Financial services experienced an unprecedented period of growth, from 1988 – when interest rates were at a peak – until 2006 when excessive risk taking caused serious problems.
During this period of growth, banks, insurance and other financial sector companies grew, increasing profits, headcount and reliance on financial services information technology (IT). Since the crash of 2007-08, which precipitated the worst economic decline in a generation, the sector has recovered.
Banks are growing again. The sector, partly thanks to accelerated startup (FinTech) innovation in London and New York, and new customer needs and trends, is evolving faster than ever before. At the same time, new regulatory pressures, from financial regulators and data protection legislation in Europe (GDPR) – are creating multiple complexities that did not exist ten years ago.
Complexity in the financial services sector
It is impossible to eliminate complexity in financial services. Bank business models depend on multiple complex features, including risk management, economies of scale, globalisation and risk diversification. How banks interact with customers, subsidiaries, regulators, other banks, mutual funds, insurance companies and central banks increases this complexity. Again, this is unavoidable and a necessary by-product of financial sector business models.
Almost all of these interactions happen using information technology.
Without IT, the sector could not serve billions of customers around the world, providing everything from credit to insurance and savings accounts. Product innovation is another by-product of complex IT systems and new customer needs since banks can access a complex array of data points, indicating what customers really need, thereby making it easier to create new products/services and serve new markets and groups of customers.
With automation, self-serve, online/mobile banking, machine learning and artificial intelligence (AI), billions of interactions happen every day, through a myriad of IT systems, automatically, or without any input needed from financial sector employees.
How can financial services companies manage complexity?
Oliver Wyman, using data from multiple sources, have found that financial firms produce a much lower return on equity (RoE) than before the financial crash, down from 20% in 2006 to 7% in recent years. Returns from twenty four banks (8 US, 16 worldwide) – considered global systemically important banks (GSIB) – have reduced 70% since 2006.
Investors and regulators – and banks that acknowledge the issues in investor reports and earnings calls – all cite complexity as one of the reasons for lower yields. Most GSIB banks in Europe and America have five board committees overseeing risk/compliance. Before the crash, most only had three or fewer committees.
Managing complexity at scale, under more scrutiny than ever before, is one of the main challenges the sector faces. Several ideas are floating around, from an IT perspective that could make complexity and risk more manageable for financial sector firms.
#1: Systematic employment of big data throughout an organisation’s data pools. Recent experience from the insurance industry has found that 10% profit uplifts are possible when AI and machine learning is used to analyse customer data, third-party sources and risk management: Taking underwriting to a whole new level with AI-powered algorithms.
#2: Standardise decision making from top to bottom. Automation could reduce layers upon layers of middle management, or make it easier for management structures to evolve, to focus on the customer experience, new products, markets and revenue streams.
#3: Improved customer targeting. Banks already have a huge amount of information on their customers, with even more available through third-party sources (e.g. web/mobile tracking, email marketing, social networks, credit agencies, etc.). With the right application of real-time big data, customers could receive highly targeted offers, when a need exists / is relevant (e.g. 0% credit card offer before a holiday), within flexible and scalable risk management models.
#4: Make managing complexity a C-suite and board issue. Banks are complex organisations. In most financial sector companies, there have been multiple attempts to reduce complexity and improve service delivery. Many of these initiatives fail, according to Oliver Wyman interviews and in-depth research.
When initiatives are only IT or operations-driven, without C-suite support, they fail. Despite the fact that these are problems leaders need to solve. Financial sector leaders can – with the tools and talent they already have (or could easily get) – reduce complexity, with the right combination of new processes, culture shifts and a clear understanding how technology can reduce decades worth of existing complexities built into financial sector business models.
Cloud Business work with several well known financial services institutions providing operational IT support and strategic consultancy services. If your organisation is interested in exploring how IT can help reduce complexity and create a more agile and responsive environment, please get in touch.
