By: Colin Dean, UK Account Director, Clarabridge

 

Customers are at the heart of any business and the financial services sector is no different. There are however, specific compliance and regulatory rules that must be applied, requiring a balancing act between satisfying the evolving demands of customers and at the same time, adhering to rules and cost pressures.

The experience provided to customers in the Financial sector is increasingly becoming the critical factor for the success, or indeed failure, for the businesses which serve them. Never has there been more choice with whom to transact with and frighteningly, change allegiance to.

As well as delivering a better customer experience, evidence shows that customer-centric businesses achieve better shareholder returns and faster growth. A 2016 Forrester report supports this, giving evidence across multiple industries that improved customer experience drives revenue growth by growing loyalty.  They find that each 1% improvement in Customer Experience index equates to an annual incremental revenue increase per customer, of an average £9 throughout the financial sector. Multiply that by the number of customers served and it equates to a healthy annual increase.

Clearly, customer needs are driving these demands for change. Disruptive challengers are entering the market, maximising technological advances, and targeting and meeting millennials requirements. The demands do not end there. Further additional complexity is added via the still significant number of customers requiring traditional access.

The challenge for businesses is therefore, how to respond to the demands of the varying customer segments, adhere and meet regulatory and compliance requirements, whilst reducing the cost to serve and generate profits. Ultimately, they need to create a fully sustainable and operational business value model with these requirements in mind.

 

Breaking down silos for business benefit

Meeting risk, regulatory and compliance requirements, combined with the need for operational transparency, is a necessary yet significant expense for today’s financial institutions.  In the past, risk, regulatory and compliance teams have not traditionally collaborated with the commercial side of the business. This developed natural divisions and a siloed approach, negating the reuse of the data within the organisation. This historic restrictive practice is nullifying the business value that could be gained from the wealth of insight retained in the regulative part of the organisation.

Understandably, leading financial institutions are now exploring the strategic possibilities of using the vast levels of transactional data in order to drive operational efficiencies, lower costs and increase revenues.

Consider the following: Regulatory feedback from the compliance department of a financial institution could be analysed to identify any suspicious transaction patterns, or complaint feedback could be reviewed to ensure transparency in all transactions. These examples help to demonstrate to the regulators that the accounts were compliant with anti-money-laundering (AML) regulations and that operational transparency was fully maintained. In addition, insights from customer interactions and transactions can be used to improve how target products, such as insurance and targeted financial offers, are marketed to specific customer segments.

 

An operationally-viable approach

Of course, in order to break down silos, analyse complaints, regulatory, transaction and other customer data, and use these insights across the business, we are dealing with a high and ever-increasing volume of data. Manually analysing all this data to draw out the insights that can inform business decisions and drive business value are totally cost prohibitive, not to mention impossible to scale across the business. Operationally, technology is now able to automate and facilitate this approach. High volumes of omni-source data, even in multiple languages, can be quickly analysed using the latest text analytics and Natural Language Processing (NLP) techniques.

The subsequent results provide a clear understanding of context, insight, and the sentiment expressed. Fully automated C-Level, operational and analytical reports can be easily produced in near real time. Alerts based on specific business value can also be triggered, enabling confident business decisions to be made based on solid data-led facts.

Integrating risk, regulatory, and compliance information with business operations can be implemented as part of an incremental approach to sharing data and analytical results across the whole organisation. This in turn, becomes a powerful component in the creation of a fully sustainable and operational business value model.