Modernising banking analytics and financial services in Africa
Data is only data - it has no inherent value – the latter is only unlocked once improved decisions are made from the data.Moreover, to acquire that insight you will need to analyse the data. Once the data pipeline and availability are both in place, there is now a platform from which to launch and accelerate value.It is now time to consider the analytics platform and the people who will provide the insights and actions required to unlock the value.
Through the deployment of the right data analytics solution, staff at every level, in every department, can uncover insights that drive competitive edge. By unpacking key performance indicators (KPIs) financial services organisations can acquire transparency with regards to trends, concentrations, and anomalies, making it possible to open a door to countless new opportunities – whilst at the same time mitigating emerging risks.
When it comes to the analytics to be performed on top of the ready data, the following insights should form the foundation of your strategy and then be made available to your BI professionals and business users in a flexible and user-friendly platform.
Customer & Product Profitability: Banks need to know which customers are profitable and which are not.They also need to know which products (accounts) and services are profitable and which are not.
Segmentation, Attrition and Retention: It’s important for banks to know which customers are likely to leave the bank or cancel a product, account, or service. They use a method called segmentation to group their customers into different risk groups and then they can focus on those customers that they wish to retain.
Customer Facing Portals: More banks today are delivering portals to their customers with embedded data and analytics. These portals allow customers to have a complete picture of their products, services, transactions, and much more.Banks like these solutions because they drive added value for their customers and encourage client loyalty.
Finance, Regulatory & Compliance: Staff expenses analysis required all the way through to more complicated analytics regarding budgeting and forecasting versus actual expenditure.Banks and financial services companies are required to meet the complex numerical and reporting regulations including Basel II, MiFID II, and the Payment Services Directive.
Operations and Call Centre Management: It is necessary to be able to analyse the effectiveness of call centre and back-office operations. The data from telephony systems can be analysed together with data from banks’ core transaction processing systems.This allows call centre managers to have good visibility of the calls being received, the number of calls being lost, the types of calls and the skills required to handle and process the calls.
Branch Performance: Monitor and improvement of the effectiveness of their branch network within banks is always a goal, this includes monitoring the number of customers visiting the branch,transactions performed, and the products sold.Often a bank will have hundreds or thousands of branches and these all need facilities management, an assets catalogue, and often a database of when the branch was refurbished and modernised.
Digital Channel Performance: As organisations migrate to online; mobile banking and insurance platforms, it is crucial to carefully monitor the migration practices, and preferences. Customer centricity is key and data essential if one is to anticipate and cater for changing financial needs.Analytics of the performance and usage of digital channels augments sales and channel data which in turn ensures customer needs are met.
Data and technology make all this possible but ultimately, people make it happen.
The last, most importantly, and probably most neglected, part of the FSI data value chain is the people pillar. Financial services is one of the most data driven industries in the world and most of the workers are now considered to be knowledge workers.However, the fact remains that they were not formally trained to work with, read, analyse, and communicate with data.
In fact,a recent study of 7,377 respondents revealed that only 25% of decision makers considered themselves to be data literate, while only 21% of the new entrants into the workplace were actually data literate.
The C suite did significantly better at 32% but that still leaves most key staff not having the requisite skills to work with the data and technology that we put in front of them to do their work in a digital world.This is nothing short of a crisis and is a significant inhibitor to acquiring a return on your data investment and ultimately the expected value from data.
The data literacy crisis can be addressed by firstly performing a scientific assessment to understand the current state of the matter across the key staff you would expect to partner with to glean value from the investment i.e., business users of data. Only then can you address the gaps in a structured and meaningful way.
While data is the foundation of this new economy transforming it into analytics ready data and analytics, is required to find the insights which in turn drive actions that ultimately transform businesses.For organisations to cash in on the tremendous transformative power of data, the data platforms and analytics engines need to be modernised to keep up with recent developments and business staff need to be enabled to effectively read, work with, analyse and communicate with data.