Innovation is a choice

There’s nothing like a week in another city to get the innovation juices flowing, and London Fintech Week was exactly that (thank you Luis and team for another week of great debate, networking and insights).

Source: Pexels.com/photo-512249/

There’s nothing like a week in another city to get the innovation juices flowing, and London Fintech Week was exactly that (thank you Luis and team for another week of great debate, networking and insights).

So, what is new in the world of Fintech? Well, if the speakers and panelists are to believed, and the messages were far too similar and consistent for them not to be…

…AI is playing an increasingly important role in the world and indeed in the world of banks – …  . It is clear that to win in the investment banking game will still require smart people – but we must couple smart banker types with AIs and we must change our definition of “banker types” to include engineers and mathematical PHDs.

…Blockchain is here, and it’s all grown up. No longer a concept for alternative funding and the underworld, the cryptocurrency conversation is upping the volume at the highest levels with countries like Canada, the UK and Singapore all running projects, and banks of all sizes experimenting and building applications both in crypto-coins and blockchain technologies. Even the highly volatile crypto-currency prices over the week did nothing to dampen the enthusiasm. With the rise of open source, I expect we will see increasing opportunities to move from our existing centralized models to new blockchain enabled ones in many economies and industries.

…Trust is no longer about relationships, nor the strength of your brand. It’s about ease of use and, increasingly, peer review. Customers are no longer seeking a similar experience to the one they get from other banking brands, they’re looking for an experience like they get from the mega brands like Apple and Amazon. Banks are going to need to up their game – and quickly!

Clients know that if they are not paying, they are the product. Both banks and clients know the power of their data – what will this mean in the future? How will this change their expectations of service? Security now becomes as important as service; will clients demand due diligence of their service providers to ensure that their data is secure?

…Innovation is a choice – it doesn’t just happen. This is potentially the most important message of all. Entities that are leading in the start-up and innovation space are choosing to  – they are seeing the possibilities that innovators bring and are finding creative ways to enable them. The innovation choice is being made at the highest level – countries like India, Canada, the UK, Germany, the Netherlands, and China are all facilitating innovation communities and the start-ups and banks coming out of those countries are moving faster than others because of it. It is a choice because there are millions of reasons and costs involved with creating change, but forward-thinking leaders recognize the importance and their choice to enable, means they are leaping ahead.

…It’s organizational cultures that will make the space for innovation and those cultures look to leaders for the messages they need. Coincidentally, I just finished reading “Under the Hood” by Stan Slap where he describes how to maximise business performance. Culture understands leadership motivators beyond words and culture works exceptionally hard to protect its own existence – so innovation will simply not happen without leaders giving the right messages. Innovation is a choice leaders have to make and their actions will send the clear message.

Everything we know, the way we work and the way we behave was all once created as a leadership or cultural choice. In this exponential era, we will need to change the stories we tell, the way in which we work, the technologies we believe in. It’s ridiculously exciting – and it’s moving…well, exponentially! At last years’ event, there was talk of what blockchain is and what AI could conceivably do, this year it was all about what businesses are being built on these technologies. I can’t wait to see what the next year brings!

by Liesl Bebb-McKay

 

Finding your True North

In RMB’s world, and indeed in corporate and investment banking in South Africa, the Foundery is an unusual paradigm. On the one hand, the Foundery is a fintech, aiming to disrupt the financial services industry with innovative and novel products and services, but on the other hand, the Foundery is very much rooted as the digital innovation unit of RMB — one of the very incumbents which stand to be disrupted by the fintechs.

In RMB’s world, and indeed in corporate and investment banking in South Africa, the Foundery is an unusual paradigm. On the one hand, the Foundery is a fintech, aiming to disrupt the financial services industry with innovative and novel products and services, but on the other hand, the Foundery is very much rooted as the digital innovation unit of RMB — one of the very incumbents which stand to be disrupted by the fintechs.

There are many things that are unique about the Foundery, not least of which is its position at the intersection between fintech startup and banking incumbent, but most pertinently is its mission to completely change and reimagine the corporate and investment bank of the future.

This is a monumental goal and certainly not something that can be achieved without great effort. It may be worth asking, why not go for something smaller or easier? Why not chase the untapped profits or go after the opportune inefficiencies in traditional banking

The Foundery’s mission is what we call its True North. This is what gives the Foundery its identity and guides its actions. Without it, the Foundery would be another player in the fintech space, but with our True North, the Foundery is a fintech with purpose.

https://www.jobmastermagnets.com/fun-facts-about-magnets

Earth’s geographic North Pole

WHAT IS TRUE NORTH?

In astronomy, True North is the direction along the earth’s surface which points towards the geographic North Pole of the earth. This seems reasonable as geographic north is the northernmost point of the earth, so why call it True North when it is already north? Why the extra qualification?

The reason is that compasses and maps point to a slightly different north pole, what we call magnetic north and grid north respectively. These differences arise out of the slightly irregular shape and magnetic distribution of planet Earth.

http://gisgeography.com/magnetic-north-vs-geographic-true-pole/

The difference between the true north and the magnetic north

True North is important in astronomy because it serves as a reference by which we can measure the position of every object in the universe relative to its point of observation on Earth. This takes us back to the analogy of the Foundery’s True North and what we mean by the concept of True North:

Your True North can be thought of as your fundamental purpose that guides everything you do.

Just like the Earth’s True North is used by astronomers to map the night sky, your True North is what informs your goals and your decisions. It is the guiding principles by which you can make your biggest and most impactful choices.

IDENTIFYING YOUR TRUE NORTH

The concept of your own True North is something which is quite abstract and extremely daunting. What does it mean to have a fundamental purpose? Where does it come from? What am I meant to do with it? How do I know if I even have one? These questions are all relevant and aren’t easy to answer. In fact, there are no obvious or immediate answers — it’s up to you to decide what they are.

