“Code” is everywhere in business today. Fuelled by data, Code lives in the algorithms that are the strategic weapons in the information age. We’re in an era of “code or be coded” and industries are getting rebooted.
From Amazon, Google, Microsoft and IBM to Uber, Square, Stripe, Airbnb, Docker, and a host of new “unicorns” (new companies valued at over $1B), Code is at the heart of their disruptive technologies, their new business models and their fantastic user experiences.
Code: Algorithms hit the C-Suite Agenda
Code is driving new business strategies including the topic of this post: the hot “FinTechs” (financial technology companies) rising in the traditionally stable Financial Services (Ten CEOs who are disrupting finance with technology).
The importance of understanding Code is why Bloomberg Businessweek recently published an entire 38,000 word essay in a double issue (June 11, 2015) for the purpose of “demystifying Code” to executives – (all executives, not just Chief Information Officers and Chief Data & Analytics Officers). The cover’s call to action: “If You Can’t Read That, You’d Better Read This“. It’s an excellent issue that gets right to the point:
“Recognizing that the world now belongs to people who code, and those who don’t understand it will be left behind, the issue is devoted to demystifying code and the culture of the people who make it.”
“Code directs the fate of everything from media to e-commerce to banking, and is arguably the most important phenomenon for the twenty-first century businessperson to understand. Yet it remains an intimidating mystery to most execs…Which means that people have been faking their way through meetings about software, and the code that builds it, for generations… ignorance is no longer acceptable.”
Fundamentally, Code is shorthand for the software and algorithms that digitize business processes by storing and swiftly moving data. While Big Data is getting the spotlight, Code manipulates and analyzes the data to drive new value from it. Code is what makes up artificial intelligence, machine intelligence and cognitive computing.
With a tidal wave of data (Goldman Sachs: 28 Billion things by 2020 ) flooding business from the “Internet of Things” (IoT), every business will be increasingly information-rich. What we do with all that data to improve customer experiences and drive efficiencies is today’s pressing question.
From healthcare to publishing to financial services, we’re in the process of digitizing and Coding virtually every industry.
Algonomic Strategy – A New Model for Business Strategy for Code and Data
It’s long been said that data is a strategic asset – but what then is the strategy? I suggest today’s overarching executive challenge is to develop a Code strategy to take advantage of Big Data and Analytics, to drive value for customers, employees, and shareholders. Just as financial knowledge became a requirement throughout the C-suite, arguably every CFO, CMO, CHRO & CRO should be Code-savvy and partner with the CIO and CDO on an aligned data-driven and Code-driven business strategy.
I think of this information-age approach to business strategy with a new term I call being “Algonomic“. An Algonomic strategy describes how the business will compete in the market to deliver economic value using algorithms (aka “Code”) either owned in house or licensed, big data, and analytics.
Google, Facebook, Amazon are largely companies natively built to deliver services and compete with their Code. Code is their strategic weapon and they’re highly Algonomic, making use of large amounts of data to drive the best advertising engines, friend suggestions, and book recommendation engines. They nurture their Code and, they’re so good at it they’ve begun offering their machine intelligence to other organizations as a cloud service.(See Amazon’s Cloud (Profitably!) Powers Major Brands, Amazon Web Services)
Executives defining strategy in the information age need to understand how information flows through the thousands of Application Programming Interfaces (API) of the “programmable web“. Code and data strategies underpin new collaborative partnerships (e.g. IBM in data sharing agreements with Twitter & Facebook) and competitive battles (e.g. Apple vs. Google vs. Microsoft vs Amazon in the Cloud Services space). Data and information sharing strategies (HBR: “The Strategic Value of API’s”) will drive new data-driven services and Code needs to be thought of by the C-level as a strategic asset too.
It’s 2015 and Here Comes FinTech…
So, given how critical Code is to business success, let’s use Code as a theme to see its impact in the banking and financial services industry, where arguably Big Data began.
A previous blog, FinTech Startups: Unbundling Wells Fargo, Citi and Bank of America, highlighted the potential disruption already taking place in banking. Many new non-bank startups are bringing Code with them to attack the incumbents on their own turf. Bain & Company also focused on the topic with Rebooting IT: Why financial institutions need a new technology model.
In addition to high profile “Ten CEOs who are disrupting finance with technology”, the overall pace of FinTech development is accelerating. VentureScanner.com is monitoring over a 1,100 FinTech companies over at least 15 categories. They also have a good view on Which Financial Technology Category Is Most Mature. At 5 years of age, Square is a relative newcomer and crowdfunding is even younger. It’s challenging to keep up with the pace of new entrants.
