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Learning to drive: data strategy

Commercial banks around the world are operating in a challenging landscape, facing compressed margins, high costs to serve and disruptive competition in key segments such as small and medium businesses (SMBs). Many are responding by ramping up investment in data, advanced analytics and artificial intelligence (AI).

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Yet most have encountered roadblocks on their journey towards data-driven reinvention. While many have developed pockets of data and analytics excellence, they are struggling to scale up deployments, embed data-driven decision-making into day-to-day operations and use data to drive truly transformative change across the business. In fact, a 61 per cent average return on investment is being achieved by banks that have progressed further in terms of data maturity.

“Commercial banks have a wealth of data to fuel better decision-making, empower relationship managers, automate processes and add value for their customers.”

Yet much of the rich, real-time transactional data to which banks have access lies fallow.

Looking for exponential returns

Unlocking the value of data and putting insights into the right hands throughout the business will enable commercial banks to compete more effectively with new-age rivals including fintechs, bigtech and neo-banks. Tomorrow’s leaders know the time for experimentation, proofs of concept and siloed deployments is over. They are looking to move from incremental change to exponential improvement.

Commercial banks have a wealth of data to fuel better decision-making, empower relationship managers, automate processes and add value for their customers. Yet, despite significant investments in using data and AI to improve sales, productivity and performance, most are only realising incremental returns.

Obstacles to growth

A focus on small-scale pilots and projects has meant many commercial banks are focusing data-driven transformation efforts on making incremental improvements to existing business models and processes. The focus tends to remain on easing immediate pain points rather than on breakout innovations that could drive exponential returns.

 

Also, after years of investment in building a digital foundation, banks and their people have become fatigued by technology change. Building this foundation and digging the bank out of technical debt is an all-consuming effort and the prospect of embracing yet another complex IT program can become daunting.

 

Breaking through these obstacles begins with the insight data-driven reinvention is not a departmental or technology project – it’s an enterprise-wide effort taking leadership from the top.

A common strand in data-driven leaders across different sectors is the prioritisation of data on the C-suite agenda, with leaders encouraging the sharing of knowledge, data-driven decision making and the taking of appropriate risks.

Data leaders see these capabilities not just as a competitive differentiator but as a means of driving return on investment.

 

Boosting growth

 

New data present a tremendous opportunity to unearth hidden signals and drive growth in commercial banking.

The challenge? In a complex, fast-changing digital and data ecosystem, it can be difficult to get data insights into the right people’s hands when they need them.

Integrating rich insights into a relationship manager’s day-to-day ways of working will enhance effectiveness and productivity and deepen relationships. Banks need multi-level segmentation, customer lifetime value and behavioural insights to retain and grow their existing portfolio, as well as manage risk.

As a bank moves further up the data maturity curve, it can use analytics to solve more complex problems as well as deploy AI to drive higher levels of automation.

 

Amplifying the results

 

Banks that want to turn data into a real competitive asset are looking at how they can align their data strategy with their corporate strategy.

This industry vision will be led from the top with a roadmap for:

  • Getting the basics right: using data and AI to monetise core business strategies.
  • Partnering to grow: creating ecosystem partnerships to provide a broader end-to-end customer experience.
  • Shaping new business models: leveraging data as a competitive differentiator to enable entirely new businesses.

As an initial step, banks will assess their platform’s ability to support their overall data strategy and accelerate their efforts to catch up on digital, AI and data asset technical debt. But they will also keep their eye on scaling their deployments and nurturing an agile, data-driven culture across the entire business.

Those that get it right will set themselves apart in an increasingly contested commercial banking landscape.

Chris Jaggard is Commercial Banking Lead at Accenture Australia and New Zealand

The views and opinions expressed in this communication are those of the author and may not necessarily state or reflect those of ANZ.

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