The good news is that we can learn from the geographic North Pole and extend the analogy. In practice, while we can’t rely on compasses or maps to navigate to the Earth’s True North, astronomers have been using the North Star, also known as Polaris, to mark the location of true north since the time of the Ancient Greeks. The North Star lies almost exactly “above” the geographic North Pole. Furthermore, the North Star is visible throughout the year (as long as you’re in the northern hemisphere*) and is therefore a reliable, although ancient, method of navigating to true north.

http://earthsky.org/astronomy-essentials/north-star-movement

The North Star: a time lapse image shows how the North Star rotates tightly around the celestial North Pole (in line with True North), while other stars rotate with a much wider radius.

Extending this analogy to your own True North, the challenge then becomes to find your North Star. What is that thing, whether it is abstract or tangible, that points to your True North? This could be a person, it could be your family, it could be your talents, it could be your hobbies or whatever it is that affirms that you doing what you love and that gives you a sense of purpose.

In the Foundery’s case, True North is our mission to change the world of banking, and the North Star is the people who have stepped up to the challenge to make this mission possible. Without the North Star, the Foundery would never be able to find its True North. Now the challenge is up to you — go out there and find your own North Star and, ultimately, your True North.

* Unfortunately there is no equivalent star in the southern hemisphere

by Jonathan Sinai

A Blockchain Problem

Blockchain has been hailed as the next ‘big thing’, a term thrown around in social gatherings with the likes of ‘big data’, ‘cloud computing’ and ‘Internet of Things’. A crucial understanding of the true value of blockchain is sorely lacking in many minds, leading to wasted resources by some of the world’s top banks and tech firms.

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Blockchain has been hailed as the next ‘big thing’, a term thrown around in social gatherings with the likes of ‘big data’, ‘cloud computing’ and ‘Internet of Things’. A crucial understanding of the true value of blockchain is sorely lacking in many minds, leading to wasted resources by some of the world’s top banks and tech firms.

Having been dubbed another ‘solution without a problem’ by some of its critics, the hype surrounding blockchain appears to oscillate between inflated expectations, and the trough of disillusionment, never quite hitting the slope of enlightenment, and thus never approaching anything quite like a product.

So what good is it really?

If you’re not familiar with the Byzantine Generals problem, here’s a quick overview:

Nine Byzantine Generals are entrenched around a city. They are divided upon their current course of action: do they attack, or do they retreat? Failing to reach consensus, they decide to cast votes, each general sending a messenger to relay their choice to the other generals, where the majority decision will be the action to take.

Four of the generals vote to attack and four vote to retreat. The group is split in two: those in favour of retreating, who begin to strike down their tents, and those in favour of attacking, who gather on the frontlines. What of the last general? Well, he’s been bribed by the city’s leaders*. Rather than vote one way or the other, he dispatches two messengers; the first states that he will attack, the second states that he will retreat.

Four of the generals thus lead their troops into battle and suffer a stunning defeat. The other four generals retreat, dishonoured, with a significantly weakened army.

This story is an allegory of a concept we have come to know as double-spending. In traditional markets, every merchant keeps their own ledger of all transactions. This is also true in the world of digital payments. Some clever customers have been known to make multiple transactions to different vendors, essentially issuing IOUs without the actual means to make good on every transaction. Come time for settlement, vendors have delivered their items, banks are short and the clever customer has high-tailed it through a proxy**.

This is the main problem Blockchain is intended solve: a distributed ledger network in which all vendors and customers share the same record of transactions and balances. Incentivised ‘miners’ add new transactions to the pool, where only one block of transactions is accepted at a time, based on mutual consensus by other parties, effectively solving the double-spend issue.

Too bad the Byzantines didn’t have blockchain.

Perhaps we need to go back to basics and focus on utilizing blockchain for its original intended purpose. All the pieces are set for us to begin digitizing financial instruments, ushering in a new era of trusted peer-to-peer transacting. The only question remains; what happened to the early adopters?

by Stuart Allen

Do corporates need garages?

Innovation is easy right? You throw a few super smart, socially awkward people into a garage and wait until they emerge with some new technology that will change the world. And, of course, that’ll take their earthly belongings from a stash of Led Zeppelin vinyls, a collection of well-worn t-shirts, and no doubt one or two student loans (for degrees they never actually finished) to billions of dollars.

Would you like a garage with that?

Innovation is easy right? You throw a few super smart, socially awkward people into a garage and wait until they emerge with some new technology that will change the world. And, of course, that’ll take their earthly belongings from a stash of Led Zeppelin vinyls, a collection of well-worn t-shirts, and no doubt one or two student loans (for degrees they never actually finished) to billions of dollars. This worked for Apple, Amazon, Google, HP and Microsoft, so surely it’ll work for everyone right?

Proximity to Business

But what if you’re not a new kid on the block, but rather, are one of the incumbents of the industry? How feasible is it to confine a portion of your company to a dingy garage, and keep them running on a diet of stale pizza and a steady stream of lofty ideals? There is a school of thought that advocates a very similar approach to this, albeit more grown-up. Whereby a portion of the company is carved out, or formed, and given autonomy to experiment, invent and innovate to their heart’s content- unencumbered by the drudgery of meetings about meetings, and without any expectation of immediate results or potentially any results at all. The hope being that, in time, the gamble will pay-off sling-shotting the company to the forefront of a bold new wave within the industry.

At the other end of the potential scale, and it should be viewed as a scale (see below), is an internal entity that is clearly part of the organization, and targets the short time-to-value, incremental, mildly-disruptive types of innovation. This is sometimes appropriate, especially for innovation that focuses on links within an existing value chain. To use a simplistic example, from the automotive industry, it is exceptionally hard to invent a new type of indicator stalk without having a steering wheel, or steering wheel column, to attach any prototypes to, nor any actual indicator lights and electrical system to test whether it even works. And as your value chain gets more complex, it gets exponentially more difficult.