Recently, Santander Innoventures, Santander Group’s innovation fund partnered up with management consultants Oliver Wyman and digital financial services investment firm Anthemis Group for this must read report: The FinTech 2.0 Paper: rebooting financial services
They conclude: “Fintech 2.0 will cause a major disruption of the banking market“. The recommended response, with Santander being one of the Big Banks with its own FinTech investment arm, calls for a stronger collaboration between FinTechs and the banks to realise the incredible opportunity ahead:
“Fintech 2.0 is just around the corner. It will deliver fundamental changes to the infrastructure and processes at the core of financial services… Fintech 2.0 will cause a major disruption of the banking market, as digital technology has in other markets, such as travel and entertainment. Pre-digital business models and processes will be rendered obsolete.”
“The strengths and weaknesses of both banks and FinTechs mean that both will often do better by cooperating rather than by competing.”
“FinTech 2.0 represents a far broader opportunity to re-engineer the infrastructure and processes of the global financial services industry, in which the top 200 banks command a revenue pool worth $3.8 trillion… to realise the opportunity of Fintech 2.0, banks and fintechs will need to collaborate.”
It’s a short but important report – in my view, the exciting and enlightening part of this report is their broad vision for how IoT will change financial services across the board, such as trade finance and mortgage lending.
A few key excerpts from the report:
Streamlining Trade Finance (revenues growing 8% p.a. to $70B by 2020) with Real-time IoT
“IoT technology willl provide banks with real-time access to trade data, eliminating the need for manual checks and paper documentation such as bills of lading. For example, GPS data would automatically alert the issuing bank once a shipment arrives at a port, and sensory technology would provide information on the condition of delivered objects. The IoT could give sellers and their banks access to real-time information they need regarding goods in transit.”
“Access to real-time trade details would enable digitised smart contracts to be verified instantaneously, assuming pre-defined conditions are met. This would allow a letter of credit to be issued more efficiently than in today’s trade finance process.”
Note that IoT will transform the industry to “real-time”. In my experience, anything approaching real-time was considered prohibitively expensive with traditional technology. Digitised smart contracts will be data-rich and new Code will be needed to manage them. Today’s low cost storage and cloud computing technologies will make real-time very real, very soon.
Leasing and Asset Financing
“Inefficiencies in the global collateral management market are estimated to cost banks up to $4 billion annually. Adopting IoT technology could significantly reduce this figure as real-time monitoring technology will improve valuation accuracy and render more assets eligible for collateral financing.”
For those embracing the digital frontier, lending services will expand and operating efficiencies will be a bottom line benefit. Real-time monitoring of assets will require new Code. The strategic question is whether this will be a function provided today’s banks or whether new service providers will manage the data and provide that service to the banks.
Banks lag behind Firms in Other Industries
“Despite substantial investment in data management, financial institutions lag behind firms in other industries. It is not unusual for large banks to spend upwards of $500 million on programmes to address the challenges related to data, yet it is widely acknowledged that these investments have not been translated to increased profits. Banks are not nearly creative or enterprising enough in their attempts to use data to offer better products or cut operating costs.”
Yes, big bank data programs have been expensive. In fact, new regulatory requirements (e.g. BCBS-239) are driving these programs. While it’s easy to criticize a lack of entrepreneurial creativity and drive, there’s also a very good argument that existing players are stuck with legacy systems that can’t just be turned off. Large banks do, however, need visionary leadership to drive replacement of the legacy that holds them back and places them at a disadvantage to upstarts with the ability to build from greenfield.
A Global Efficiency Play with Distributed Ledgers
“Our analysis suggests that distributed ledger technology could reduce banks’ infrastructure costs attributable to cross-border payments, securities trading and regulatory compliance by between $15-20 billion per annum by 2022.”
Bitcoin and blockchain made it possible. Banks with innovation labs like Citi are experimenting with the new distributed ledger technology (see: Citi Creates its Own Citicoin). The US Fed is definitely watching closely: “the Federal System could utilize a distributed ledger system to keep all the books simultaneously in their member banks. So in case of a system breakdown, the records could be recovered from the ledger.”
Mortgage Lending Will Be Less Painful ($25 trillion in new mortgages issued globally every year)
“Digitisation is taking much of the pain out of banking. This progress, however, has been limited mainly to transaction accounts and consumer lending. Mortgages and long-term savings products still involve processes that are expensive, time consuming and a source of customer dissatisfaction. Removing the “friction” from these products is where the greatest opportunity now lies.”
OnDeck and Lending Club , Prosper, and Canada’s Borrowell have started with business and personal loans. Their approaches resonate with the customer experience Millenials have grown to expect — including a brand new set of mobile apps driven by new Code. These new companies are coding in new ways – running internal hackathons (e.g. new player OnDeck has run two already ) with talent that thinks web first and isn’t afraid to take risks.
