Using Predictive Analytics to Drive Competitive Advantage in Financial Services

Like most industries and sectors, financial services organizations are fully aware of the positive impact of better business insight and market understanding. As data volumes continue to grow and diversify, being able to make greater use of the information organizations are creating and capturing enhances competitive advantage. 

A  recent SAP survey revealed that 41% of financial services organizations state that predictive analytics is more about minimizing risk than exploiting opportunities, with bank fraud detection at the top of the list of list of valuable outcomes. While minimizing risk is obviously very important for these organizations, financial services firms now need to think beyond this and understand the wider benefits this technology can bring in terms of providing a better customer experience, driving opportunities and increasing revenue in a highly competitive market.

The industry is taking steps towards utilizing predictive analytics technology to do just that.

Improving financial services customer service through predictive analytics

Financial events in our recent history, including the crisis in 2008, have led people to lose faith in the industry as a whole, and trust is at an all-time low. This in turn has resulted in a lack of loyalty among customers, further driven by the ability to switch banks more easily than ever before. New market entrants offer competition and new services that appeal to a younger, more demanding generation that want instant access to information and a better customer experience. As a result, these new organizations have seen a rise in demand for their current accounting products, pressuring traditional banks to focus on customers.

As this lack of trust and loyalty combines with the greater financial tensions in banks today, customer-centricity becomes more important. In order to attract and retain customers in today’s environment, financial services organizations are challenging traditional approaches and using technology fundamentally change their existing operating models. Seventy-three percent of financial service organizations surveyed agreed that predictive analytics would help them to make better product recommendations and offers to their customers.

We are seeing this transition take place right now. Banks, for example, currently tend to offer standard products and services and are unable to effectively tailor these for individual customers. They are beginning to use analytics to get a single view of their customers across all product lines, which enables them to provide customer-centric products and services targeted on individual and group behaviors. These banks can more accurately anticipate customers’ financial needs and improve service; one example is a bank proactively offering a savings account bundled with a mortgage offer when a couple gets married. 

Using the right tools can help identify new opportunity in big data

In a competitive market, making speculative decisions is not enough. In order to really differentiate, it’s important to think about the future, and using historical data to predict market trends can help ensure decisions are made that best suit the business in the long-term.

For financial services organizations looking to drive new revenue opportunities, it comes back to being more customer-centric in their approach. These organizations have a huge amount of data on their customers but most are not currently using it to its maximum effect. Among other uses, a comprehensive customer database, combined with advanced analytics, will allow organizations to spot trends, identify cohorts, and micro-target discrete populations.

Regardless of the benefits, there is still reluctance among financial services firms to adopt new predictive analytics technologies. For many, this occurs where data volumes are too high (57%) and across disparate systems (45%), specialist skills are needed (55%), and ROI is unknown (35%).

As with many new technologies, these concerns are not uncommon. However, the opportunity to obtain competitive advantage through use of the right tools can result in increased customer loyalty and the ability to identify new opportunities cannot be ignored.

We are operating in a data-driven world where advanced predictive analytics needs to sit at the core of the business function if banks and financial services organizations want to remain competitive. As well as helping to minimize risk, it provides the opportunity for organizations to identify new opportunities, differentiate themselves by allowing them to be much more targeted in their product offerings and increase loyalty by improving customer service and satisfaction. As more and more organizations wake up to the benefits of predictive analytics the race is now on to harness data faster and more effectively than competitors.

Image courtesy of Shutterstock.

About the author: 

James Fisher is vice president of marketing for analytics solutions at SAP and has over 16 years of experience in analytics, performance management and finance software and consulting businesses.  He previously held marketing and consulting roles at BusinessObjects, Cartesis, PricewaterhouseCoopers and KPMG.