So perhaps the most critical element in choosing an approach should be dictated by what you’re wanting to innovate. Too often people are given the broad directive to innovate, without any specific focus, and with no appreciation of the independence of the portion they need to innovate. Big corporates got big because of a certain set of competencies, so often, to avoid throwing the baby out with the bath water, they’d opt to innovate portions of an existing value chain and that would then require closer collaboration (left edge of the scale above). One caveat though, is that you may need to rely on the parts of the value chain, and by implication the people running those parts, to test your innovation. An innovation, that may very well be trying to disrupt another portion for which they are also accountable, so they may actually prove to be obstacles to innovation. It is the corporate equivalent of attempting to get turkeys to vote for Christmas.

Reputation of Innovation Arm

The reputation of your innovation arm also dictates the most appropriate innovation portfolio. If your innovation arm is yet to win over the skeptics in the mothership company, then you may need some quick, incremental wins before you’ve earned your freedom to go after the long-shots. Obviously there are ways to circumvent this, such as ensuring that Innovation teams report directly into the CEO, and using the subsequent hierarchical power to build their reputation, and its associated freedom to innovate. However, innovation teams’ reporting lines would need a blog of its own to fully explore.

Harvard Business Review, published a seminal article that divided innovation up into Core, Adjacent and Transformational (see right, with some additions to the original HBR diagram). They found that different industries, and companies with different levels of maturity, would find a different mix between these 3 types appropriate. However, if an innovation arm still needs to build its reputation then it may well be advised to more heavily weight core innovation, and then, as their reputation for delivering value grows, they can move towards a higher proportion of adjacent and transformational innovation types.

Take-outs:

  • Garage style innovation may not be appropriate for corporates.
  • Clearly define what you’re wanting to innovate (part of a value-chain or long-shot), and choose the appropriate proximity based on your intentions. Take note of corporate culture here too- turkeys won’t vote for Christmas.
  • Consider your innovation arm’s internal reputation in selecting your innovation portfolio.

by Brad Carter

The Dimensions Of An Effective Data Science Team

Organisations worldwide are increasingly looking to data science teams to provide business insight, understand customer behaviour and drive new product development. The broad field of Artificial Intelligence (AI) including Machine Learning (ML) and Deep Learning (DL) is exploding both in terms of academic research and business implementation. Some of the world’s biggest companies including Google, Facebook, Uber, Airbnb, and Goldman Sachs derive much of their value from data science effectiveness. These companies use data in very creative ways and are able to generate massive amounts of competitive advantage and business insight through the effective use of data.

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The Need for Data Science

Organisations worldwide are increasingly looking to data science teams to provide business insight, understand customer behaviour and drive new product development. The broad field of Artificial Intelligence (AI) including Machine Learning (ML) and Deep Learning (DL) is exploding both in terms of academic research and business implementation. Some of the world’s biggest companies including Google, Facebook, Uber, Airbnb, and Goldman Sachs derive much of their value from data science effectiveness. These companies use data in very creative ways and are able to generate massive amounts of competitive advantage and business insight through the effective use of data.

Have you ever wondered how Google Maps predicts traffic? How does Facebook know your preferences so accurately? Why would Google give a platform as powerful as Gmail away for free? Having data and a great idea is a start – but the likes of Facebook’s and Google’s have figured out that a key step in the creation of amazing data products (and the resultant business value generation) is the formation of highly effective, aligned and organisationally-supported data science teams.

Effective Data Science Teams

How exactly have these leading data companies of the world established effective data science teams? What skills are required and what technologies have they employed? What processes do they have in place to enable effective data science? What cultures, behaviours and habits have been embraced by their staff and how have they set up their data science teams for success? The focus of this blog is to better understand at a high level what makes up an effective data science team and to discuss some practical steps to consider. This blog also poses several open-ended questions worth thinking about. Later blogs in this series will go into more detail in each of the dimensions discussed below.

Drew Harry, Director of Science at Twitch wrote an excellent article titled “Highly Effective Data Science teams”. He states that “Great data science work is built on a hierarchy of basic needs: powerful data infrastructure that is well maintained, protection from ad-hoc distractions, high-quality data, strong team research processes, and access to open-minded decision-makers with high leverage problems to solve” [1].

In my opinion, this definition accurately describes the various dimensions that are necessary for data science teams to be effective. As such, I would like to attempt to decompose this quote further and try to understand it in more detail.

Drew Harry’s Hierarchy of Basic Data Science Needs

Great data science requires powerful data infrastructure

A common pitfall of data science teams is that they are sometimes forced either through lack of resources or through lack of understanding of the role of data scientists, to do time-intensive data wrangling activities (sourcing, cleaning, preparing data). Additionally, data scientists are often asked to complete ad-hoc requests and build business intelligence reports. These tasks should ideally be removed from the responsibilities of a data science team to allow them to focus on their core capabilities: that is utilising their mathematical and statistical abilities to solve challenging business problems and find interesting patterns in data rather than expending their efforts on housekeeping work. To do this, ideally data scientists should be supported by a dedicated team of data engineers. Data engineers typically build robust data infrastructures and architectures, implement tools to assist with data acquisition, data modeling, ETL, data architecture etc.

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An example of this is at Facebook, a world leader in data engineering. Just imagine for a second the technical challenges inherent in providing over one billion people a personalised homepage full of various posts, photos and videos on a near-real time basis. To do this, Facebook runs one of the world’s largest data warehouses storing over 300 petabytes of data [2] and employs a range of powerful and sophisticated data processing techniques and tools [3]. This data engineering capability enables thousands of Facebook employees to effectively use their data to focus on value enhancing activities for the company without worrying about the nuts and bolts of how the data got there.

