claim to be when the physical branch is diminishing. When analysing if a person is the same as the picture on their documentation, for example, a biased AI model can completely undermine the decision made.

However, it’s reassuring to see that the 2020 Gartner Market Guide for Identity Proofing & Affirmation predicts that by 2022, 95% of RFPs will have introduced clear requirements around minimising demographic bias. This demonstrates how organisations are now becoming more aware of the detrimental impacts that demographic bias in the performance of identity-proofing processes could have on their brand as well as being clear on the legal consequences they risk facing.

In turn, there is a real opportunity to leverage AI solutions to provide the best service, but financial institutions must ensure that they are doing so in an ethical, accurate, and representative way.

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SFF x SWITCH 2020 to Feature 40 Global Satellite Events and 24-Hour Online Experience

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SFF x SWITCH 2020 to Feature 40 Global Satellite Events and 24-Hour Online Experience 2

SFF x SWITCH 2020 to Feature 40 Global Satellite Events and 24-Hour Online Experience 3

 

SFF x SWITCH 2020 to Feature 40 Global Satellite Events and 24-Hour Online Experience 4

 

The Monetary Authority of Singapore (MAS) and Enterprise Singapore (ESG) announced today that more than 40 global satellite events will take place across the world as part of the Singap ore FinTech Festival (SFF) x Singapore Week of Innovation & TeCHnology (SWITCH) 2020.

  1. To be held from 7 to 11 December, SFF x SWITCH 2020 will feature a unique hybrid format that combines a 24-hour online event platform with global satellite events around the world. This new hybrid model will provide participants with greater access to the global FinTech and deep tech communities who are looking to discover partnerships, draw investments, and boost sales cycles.
  2. SFF x SWITCH has worked with a network of global partners to host the global satellite events (refer to Annex A). They comprise physical events in selected cities in accordance with local safe distancing measures as well as digital-only events. They will bring together content from innovation hubs and tech showcases around the world, and provide in-person attendees access to networking opportunities with industry leaders and sponsors. In collaboration with MAS and ESG, SingEx Group will manage the physical and digital experiences for attendees and ensure a seamless execution of the FinTech and innovation showcases across the cities.
  3. SFF x SWITCH will feature a 24-hour online experience over five days. This online event platform will feature a digital city, supported by partners including Accenture, Microsoft and Pico Art International. The digital city will feature more than 800 speakers from around the world, including leaders in finance and technology, entrepreneurs, policymakers, and officials from multilateral agencies. Participants can access live content broadcasts running round-the-clock and on-demand sessions. Some of the confirmed speakers include:

SFF

  • Dr Abhijit Banerjee, 2019 Nobel Prize in Economics, Ford Foundation International Professor of Economics, Massachusetts Institute of Technology (MIT)
  • Kristalina Georgieva, Managing Director, International Monetary Fund
  • Guo Shuqing, Chairman, China Banking and Insurance Regulatory Commission
  • Hong Feng, Co-Founder and Senior Vice President, Xiaomi
  • Arianna Huffington, Founder and CEO, Thrive Global, Founder, Huffington Post
  • Sallie Krawcheck, Chief Executive Officer & Founder, Ellevest
  • Satya Nadella, Chief Executive Officer, Microsoft
  • Nandan Nilekani, Co-Founder and Chairman, Infosys
  • Henry M. Paulson, Jr, Founder and Chairman, Paulson Institute
  • Sundar Pichai, Chief Executive Officer, Google and Alphabet
  • Dr Raghuram Rajan, Katherine Dusak Miller Distinguished Service Professor of Finance, University of Chicago’s Booth School
  • Eric Yuan, Chief Executive Officer and Founder, Zoom

