Sorry, you need to enable JavaScript to visit this website.

Financial Services: Managing Traditional to Gen Z via Big data

Financial Services: Managing Traditional to Gen Z via Big data
November 20, 2018

A new generation of users is fast emerging; a customer demographic that is pushing the financial services industry to change itself exponentially at a pace never experienced before. Meet the Gen Z, the first time bankers/users that are now joining the millennials, moving up the value chain as spenders. Both these classes teaming up with the traditional users and demanding their own way of using services.

#Financialservices industry to change itself exponentially at a pace never experienced before. Read the blog to know why. @hclfs

While Gen Z was born with devices in hand, millennials, on the other hand, have assimilated the technology well to now start creating their share of impact on the services. Result: the financial industry is looking to service three entirely different set of user characteristics. Traditional users want trust and are tied between old ways of banking while being exposed to new age financial tools. The millennials are more susceptible to self-service (with agility) and are tied between tools and human advice scenarios for usage. Finally, the Gen Z users are epitomes of instant gratification and take self-service to a new level. They want to not only have self-service once a decision has been made, but even want to have online tools for reaching that decision.

The need is for instant gratification, all services to be available on mobile, and while being mobile, the need for integration with the larger ecosystem, customer experience being at the forefront of judgement rather than quality alone. These are some of the key new-age service traits that are pushing financial services to take to innovation faster to best serve this wide range of customer segmentation.

This translates into four types of needs: competing effectively (against both traditional and technology native), staying relevant to its user base (typically a mix of traditional and new users), catering to scalable services as financial inclusion increases both in scope and access, and finally, remaining transparent and compliant while being agile at the same time.

The only way for them to service a business model that can effectively bear the load of these four pillars is via the effective use of data. There are heaps of data that financial services industry sits on but so far has only been able to make limited use of. For smart financial services to emerge as a winner and service even the most passive clients, it would need to transform itself from a mere source of data to a smart user and integrator of the same. The digital, IoT and other customer experience initiatives can only be built on the back of effective big data usage and that too in a collaborative manner but more importantly, will only give better ROI if data is being managed well.

Effective use of big data techniques can lead to a much better understanding of customer, can provide more localized and personalized services as well as better influence the purchase decisions. At the same time, the insights can also serve as a tool for the interested Gen Z and other customer segmentations to utilize it in a self-service mode and in a real-time scenario. Not only externally, the employee and user communities can also be internally engaged and their performances measured better via big data analytics instead of analyzing mundane, age-old productivity metrics.

Such big data-based hubs would mean better understanding of customer behavior and relationships that would result in better segmentation or effective campaigns or insights that can help organizations effectively cross-sell or up-sell more according to both active and passive customer needs. According to McKinsey’s insights, using big data application for marketing campaigns and decisions could mean a growth of 15-20% in straight productivity benefits. While for traditional customers, it would mean being able to take a better-informed decision about new financial instruments, for Gen Z, it would mean more integrated products and an effective investment strategy.

Internally, big data can effectively cater to a variety of use cases ranging from handling real-time governance and compliance issues to creating various models for predicting, detecting, and preventing fraud. This could be done on the back of integrating customer spending trends, real-time finances, their investments, other activities like current market scenarios, and so on.

Lastly, big data can even help in making operations better. This could mean continuous process improvements, better reporting structures, and finally, some predictability in various optimization initiatives. This would help the organizations to not only reduce cost, attrition, and effectively manage their operations but also increase their topline and bottom-line and stay more relevant to the market. Finally, big data can help analyze customer behaviors and patterns that can play a key role in various security initiatives as well as incidents.

But all this can’t be done without an effective and parallel investment strategy on four key aspects: technology, people, processes, and leadership commitment. The first three are tangible investments while the fourth needs the will to constantly change and support such initiatives. Investment on technology should be such that both legacy and modernized systems are able to serve together the different customer personas. People investment should be in terms of hiring/contracting the best talent and employing training methods that are aligned to one’s role. A T-shaped training model where he/she undergoes deep dive trainings to perform his/her duties better along with basic training and understanding of other roles in the ecosystem, can also be followed. Processes are the backbone of any organization and they need to be in order and followed diligently. An effective investment on the processes would mean effective predictive modelling, reporting, constant feedback, etc. that can ease out the stress caused by peak periods.

Lastly, as the customer experience-centric economy takes shape via APIs, apps, and other engagement channels, it is imperative that the technology investments are done with the aim of making the best use of big data to service the various customer segments. This should be balanced with the fact that for any financial services organization, bottom line, risk mitigation, and compliance should be met at all costs. They have been managing our money well traditionally, but it’s time they learn to manage our assets well and the most important one of them is data.