I realise that we are not all blessed with the resources and data talent inherent in Silicon Valley firms such as Facebook. Our data landscapes are often siloed and our IT support teams where data engineers traditionally reside mainly focus on keeping the lights on and putting out fires. But this model has to change – set up your data science teams to have the best chance of success. Co-opt a data engineer onto the data science team. If this is not possible due to resource constraints then at least provide your data scientists with the tools to easily create ETL code and rapidly spin up bespoke data warehouses thus enabling them with rapid experimentation execution capability. Whatever you do, don’t let them be bogged down in operational data sludge.

Great data science requires easily accessible, high-quality data

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Data should be trusted, and be of a high quality. Additionally, there should be enough data available to allow data scientists to be able to execute experiments. Data should be easily accessible, and the team should have processing power capable of running complex code in reasonable time frames. Data scientists should, within legal boundaries, have easy, autonomous, access to data. Data science teams should not be precluded from the use of data on production systems and mechanisms need to be put in place to allow for this rather than being banned from use just because “hey – this is production – don’t you dare touch!”

In order to support their army of business users and data scientists, eBay, one of the world’s largest auction and shopping sites, has successfully implemented a data analytics sandbox environment separate from the company’s production systems. eBay allows employees that want to analyse and explore data to create large virtual data marts inside their data warehouse. These sandboxes are walled off areas that offer a safe environment for data scientists to experiment with both internal data from the organisation as well as providing them with the ability to ingest other types of external data sources.

I would encourage you to explore the creation of such environments in your own organisations in order to provide your data science teams with easily accessible, high quality data that does not threaten production systems. It must be noted that to support this kind of environment, your data architecture must allow for the integration of all of the organisation’s (and other external) data – both structured and unstructured. As an example, eBay has an integrated data architecture that comprises of an enterprise data warehouse that stores transactional data, a separate Teradata deep storage data base which stores semi-structured data as well as a Hadoop implementation for unstructured data [4]. Other organisations are creating “data lakes” that allow raw, structured and unstructured data to be stored in a vast, low-cost data stores. The point is that the creation of such integrated data environments goes hand in hand with providing your data science team with analytics sandbox environments. As an aside, all the efforts going into your data management and data compliance projects will also greatly assist in this regard.

Great data science requires access to open-minded decision-makers with high leverage problems to solve

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DJ Patel stated that “A data-driven organisation acquires, processes, and leverages data in a timely fashion to create efficiencies, iterate on and develop new products, and navigate the competitive landscape” [5]. This culture of being data-driven needs to be driven from the top down. As an example, Airbnb promotes a data-driven culture and uses data as a vital input in their decision-making process [6]. They use analytics in their everyday operations, conduct experiments to test various hypotheses, and build statistical models to generate business insights to great success.

Data science initiatives should always be supported by top-level organisational decision-makers. These leaders must be able to articulate the value that data science has brought to their business [1]. Wherever possible, co-create analytics solutions with your key business stakeholders.  Make them your product owners and provide feedback on insights to them on a regular basis. This will help keep the business context front of mind and allows them to experience the power and value of data science directly. Organisational decision-makers will also have the deepest understanding of company strategy and performance and can thus direct data science efforts to problems with the highest business impact.

Great data science requires strong team research processes

Data science teams should have strong operational research capabilities and robust internal processes. This will enable the team to be able to execute controlled experiments with high levels of confidence in their results. Effective internal processes can assist in promoting a culture of being able to fail fast, fail quickly and provide valuable feedback into the business experiment/data science loop. Google and Facebook have mastered this in their ability to amongst other things; aggregate vast quantities of anonymised data, conduct rapid experiments and share these insights internally with their partners thus generating substantial revenues in the process.

Think of this as employing robust software engineering principles to your data science practice. Ensure that your documentation is up to date and of a high standard. Ensure that there is a process for code review, and that you are able to correctly interpret the results that you are seeing in the data. Test the impact of this analysis with your key stakeholders. As Drew Harry states, “controlled experimentation is the most critical tool in data science’s arsenal and a team that doesn’t make regular use of it is doing something wrong” [1].

In Closing

This blog is based on a decomposition of Drew Harry’s definition of what enables great data science teams. It provides a few examples of companies doing this well and some practical steps and open-ended questions to consider.

To summarise: A well-balanced and effective data science team requires a data engineering team to support them from a data infrastructure and architecture perspective. They require large amounts of data that is accurate and trusted. They require data to be easily accessible and need some level of autonomy in accessing data. Top level decision makers need to buy into the value of data science and have an open mind when analysing the results of data science experiments. These leaders also need to be promoting a data-driven culture and provide the data science team with challenging and valuable business problems. Data science teams also need to keep their house clean and have adequate internal processes to execute accurate and effective experiments which will allow them to fail and learn quickly and ultimately become trusted business advisors.

Some Final Questions Worth Considering and Next Steps

In writing this, some intriguing questions come to mind: Surely there is an African context to consider here? What are we doing well on the African continent and how can we start becoming exporters of effective data science practices and talent. Other questions that come to mind include: To what end does all of the above need to be in place at once? What is the right mix of data scientists/engineers and analysts? What is the optimal mix of permanent, contractor and crowd-sourced resources (e.g. Kaggle-like initiatives [7])? Academia, consultancies and research houses are beating the drum of how important it is to be data-driven, but to what extent is this always necessary? Are there some problems that shouldn’t be using data as an input? Should we be purchasing external data to augment the internal data that we have, and if so, what data should we be purchasing? One of our competitors recently launched an advertising campaign explicitly stating that their customers are “more than just data” so does this imply that some sort of “data fatigue” is setting in for our clients?

My next blog will explore in more detail, the ideal skillsets required in a data engineering team and how data engineering can be practically implemented in an organisation’s data science strategy. I will also attempt to tackle some of the pertinent open-ended questions mentioned above.