Robo-Advisors are on the Way
Industry advisors may not agree on timing but agree that robo-advisors are here to stay (EY).
“Algorithm-driven investment platforms typically focus on just a few variables, such as asset diversification and risk tolerance, without taking account of other important variables, such as the customer’s current investments, especially where these are not tradable securities.”
“Fintech players could automate several basic PFM services such as estate planning (e.g. setting up trusts), life insurance and basic tax planning. Current robo-advisors can extend their offering up the wealth spectrum, for example, to include people worth $1 million”
NestWealth, Wealthsimple , Betterment among others have entered the race in this space. There’s been much written about the Millenials and their natural expectations of a mobile experience. For example, Betterment’s message hits directly at the big banks with “We help people to better manage and grow their wealth through smarter technology for a fraction of the cost of traditional financial services.”
Also, at the World of Watson recently, IBM and Development Bank of Singapore (DBS) showcased how they’ve “taught” the Watson cognitive computing engine how to make daily product recommendations that its Relationship Managers can present to its Wealth Management customers. It doesn’t replace RM’s but, as Olivier Crespin explained, it certainly makes them smarter. Analyzing hundreds or thousands of client and DBS parameters relating to its investment products and global financial conditions just wasn’t possible before the new era of machine intelligence Code that manipulates ‘big data’.
The Opportunity to Partner with FinTechs
The report concludes: “The message to banks and to fintechs is the same: if you can’t beat them, you should join them to achieve Fintech 2.0”
“Banks could take advantage of the specialised expertise at fintech companies by engaging these firms to perform the required work or by acquiring them. Partnerships between banks and fintechs would create a powerful combination of information, supplied by the bank, and innovative analytical tools, supplied by the fintech.”
“Identifying problems that can be solved by data is the first step to its smarter use. Assuming banks make their data readily accessible to those who need it, specialised teams can be assigned to problems such as these and create algorithms that uncover trends, patterns and anomalies. Then banks will be able to extract value from their ever-increasing supply of data.”
Code: The New Strategic Opportunity
So, as the pace of FinTech startups wielding new Code increases, incumbent banks find themselves in relatively new territory but they may still be in the driver seat. As noted in “Will Nonbanks Kill the Banks?“, nonbanks such as Moven and Lending Club provide experiences generally superior to those of banks, but still rely on banks to operate. While their regulatory pressures increasingly require attention and resources, the Big Banks need to rapidly assess the strategic threats and opportunities from the potentially disruptive FinTechs.
Being strategically Algonomic, focusing on the algorithms and the data is one way to approach it. In the Algonomic model, I’d approach it with many strategic questions, including:
- Which of the Fintechs will resonate most with the customer experience demanded by increasingly demanding clients today?
- Are some FinTechs best for innovative analytics to service the Banks’ relationship managers?
- Which FinTechs are threats to the Big Banks and which ones should be service partners?
- How will the partnerships shape up amongst the Big Banks? Will some be exclusive?
- Which FinTechs will survive threats from each other?
- Which FinTechs have protected their intellectual property with patents and will be the likeliest to grow?
- Which FinTechs can and should be acquired as a strategic asset?
- Do the Banks’ M&A teams have experts in software?
Coming full circle, we’re seeing how disruptive and strategic new “Code” can be for Financial Services. With new data, Code will underpin a new era of services, drive enhanced customer experiences across mobile and other channels, enable new personalized marketing and sales, and improve efficiency for the Back Office. FinTechs have the advantage of being able to reimagine financial services, but they’ll need to align with Big Banks who understand today’s regulatory environment. Executives making strategic investment and partnering decisions will need to treat Code as a strategic asset. The wave of IoT data will certainly make data quality critical as the fuel for the organization’s Code.
Welcome, “Code”, to the C-suite agenda.
Let’s continue this conversation. Connect with me on LinkedIn. Follow me at Twitter @alanwunsche and @algonomic. (This Algonomic Blog discusses topics important to CIO’s, CDO’s and the strategic and economic importance of Code in business)
I’m a strategic information solutions executive combining financial acumen, consulting discipline, technology expertise and delivery experience. I envision, develop and implement leading edge information solutions to grow and optimize business.
As an operating executive and management consultant, I’ve been a trusted business partner to CIO’s, CFO’s, CRO’s, CMO’s and CHRO’s improving business performance by transforming finance, customer and risk systems, processes and organizational structures. I’ve led large financial and operating information systems programs (including SAP, Oracle, IBM Cognos Business Intelligence, SunGard, Moody’s Analytics) and enabled better, faster decisions for customer profitability and risk.