Crafting the path for a real Digital Transformation for Banks

Days ago talking with friends and after a short survey, I could confirm something that I just was wondering, in the Digital Transformation (DX) adventure it's easy to find financial institutions that believe in DX and have its roadmap, others that have been watching and have some steps addressed to change things but are misunderstanding transformation with filling themselves with a bunch of systems and applications, others that are aware of this change but do not know where to start, others who have not done anything. To cut short, the scale is full of representatives at any level.

One thing that attracted my attention is the majority is talking about FinTechs, FinTechs up, FinTechs down, in the sky, at the gym, FinTechs (FTs) everywhere and do not see that the main threat are themselves.  First, Banks should learn to survive and live with those alternate "money and financial disruptors", never ever better than today to say: If you cannot defeat them, be part of them".

Let's be clear,  there's a bunch of FT flourishing everywhere,  giant technology companies like Apple or Google with humongous numbers of data form credit card holders and users, PayPal running wild on money transfers,  in Asia the social networks allow for money transfers, Facebook and WhatsApp can take the hell upside down if they provide with money transfers and personal loans. Let's face it, FinTechs are the face of simplicity, that's why they are the best alternative in disruptive solutions.

But, DX it is not just fighting against FTs, it is about simplification, it is about do more with less effort. Unfortunately, less effort means less headcount in many situations. Here, it is important to plan with people in mind. Your workforce knowledge can lead to a bright future with better business services and lines. Who can tell what is wrong or right? Your people, who else, so why do you will fire them?

The roadmap definition is not enough, there's a lot to take in account:

- Customer
- Processes
- Key Services
- Technology
- Security
- Key indicators
- Follow up dashboards
- Strategy

Nevertheless, the main pillars to define a real  DT roadmap are:

Customer on board	Strategy	Technology	Operations	Culture. Organization. People
Aquisition	Brand Management	Applications	Agile Change Management	Culture
Customer Experience	Ecosystem Management	Connectivity	Automatic Resource Management	Leadership and Governance
Behavior Knowledge	Investment and Financing	Data and Analytics	Integrated Services Management	Organizational Talent Design Management
Trust and Perception	Market and customers	Distribution Gonvernance	Understanding and Real Time Analysis	Workforce enablement
	Portfolio, Concept and Innovation	Networking	Adaptive and Intelligent process management
	Stakeholders Management	Security	Standards' Automation and Governance
	Strategic Management	Architecture

There are advices, yes of course, a lot. But every company is quite different. So, it is mandatory to have master advisors at hand. Take care when dealing with technologies like Blockchain or Kubernets implementations (to name a couple) , technical resources are scarce and you need good ones.

To finish this post, take a look at BBVA, they have an innovation pool, good to check for Apps ideas for your bank. Take a look, reinvent your services, get better ones.

Big Data and customers’ retention

As any other business, banking relies heavily on its customers. Is it possible to predict if any customer is about to leave? Well, starting from the fact that keeping customers under your umbrella costs less than acquiring new ones we are in a good path. Acquiring new customers cost from 5 to 15 times more than retaining current ones.

Let´s suppose we have Loui who all Mondays goes to the ATM for his customary $100, all of a sudden Loui transactions begin to be scarce or inexistent. Loui is about to leave but we do not know why. And the worst is that we barely notice about Loui among all our customers. How important is to predict customers who move off from our bank? Which kind of data do we need to analyze?

Our mission is to predict customer’s departure before it actually happens to retain him. Data that comes to our help include: number of contracted products, savings evolution or account movement, occupation, claims, demographic data, etc.

Other source is the one that the bank has collected from lost customers, who had left the bank. Behavioral patterns are there.

Moreover, there are different kind of “break ups” to design and build maps of departure, profile of customers who leave, most common channels that originate such response from our customers, geographic zones, products, and related data.  

What do we obtain from such analysis?

1.       To   know which customers’ segment should be care and kept.

2.       Plans and strategies to respond before customer relinquishment. We can know with anticipation when, who and why.

3.       Increase customer’s satisfaction and fidelity by knowing his needs in a better way.  consumption

Data	How to analyze
·         External Sources that have information about demographics, employment status and current personal status. ·         Social Networks	·         Fusion and analysis of structured and unstructured data ·         Interactive data visualization
·         Customer value that it is used as index of acquiring customers who potentially can leave
·         Statistical external sources with expenditures/payments information.