The dimensions discussed in this blog are by no means exhaustive, and there are certainly more questions than answers at this stage. I would love to see your comments on how you may have seen data science being implemented effectively in your organisations or some vexing questions that you would like to discuss.

References

[1] https://medium.com/mit-media-lab/highly-effective-data-science-teams-e90bb13bb709

[2] https://blog.keen.io/architecture-of-giants-data-stacks-at-facebook-netflix-airbnb-and-pinterest-9b7cd881af54

[3] https://www.wired.com/2013/02/facebook-data-team/

[4] http://searchbusinessanalytics.techtarget.com/feature/Data-sandboxes-help-analysts-dig-deep-into-corporate-info

[5] https://books.google.co.za/books?id=wZHe0t4ZgWoC&printsec=frontcover#v=onepage&q&f=false

[6] https://medium.com/airbnb-engineering/data-infrastructure-at-airbnb-8adfb34f169c?s=keen-io

[7] https://www.kaggle.com/

by Nicholas Simigiannis

The Doosra

Working in an investment bank over the past decade has provided the opportunity for many interesting conversations around what the value to society of an investment bank represents. Often the model of a “zero sum game” is proposed which suggests that finance often doesn’t add much – in terms of the transactions that banks facilitate, someone is a winner and someone else is the loser, there is no net gain to the world. Other purists would argue something along the lines of efficient allocation of resources. That initially sounded a bit too creative for my more linear reasoning, but after years in the trenches, it has developed an intuitive ring of truth to it.

Working in an investment bank over the past decade has provided the opportunity for many interesting conversations around what the value to society of an investment bank represents. Often the model of a “zero sum game” is proposed which suggests that finance often doesn’t add much – in terms of the transactions that banks facilitate, someone is a winner and someone else is the loser, there is no net gain to the world. Other purists would argue something along the lines of efficient allocation of resources. That initially sounded a bit too creative for my more linear reasoning, but after years in the trenches, it has developed an intuitive ring of truth to it.

Similarly, digital disruption suffers a questionable motive. For some enterprises, such as Uber, it may appear that the shiny plaything of some young geeks on the west coast of america has been allowed to plough through the livelihoods of real people with real jobs and families around the world. When applying such thinking to digital disruption in the realm of investment banking, the question arises as to whether there is any real value that this rather obscure digital offspring of an already often questioned enterprise can produce.

At times this line of thinking led me to check my own passion for this “new vector of commerce”. How do I ensure that my natural fascination with some “new and shiny” geek toy is not diverting what should be a cold, objective application of technology to investment banking, rather than being an excuse to pursue disruption for its own sake. How do we ensure a golden thread of validity and meaning to this exercise.

I started thinking about Google, and how I could justify what value they might have brought to the world (and not just their shareholders). I won’t pretend that I spent much time on this question, but I did come to the following example. Google maps is a fantastic application, and I probably initially loved it more for the fact that in this we have an application that is bringing the real world (travel, maps, my phone, my car) together with the digital world (the internet, GPS technology, cloud based algorithms).

However, it is a tool that many people use, and its value extends beyond that initial fascination. I have considered that in a very real way there are likely to be hundreds of millions of people that might use google maps every day to guide them on an optimal route in their cars. And, true to form, it manages to do this: either by advising detours around potential traffic jams, or by merely showing quicker routes that save time.

That extra time in traffic that has been avoided represents a very real saving in carbon emissions into the atmosphere, and real energy that would have been wasted pumping cylinders up and down in an idling vehicle. This is not a zero sum equation where google benefits and many small companies lose out. This is a very real benefit to the world where increased efficiency reduces the amount of wasted energy, and wasted time of humans. This is a net positive game to the world. In some respect the world of humans win, and the domain of entropy loses – if we are forced to put a name to it.

Personally I would feel deeply gratified if I could produce such a result that created a new benefit to either the world, or at the very least some small piece of it.

Interestingly enough, this speaks to an underlying theme which appeals to many people that are attracted to incubators of disruption, such as the Foundery. Many people do really feel that they would like to be part of something that changes the world. Perhaps this is because such incubators invoke the perceived “spirit” of Google, Facebook and other silicon valley heroes as an inspirational rally cry. I believe that the example of google maps does show that the present opportunity of disruptive technology can represent a possibility for such very real efficiencies and benefits to be created. Perhaps those seemingly naive passions that are stirred in the incubatees are valid, and should be released to find their form in the world.

So how do we harness this latent energy? Where do we direct it for the best chance of success?

Some of the technologies to be harnessed, and which represent the opportunity of disruptive technology:

  1. IoT (the internet of things):

At its most simple, this means that various electronic components have become sufficiently small, powerful and most importantly, cheap. It can become possible and economically viable to monitor the temperature, humidity, soil hydration of every single plant in a field of a farm. To measure the status of every machine on a production line in a small factory in the east rand, without bankrupting the owner with implementation costs.

Apart from sensors, there are actuators in the world such as smart locks, smart lights and the smart home which enable real-world actions to be driven and controlled from the internet. Together these provide the mechanism for the real world to be accessible to the digital world.

This extends beyond the “real“ real world: there are changes at play, not too far under the surface of the modern financial system, that are turning the real world of financial “things” (shares, bonds, financial contracts) into the internet world of financial “things” (dematerialised and digitised shares, bonds online, financial contracts online).

There are also actuators in this world, such as electronic trading venues and platforms which enable manipulation of digital financial contracts by digital actors of finance.

  1. Data is free:

The cost per megabyte of storage continues to drop exponentially, and online providers are able to offer services on a rental basis that would have been inconceivable a decade ago. The ubiquity of cheap and fast bandwidth enables this even more so.

