The migration to a digital banking world is expected to be a rough drive and likely to lead to further fragmentation in financial service markets. This digitization of financial services will be accompanied by a significant shift in power and influence from existing financial services providers to other intermediaries and customers.
How do banks evolve to meet the emerging challenges and expand their role beyond traditional financial activities? How do they fit into the ‘brave new world’ of Banking-as-a-Service (BaaS) and partner with banking aggregators to deliver personalized services to customers in real-time based on what they want and not what can be offered? The time has come for a new wave of Automation – quite different from the heady days of bank mechanization or computerization. BI and Analytics will bring in the next wave of differentiation. There will be increasing use of API-based aggregator ecosystem where each partner of the conglomerate performs optimally based upon inherent core competencies to deliver value and enhanced customer experience (CX) and generate and optimize revenues for the banks.
An evolution like this requires acquiring and mastering new tools, developing robust technical foundations, and devising new strategies for business growth.
The roadmap for adoption and mastering of new tools is expected to follow the following implementation strategy for a successful adaption to the new business models:
MEDIUM TERM: TECHNOLOGY ADOPTION
In the medium term, the following technologies must be adopted:
A customer omni channel experience platform (consistent, cross-channel, etc.).
Marketing and CRM based on advanced analytics and leveraging existing and newly available customer data for targeted offerings.
Open platforms and APIs to participate in an extended ecosystem, to deliver services and to provide an offering beyond traditional financial products.
A social and collaborative platform, leveraging communities (either existing or bank-created) to interact, exchange information, advise, check peer opinions, use the community’s knowledge, etc.
This enables banks to gradually step into new business models, co-operate with new players, and adapt to new customer expectations and behavior. In this way, banks can achieve significant results in securing market share and growing their business.
LONGER TERM: TRANSFORMATION PROGRAM
From a longer term perspective, a deeper transformation of a bank’s culture and organization is required to achieve the full potential of digitization. In particular, mastery will be achieved by those who make full use of data to drive their business and marketing strategies and pursue innovation beyond existing banking practices.
Main focus areas include talent acquisition, culture and IT transformation.
Organizations are struggling to find the right talent in areas that cannot be automated. Such areas include digital skills like those of artificial-intelligence programmers or data scientists, and of digital marketers and strategists who can think creatively about new business designs.
In the digital age, a bank will put innovation at its core, which will drive the development of new services and offers and create competitive advantages.
A business transformation must be supported by a corresponding IT transformation.
Investment prioritization should thus establish a robust technical foundation for digitization, including customer communication solutions, cyber security, collaboration tools, storage technologies, analytics, modern core systems, and risk management.
As such, the transformation program should create the agility, flexibility and openness necessary to thrive in the digital world. This can be achieved by decoupling the production, offering, and customer interaction layers. These layers can then feed and build on a data core (comprising customer data but also data from the entire ecosystem). In the digital age, data will be at the heart of every business activity, and a competitive advantage in its own right.
Banks are in various transient stages of mechanized to digital (internet and mobile) to a truly digital model (Robotics, Analytics and AI). AI and Machine Learning algorithms are increasingly used to self-learn and predict outcomes to enhance the customer experience. Digital is a journey, not a destination. Banks like other businesses must continuously and relentlessly evolve at higher velocities to meet the challenges of the digital age.