SWITCH

  • Albert, Co-Founder, Traveloka
  • Dr Chi Youngcho, President and CIO, Hyundai Motor Group
  • Timothy Draper, Founding Partner, Draper Associates
  • Arvinder Gujral, Managing Director SE Asia and Senior Director Business Development – APAC, China, Australia, Twitter
  • Shobana Kamineni, Executive Vice Chairperson, Apollo Hospitals Enterprise
  • Lei Ming, Co-Founder, Baidu; Former CEO and Founder, Kuwo Science and Technology; Founding Partner, AIBasis Ventures
  • Henry Ma, Executive Vice President and Chief Information Officer, WeBank
  • Candice Ong, Chief Commercial Officer, ShopBack
  • Lars Reger, Group Chief Technology Officer, NXP Semiconductor Germany GmbH
  • Professor Sir Adrian Smith FRS, Institute Director and Chief Executive, The Alan Turing Institute
  • Professor H.S. Philip Wong, Willard R. and Inez Kerr Bell Professor in the School of Engineering, Stanford University
  • Ye Gang, Group Chief Operating Officer, Sea Ltd
  1. The SFF Global-Common Channel will feature five global summits on the themes of: economics, infrastructure, impact, investor, and talent. They will focus on driving cross-border commercial activity to support pandemic recovery, and how financial institutions should position themselves in 2021. The SWITCH Global Channel, curated by SWITCH’s global innovation partners (refer to Annex B), allows participants access to market knowledge, opportunities, insights and tips on business culture from over 42 cities in 31 countries across Africa, Asia (China, India and Southeast Asia), Europe, Middle East, North America and Northeast Asia & Oceania.
  2. A digital map will show all SFF x SWITCH activities across Singapore, with dedicated zones[1] for various activities, including an international zone, early stage and growth stage FinTech zones, talent zone, technology showcase zones, and a networking zone. Participants will be able to visit locations on the map via a searchable and interactive directory of organisations and activities, tailored to their interests and profiles. Participants can meet and network with attendees on the event platform and schedule 1-on-1 meetings, by leveraging on the platform’s business matching functionality.
  3. Sopnendu Mohanty, Chief FinTech Officer, MAS, said, “The global pandemic has led to a reimagination of how we can deliver SFF x SWITCH as a global platform. To recreate the connectivity, collaboration and networking that have become the hallmarks of SFF x SWITCH, this year’s unique hybrid format will break new ground to create a truly global and inclusive event for the FinTech community. We are delighted to work with key global partners to deliver over 40 global satellite events for attendees across the globe, and Microsoft and Accenture to design this first-of-its-kind global platform for the FinTech community to innovate and forge new connections, anchored on the delivery of a powerful, new digital experience at scale.”
  4. Edwin Chow, Assistant Chief Executive Officer (Innovation & Enterprise), Enterprise Singapore, said, “While SFF x SWITCH is being run in a new, unprecedented way, our aim to enable networking and collaboration has not changed. In fact, we are very pleased to see that SWITCH has attracted even more global innovation partners this time, with established names such as 500 Startups, Sunway Group and VinaCapital joining us at various thematic panel discussions. This digital format not only enables the deep tech and innovation community to access deep market knowledge; it allows us to connect across geographies and time zones at a much faster pace, making this event a truly global one.”
  5. “Together with our partners we’ve designed the entire customer journey identifying critical touchpoints for optimal experiential engagements, paving the way for a bold new format that’s driven by customer insights. We’re proud to be the nerve centre for SFF x SWITCH orchestrating the global event experience across the satellite cities, online and offline, through our hybrid events studio in Singapore as well as robust capabilities in content, digital and operational excellence. We look forward to showing the world a new standard of audience engagement made possible with our established network of community partners from around the world”, said Aloysius Arlando, Chief Executive Officer, SingEx.

[1] The digital map will feature dedicated areas for various SFF x SWITCH activities, comprising the SFF x SWITCH Content Channels, International Zone, MAS Zone, Sponsor and Exhibitor Zones, Early Stage FinTechs Zone, Growth Stage FinTechs Zone, APIX, Talent Pavilion, Blockchain Zone, SME Zone, SFF AI Summit @Bridge+, Networking Zone, SWITCH Village and SG Blockchain Village.

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Leumi UK completes core banking upgrade with Finastra

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Leumi UK completes core banking upgrade with Finastra 5

Multi-specialist bank Leumi UK improves customer experience and streamlines processes with updated technology

Leumi UK, the London subsidiary of Israel’s largest banking group, has selected Finastra, one of the world’s largest fintechs, to upgrade its core banking systems.

For Leumi UK, this is the culmination of an extensive bank-wide programme to boost the efficiency of internal processes. The upgrade provides a solid foundation on which to make further improvements to the speed and functionality of Leumi UK’s processes.

The enhanced core banking system is a fundamental component of Leumi UK’s new IT strategy, as defined by Chief Technology Officer, Alon Shmuel. This will enable the bank to focus on business growth, as it builds momentum in its specialist areas of hotel and property finance. With this latest technology in place, it is now better equipped to onboard new business and ultimately improve the overall customer experience.

Alon Shmuel, Chief Technology Officer at Leumi UK, says: “This upgrade is part of the promise to our customers to constantly build upon the services and solutions we offer. Thanks to Finastra, we can ensure that we are using the latest software and most up-to-date technology to provide an even better, faster service to our customers. We are very grateful to Finastra for the expertise, dedication and professionalism they exhibited as we undertook this ambitious endeavour together. Their support allowed us to complete the project in under nine months, despite the challenges we faced from the Coronavirus pandemic.”

John Mitchell, Vice President Global Services Europe at Finastra said, “Finastra has worked hard to deliver a robust services strategy that enables us to support customers, like Leumi UK, and help them to achieve their goals, whether for a new implementation or a core upgrade. This is particularly crucial with current restrictions preventing us from being on the ground with our customers. We are delighted to support Leumi UK during its transformation and pleased that we were able to complete the project together ahead of schedule. Our collaborative working relationship was a significant mitigation to the challenges faced with the onset of the pandemic.”

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