  1. Computation is cheaper than ever, and simple to locate with cloud based infrastructure:

Moore’s law continues unabated, providing computational power that drops in cost by the day. Notwithstanding the promise of quantum computing which seems around the corner

  1. The technologies to utilize are powerful, free and easy to learn:

If you have not yet done so, have a sojourn on the internet across such topics as python, tensorflow, quandl, airflow and github. These represent free, open-source (largely) capabilities to harness the technologies above and make them your plaything. Not only that, the amount of free resources “out there” which can help you master each of these is astounding.

A brief exercise into trying to automate my house using python has revealed hundreds of youtube videos of similarly obsessed crazies presenting fantastic applications of python to automating everything from their garage doors, fishtanks, pool chlorine management systems, alarms etc. These youtube videos are short, to the point, educational, free and most importantly crowd moderated – all the other python home automation geeks have ensured that all the very good videos are upvoted and easily found; and the least fit are doomed to obscurity.

This represents another perhaps unforeseen benefit of the internet which is crowd-sourced, crowd-moderated, efficient and specific education. JIT learning (“just in time learning”) which means being able to learn everything that you need to accomplish a task five minutes before you need to solve it, and perhaps to forget everything almost immediately once you have solved it…. (That is an interesting paradigm to counter traditional education).

( P.S. if you have kids, or want to learn other stuff, checkout https://www.khanacademy.org/ )

Given the above points, it has never been easier for someone to create a capability to source information in real time from the real world, store that information online, apply unheard of computing power to that information using new, powerful and easy programming languages which can be learned online in a short period of time.

It might be a moot point that is valid at every point in time in every generation, but it has never been easier and cheaper to try out an idea online and see if it has legs.

So we have identified people with passion, a means of delivery and so now … what?

Those of you that are paying attention would realise that I have skirted the question of whether we have added any real value to the world, or feel that we can? Time will tell, and I would hate to let the cat out of the bag too early. But there is one thing that is true: if you are one of those misguided, geek-friendly, meaning-seeking, after hours change agents, or if you have an idea that could change the world, come and talk to us … the door is always open.

by Glenn Brickhill

The essence of a FinTech team

Along my short career I find myself wondering what the keys to success are. I have come to the realization that though the media will tell us stories of successful individuals, few key inventions were conceptualized and industrialized by just one person. So what makes a successful team and how would you put one together?

Along my short career I find myself wondering what the keys to success are. I have come to the realization that though the media will tell us stories of successful individuals, few key inventions were conceptualized and industrialized by just one person. So what makes a successful team and how would you put one together?

The idealist within me wishes that I could provide a recipe for the ideal FinTech team. I would like to be able to say in order to revolutionize the world you need 5 analysts, 10 developers and 17 Data scientists but this still wouldn’t guarantee success. So what is the essence of a Fintech team? I may not have all the answers but I do think there are some common elements in truly successful teams.

Purpose

The word purpose is over used but misunderstood. The true meaning of the word took on a new meaning when described by Viktor Frankl in his 1946 classic, “Man’s Search for Meaning” within the context of a World War 2 prisoner camp. Viktor was a neurologist and psychiatrist who was captured and lived in a prisoner of war camp. He shares his observation on the elements of motivation and depression that he observed in his fellow prisoners.  Personally I think Viktor does a better job at explaining it than I could.

Viktor explains that the reason people survived the Holocaust is they had something else to live for, a true purpose. Sometimes this was as simple as a desire to see their family again, in other cases it was more complex. It is this motivation by purpose is that I believe galvanizes a team.

Salim Ismail insists that all start-ups set a multi transformational purpose. These purpose statements need so be short and to the point so that there is no room for misinterpretation. If your purpose cannot be stated in one sentence, then it has not been distilled into its essence. This helps focus all team members at the same goal. Most importantly it means that all team members should believe in the purpose. Getting this right is almost impossible but I would be willing to bet that successful teams have gotten this right. My memory takes me back to South Africa’s 1995 Rugby World Cup winning team who went through the entire tournament with the purpose statement of “one team, one nation.” A purpose that resonates so strongly in all individuals within the team makes it impossible to fail.

http://www.sport24.co.za/Rugby/Springbok-Heritage/1995-RWC-squad-honoured-for-greatest-day-in-SA-rugby-history-20150624

People

I was in awe of these start-up stories outlining how a group of people started a multi-billion-dollar company in their garage.  In the past few years I found myself in the proverbial garage of multiple different acquaintances and friends, it was only then that I realized what was driving this behavior. I found myself drawn to this group merely because we were enjoying the hard work and the time we were spending with each other. It is easier to accomplish a complicated and long goal when you have good people around you that you connect with. I’m not at all saying that you need to be best friends with all your team members but I do believe that you need to find some commonality to have a human connection.

What about skills?

I’m am by no means diminishing the need for skilled people in your team. I am however making an assertion that even if you have the best skills, without a purpose and connected team you are doomed to fail. Pay more attention to the qualitative things when setting up the team. The things we take for granted like the feeling when you walk through the office doors, the vibe in the room, the “nice to have” social interactions.

So I guess my recipe is this:

Find a purpose that resonates with you. Then find a group of people that you can connect with. If the purpose resonates with your team, I believe you have a good chance of success.

by Tyrone Naidoo

Link to video: https://www.youtube.com/watch?v=fD1512_XJEw

Which race are you in?

As we hurtle head on in 2017 its becoming increasingly clear that no matter what generation you find yourself in – Xers embracing tech, Y’s passionately living the dream or Z pushing us all faster than we ever believed we could go – if you are not concentrating…this digital world will run right past before you blink.

http://europe2017.finovate.com/
http://europe2017.finovate.com/

At Finovate 2017 in London last week, I was struck firstly by the intensity of this pace – the leaps that tech has taken over the past year, but also, and more importantly, by the spirit of partnership.

