The case for an enterprise-wide approach to analytics in retail banks

By John Lyons, SAS Ireland

 

I recently finished a master’s in Business Management, researching the question: can retail banks gain competitive advantage by taking an enterprise-wide approach to data analytics? I interviewed a number of highly knowledgeable people from within the sector and the following core themes emerged.

I noted increasing concern that analytical talent tends to be a small number of specialised individuals – often in somewhat isolated functions – who leave a big knowledge gap if and when they move on to pastures new. With many banks experiencing a pay freeze, and the demand for big data analytics skills set to create 60,000 new jobs in Ireland by 2017, it’s a valid concern.

Part of the issue is that, despite holding a wealth of data across the organisation, most retail banks are still approaching analytics on a departmental or functional basis. Not only does this limit a ‘single view’ across customer, risk, liquidity, etc., it also limits the scope of the analytical talent and prevents them sharing ideas and experience. Many banks are therefore feeling the pressure to find and retain the best talent and struggle to encourage their teams to share their knowledge and working practices across the organisation. An enterprise-wide analytics culture would certainly help with that.

My research also showed a significant opportunity for a more holistic approach to support two major strategic priorities:

• Improving governance and control: to ensure efficient capital management and regulatory compliance.
• Rebuilding customer trust: and enabling growth through deeper customer relationships.

 

I identified 5 analytical processes that would support these priorities, namely:

1. Customer management & retention: by integrating customer, risk and pricing data to give deeper insight.
2. Omni-channel real-time next best action: for managing customer experience and driving targeted personalised sales.
3. Capital management: by integrating risk and financial data to get an enterprise-wide view of risk and up-to-date calculations.
4. Liquidity, asset and liability management: informed by customer behaviour.
5. Product design: based on integrated customer, risk and financial insight blending   customer needs, price elasticity, liquidity and potential profitability of new products.

 

Of course, establishing a holistic approach takes time and would require strong executive leadership to ensure buy-in across the bank. However, once the process is underway, value can quickly be driven in the areas of customer relationship management, visibility of risk, capital calculations, profitability and staff retention.

To expedite enterprise-wide adoption, it would be useful to establish an Enterprise Analytics Centre of Excellence (CoE). A CoE would enable data, skills and insight sharing across the organisation. This would not just help retain and fulfil valuable talent, but it would significantly increase analytical productivity in measurable and demonstrable ways.

Contact me to find out how an analytics CoE could drive competitive advantage in your bank and find out more about SAS solutions for banks. Or you can follow me and my colleagues on Twitter and LinkedIn for more insight around data analytics.