Welcome to Data Strategy Chats with Synthesized - a brand new blog series where we discuss the hottest topics in the world of DataOps with technology leaders and data practitioners from around the world.
In our first episode, Nicolai Baldin, Synthesized CEO and founder, welcomes NextWave CEO and Founder Dave Aston and founding partner Iain Ivey to share their thoughts on what’s driving the executive agenda in financial institutions in terms of data challenges and the role of the Chief Data Officer.
NB: I’m thrilled to welcome Dave and Iain to our new blog series. David, based in Amsterdam, is focused on large scale transformation and the application of the latest in technology and innovation, developing solutions that are specific to the financial sector, drawing on his more than 30 years of experience at top-tier financial firms, in Europe, the Middle East, U.S and Asia.
Iain, based in London, brings a wealth of experience and real world learnings from the financial sector as both a consultant and industry practitioner. Iain held various leadership roles in his previous organisation such as Head of Data Design, Head of Regulatory Compliance IT and Chief Risk Architect among others.
NB: It goes without saying, 2020 was a strange year - many aspects of the Finance sector including internal processes and external operations were affected and had to adjust to the new environment. Despite the pandemic, one trend, which we noticed at the beginning of the year with our partners, is clear - the Finance sector keeps investing in automating internal data operations and processes. David, Ian, as we start 2021, what do you believe are the top 3 data challenges on the executive agenda?
Overall it is a drive to use data more effectively in the running of the business. The immediate challenges we see in the market are:
- The focus is on cost control, staff reductions and restructuring the business, and banks are looking closely at data to make these decisions.
- Defaults and fraud in the loan book – COVID has shifted the landscape massively and executes need to be on top of this data intensive process.
- Automation, data analytics, optimisation and leveraging technology to reduce costs is a constant challenge and very much on the agenda heading into 2021.
NB: And why are these challenges immediate? What creates the urgency and the need to act now?
COVID related provisions, write-offs and their impact on returns to shareholders are forcing cost control, staff reductions and business restructuring to the top of the agenda. This is further exacerbated by losses in specific businesses as a result of fraud (e.g. Trade Finance). For traditional organisations, the cost base is just too high and there is a new wave of innovation and technology that can help reduce the cost base.
We’re seeing a massive rise in defaults and fraud in the loan book. 2020 has seen high levels of provisions and a massive increase in lending as a result of COVID (much of it rushed through at the behest of governments). Banks are expecting non repayments to reach 50% or more.
Banks see their competitors rapidly adopting new technologies; cloud computing, low-code, data analytics and RPA led tooling, all focused on driving automation and data optimisation to reduce costs. Those that do not adopt new tech quickly will be left behind and will continue to suffer high costs and loss of clientele due to poor and outdated customer experiences.
Our belief is banks must focus on new technology now more than ever to create new business opportunities. By harnessing new technology they can achieve the intelligence critical to better understanding customer behaviours buried in their mountains of data.
NB: We’ve discussed that leveraging technology to automate internal data processes is one of the focus areas of a chief data officer. Since the first chief data officer was appointed by Capital One in 2002, the CDO role itself has evolved and risen to prominence. In your view, why is the CDO role important and what an FS organisation expects of its CDO now vs previous years?
The CDO was originally seen as a custodian of internal data standards and the role was really created as a response to regulatory requirements. It started as a cost centre type role that focused on data quality to drive usability of data within the organisation.
The CDO role is evolving to be a custodian of data products to create value and provide better protection and risk management for the organisation.
The new data products can deliver value in a number of ways:
- Better customer service for retaining clients (revenue protection)
- More focused cross selling based on behaviours
- Protecting the business from KYC, AML, Fraud related issues by enabling better data analytics when on-boarding new customers
- Better control through data driven continuous control monitoring through 1st and 2nd Lines of Defence
NB: You have both added substantial value to the Finance sector during your career at HSBC, NatWest, ABN AMRO, Merrill Lynch and other FS organisations. When the UK is no longer in the EU, and in view of the pressing data challenges on the executive agenda, the Q1 is absolutely crucial to set the right priorities for the business. What are your top 3 practical recommendations to financial institutions?
The key focus is on being ‘practical’ – not just blue sky thinking.
- Continue to ‘’lean in’’ to digital transformation, both from a client perspective and internal processes and activities. Look at low-code as a means of accelerating this transformation.
- Adapt the organisational mindset to allow the business to leverage new technologies to improve automation and reduce costs (e.g. by changing procurement guidelines)
- Look to get more out of data, across all areas of the business, while reducing the risk profile. Define and build safe ‘data products’ upon which to apply extensive data analytics to service use cases across Compliance, Risk, Fraud and the Customer.
Digital disruption and innovation have been accelerated by COVID and this will continue across 2021. Those who leverage new technologies quickly and lead their adoption by specific use cases will see the most benefits. Those who lag behind and wait too long, risk being left ‘far’ behind, and this will happen very quickly.
Find out more about this by downloading our white paper on enabling best data practices with AI-powered data assets.