No longer are we in a world where competition is about being the fastest or the smartest, we are living in a world where winning is about bundling those that are faster and smarter than you into meaningful solutions for the business you are in, and the clients that you serve.

In banking it’s too late for us to say “let’s build our own” or “let’s throw money at disruption”; we need to get our heads around connecting fintech dots to build the best solutions for our clients. In biometrics and authentication, the solutions are overwhelming, similarly in app design and integration.  Banking is less and less about paper trails and complicated products and more about integrating whole life solutions with ease of use and integrated platforms. It’s not at all about selling products and more about connecting the right client to the appropriate product they need for the time of their life that they are in – most often aided by a funkily named chatbot.  The world of social media and banking have converged already (yup ship sailed), payments is fast becoming something everyone does …everyone! We can already buy packaged analytics and information about pretty much anything we need.

Banking has morphed from functional practicality to gorgeous design, insightful user experience and lifestyle products that adjust to the needs of its customers. Tricky thing is that much of that “banking” isn’t coming from banks! So what on earth should banks be doing?

Concentrating? Yes. Trying to keep up? No. Collaborating? Absolutely!

Finovate entrepreneurs brought solutions to banking problems we never even knew existed. They challenged views of what banks do and encouraged us all to ask “how can we help you help us help our clients?”  More importantly though, they showed what collaboration brings.  Over and over as the 7 minute spots passed by, it was clear that these entrepeneurs are building on what each other are building.  Each using bits of what others had built, to supersize the solutions they were prototyping.

And that is the way to stay in the race! So as we train for the year ahead, we need to make sure we have the insight to navigate the way forward, the partnerships with fintechs to supersize our banking offerings and the deep relationships with clients to package this stream of incredible ideas in ways that makes them not only satisfied but thrilled with the way they interact with our ecosystem.

by Liesl Bebb Mckay

A case of keeping up with the Joneses?

The world is changing. Drones are fighting in armies, driverless cars are no longer a fiction of someone’s imagination, robots have the ability to outsmart humans in offering legal and financial advice. Exciting? Most definitely. But for a developing country such as South Africa there is also a sense of uneasiness.

South Africa and the Fourth Industrial Revolution

Source: genesisnanotech.com
Source: genesisnanotech.com

The world is changing. Drones are fighting in armies, driverless cars are no longer a fiction of someone’s imagination, robots have the ability to outsmart humans in offering legal and financial advice. Exciting? Most definitely. But for a developing country such as South Africa there is also a sense of uneasiness. How will our economy keep up with a changing world while having to fight poverty, inequality, corruption? As one of the most unequal societies of the current age one has to wonder what technological advances will do to the already high Gini coefficient? Are we entering a dystopian world order where some countries will ride the wave of a revolution and others will be left behind, feeding on the scraps?

Prof. Klaus Schwab from the World Economic Forum has proposed that a fourth industrial revolution is imminent. An industrial revolution is seen as a change in the basic economic structure, driven by innovation and invention. In the late 18th century coal and locomotives introduced the first industrial revolution with mechanization being the key driver.  The fourth industrial revolution will fundamentally change the world that we live in through so-called cyber physical systems where the natural, human and digital world meet. In short, extreme automation and connectivity might mean that boundary lines between humans and technology are blurred with concepts such as artificial intelligence, virtual reality and the internet of things taking civilization where it has not gone before.

While South Africa’s economy relies heavily on its natural resources the question is whether the country has progressed sufficiently on the ladder of previous industrial revolutions, or rather whether a platform has been created from which to launch into the rising age. One simply has to look at the state of railways and even the huge amount of manufacturing that happens off-shore to wonder whether South Africa has been able to progress industrially with the rest of the world. UBS highlights in a white paper (Davos 2016 White Paper) that South Africa is behind the curve with regard to the evolving of manufacturing along with demographics. In effect, the failure to move to high level of manufacturing with the demographic prime could indicate that SA has not adequately adapted to the second and third industrial revolutions.

The question remains whether the fourth industrial revolution would be a case of keeping up with the Joneses or whether it would be possible to fast track development in order to launch South Africa into the new era.

Africa is a continent that upholds a certain reputation for innovation particularly to overcome obstacles often created by the lack of development in a certain area. The continent is also seen as an early adopter of technology, with success stories of financial applications such as M-Pesa flying the flag for an innovative continent. Pockets of excellence mean that it is not all doom and gloom for South Africa. The financial sector is one of the best in the world and may well be a field in which new technologies will get traction.

The WEF looks favourably towards South Africa in terms of innovation and new fourth industrial revolution indexes in their Global Competitiveness Report (2016-2017) (WEF – Global Competitiveness Report ) with the following global ranks: innovation and sophistication (31st), business dynamism (50th) and innovation capacity (38th ) perhaps indicative of the silver lining of promise that the country will punch above its weight in the revolution.

Although ranked low in basic requirements and some efficiency parameters indicating a lag in fully adapting to previous industrial revolutions, positive innovation rankings paired with the right industry, such as financial markets, could position South Africa favourably in terms of moving towards the fourth industrial revolution.

It would be easy for South Africa to adopt a fearful approach towards the new era of automation and robotics. In a country with high unemployment low-skilled workers are likely to face a world where the job-market has no space for them. Some pessimists are predicting a world where humans are not needed. The reality is that change is coming and being a country that is able to adapt is non-negotiable. Education has been a pain point and South Africa is ranked a low 123d on the Global Competitiveness index for Health and Primary Education. Education is a critical factor to the challenges that a new revolution would bring forth and ensuring that a new generation can hold their own in a changing world will make the difference between those running the race well and those falling out along the way. Adapting education models is an important measure to be put in place if South Africa wants to approach the fourth industrial revolution with courage.

In our experience, it is evident that successful disruption is often birthed within a start-up atmosphere. Where current incumbents, especially in the financial sector, are faced with issues such as integration and legacy systems, a start-up with a dedicated and talented team and a great innovative idea have a greenfield approach that lends itself toward disruption.

Drawing the parallel to country-wide development there is a case for cheering on Africa and South Africa’s jump to the fourth Industrial Revolution modelled as a start-up with leeway to embrace the new era and its corresponding shifting boundaries. Leapfrogging some of the essential factors of previous revolutions toward a new disruptive way of using computer systems to address fundamental social problems. But investments in skills, particularly software development and the required infrastructure will need to be fast-tracked to create an enabling environment for the innovative nature of South Africans – to not just keep up with the rest of the world but to leverage a strong innovative culture and excel.

                               by Charlotte Hauman

 

RegTech: a key component of the burgeoning FinTech movement

Unpacking the opportunity to build a robust, compliance function with innovative tech solutions promising many benefits, derived from a number of applications.

http://www.memes.com/meme/554682
http://www.memes.com/meme/554682

A few months ago, I was lucky enough to be “the chosen one” at our consulting firm to join the rest of our team working at the Foundery. I was told that the Foundery was all about developing FinTech capabilities to solve inherent challenges within banking in a unique way. Thus, we had to be up-to-date with the new technologies in this space. “RegTech” was one of these new technologies that were on our radar, and I had to develop a research pack on it… My initial reaction was that of a student opening up her exam paper having no idea where to begin… and in this case, there would be no “winging it” either! Yet, as I embarked upon this journey, I was fascinated by the immense potential of reducing compliance costs for financial institutions using this technology of today to facilitate the delivery of regulatory requirements in an innovative way and wanted to delve deeper into this amazing world of RegTech. So, here are some of my discoveries from this journey:

What is RegTech?

RegTech, as the word suggests, is an amalgamation of regulation and

 https://www.trulioo.com/blog/regtech-solutions-for-regulatory-compliance-requirements/
https://www.trulioo.com/blog/regtech-solutions-for-regulatory-compliance-requirements/

technology, a niche carved out from Fintech. Javier Sebastián, BBVA Research’s expert in digital regulation, also explains that it is deemed a subarea of what is generically known as Fintech. He adds that RegTech providers who are, “harnessing the capabilities enabled by new technologies such as cloud computing, big data, and blockchain, are devising solutions to help companies across all sectors of activity ensure that they comply with regulatory requirements.”

What type of solutions does RegTech offer?

Globally, RegTech encompasses many different technologies that can reduce the cost of compliance & show commitment to high standards of regulatory compliance, through the use of advanced data analytics, risk & control convergence, and sustainable & scalable solutions. The solutions can fall into three buckets: Interpretation, Implementation & Optimisation.

  • Interpretation solutions are solutions that help in decoding regulatory requirements. These include regulatory gap analysis tools, compliance universe tools and training tools to track and understand the regulations & help build risk management plans thereof.
  • Implementation solutions assist in doing the actual work to meet the regulatory requirements. These include regulatory reporting & health check tools, incorporating everything from compiling and interpreting data, to producing gap analyses and ad-hoc reports.
  • Optimisation solutions are customised solutions that simplify the compliance process further, on an organisation level, through automation and machine learning. Management information, transaction reporting & analysis, and case management tools fall under this category. These tools empower compliance functions to make informed risk choices based on data-provided insights about the compliance risks the company faced and how it mitigates and manages risks.

Is there really a need for RegTech?

https://letstalkpayments.com/global-regtech-the-billion-dollar-opportunity/
https://letstalkpayments.com/global-regtech-the-billion-dollar-opportunity/

The cost of compliance in the financial services industry is high, and continuously rising, with the supervisory backdrop growing more complex, and constantly changing regulations and processes. According to the Consumer Financial Protection Bureau of the United States of America, on an average, large banks with an asset size of $1 billion to $100 billion, have total compliance costs of 1.4% of estimated retail deposit operating expense. Operations, HR and IT carry the largest share of these costs. The cost of non-compliance is even higher than the cost of compliance, with increasing penalties and fines paid by banks year-on-year.

 

https://www.trulioo.com/blog/regulatory-curse-regtech-opportunity/
https://www.trulioo.com/blog/regulatory-curse-regtech-opportunity/

Investments in regulatory software have the potential to address this immediate challenge of regulatory compliance which can lead to an ROI of 600+% with a payback period of less than three years, according to letstalkpayments. Hence, the global demand for regulatory, compliance and governance software is expected to reach USD 118.7 billion by 2020. But, yet it still remains a relatively small recipient of Fintech funding. This is because dominant, widely used solutions are yet to emerge, and financial institutions are often still unfamiliar with the technology. Regulatory reform is also not yet complete; uncertainty about the exact reporting requirements makes it harder for financial institutions to choose a particular compliance solution.

Is RegTech here to stay?

With growing regulations, there is a growing demand to oversee data, reporting, and operational processes. A growing number of start-ups have the potential to meet this demand. But, RegTech is about the application of technology to solve a specific regulatory problem, rather than the technology itself. Thus, each of the key players in the system has a distinct role to play in the growth of this technology, through the development of common industry solutions and successful integration into risk management frameworks within the wider regulatory change agenda. Financial Institutions have a primary responsibility for supporting this development, by creating IT and risk infrastructures that are capable of integrating these new solutions.

Supervisors and regulators can also provide support by creating an enabling regulatory environment, where financial institutions can safely share their challenges in compliance and opportunities. The UK is taking the lead to encourage the rest of the world to follow suit. In 2015, the Financial Conduct Authority (FCA) announced its 2016/17 business plan focussed on supporting the widespread adoption of RegTech. The FCA, through its ongoing roundtables and bilateral meetings, has provided a platform for collaboration between software developers, financial institutions and the public sector.

My final take on this?

South Africa has a lot of catching up to do!

by: Rachana Bedekar