By CHARLES NYAMUZINGA
AS one of the most regulated industries in the world, banks are under pressure to not only comply with constantly changing regulations but also to modernise their systems, so that they can reduce compliance costs, improve efficiency and effectiveness in risk management processes, stay competitive in the age of the FinTech, and be innovative on risk assessments during new product development, to better serve their customers.
Yet banks in Africa face additional challenges, including risk analytics skills shortages, data management issues and integrating their risk management and finance processes across the enterprise. But, on the positive side, they have started considering technology as a way of eliminating these challenges and have access to new streams of data that are also helping to advance the financial inclusion mandate.
As with banks all over the world, banks in Africa should already be compliant with the new IFRS 9 accounting standard, which changes the way they calculate expected credit losses.
And if they haven’t already, they need to start thinking about the new ‘Basel IV’ framework, which impacts on how banks calculate their risk weighted assets and the amount of capital they need to offset those risks.
Another source of regulatory pressure banks are grappling, with are the requirements, questions and challenges related to conducting stress tests, as the regulators become more stringent on stress testing processes.
If either of these calculations, which are based on risk models, are incorrect, banks will not only have to worry about non-compliance penalties but also the capital shortfalls, reputational impact and negative impact on earnings performance.
There’s a good chance that banks in Africa could get this wrong if they use disparate and fragmented systems for data management, model building and implementation and reporting – which is often the case – or if they try to do the computations manually.
The biggest causes of incorrect modelling are data management and quality issues and skills shortages. Banks have to obtain and analyse enormous amounts of detailed data, for example. And, to comply with IFRS 9, banks must look at millions of customers with hundreds of data points.
Typically, banks in Africa draw data from a number of disparate systems, thus impacting on the quality of the data used. For example, the credit department may come up with different figures to the risk department, making it difficult to know which data to trust.
If a bank miscalculates an individual’s credit score, for example, it could end up granting a loan to someone who can’t afford to repay it, which has implications for IFRS 9 expected credit loss calculations. And If the bank does not have enough capital on hand to offset the risk of non-payment of that loan, it will run into Basel Capital requirements compliance issues.
Data gathering and manipulation from disparate data sources wastes time and resources that banks could have used to develop new products and find more convenient ways to serve their customers – something their competitors in the FinTech space are very good at.
FinTechs are using entirely new data streams to make instant, value-adding decisions for customers. For example, they’re basing their decisions to grant a loan to someone who doesn’t have a bank account or credit history on how often that person recharges their mobile phone – an innovative way to give the unbanked population access to finance.
Another problem which has significant implications, is the way risk models are managed. To be more effective, development of risk models and deployment require an end-to-end technology solution that includes data management, model development and deployment, model risk management and the ability to integrate risk analytics across the enterprise.
Combining data and skills confidence with integrated technology
Accurate modelling and calculations is critical in credit scoring, estimation of credit losses, calculation of risk weighted assets and stress testing. It depends on all departments in the bank having access to the same clean, accurate data and a flexible integrated risk management platform. It also depends on having access to data analytics skills, which is another common challenge among African banks.
Yet, with solutions like SAS’s Risk and Finance Platform, none of these challenges are major issues anymore. Bundled with data management, risk calculations, scenario management and reporting capabilities, SAS solutions are easy to use through a simple drag-and-drop or point-and-click interface. From a single platform, Risk and Finance departments can access the same datasets, populated with data that has been scrubbed, scrutinised and validated, perform calculations and produce reports, so that executives can make confident business decisions.
Banks can trust that the information they’re using to build their risk and credit models is reliable and that the reports they generate are automatically compliant with regulatory requirements and can easily adapt to regulatory changes as and when they happen.
Banks need to modernise and integrate their risk management systems if they hope to stay relevant in a rapidly changing market. Compliance is no longer their single biggest consideration. Banks should also take into account cost reductions as well as high performance, efficiency and governance issues in risk and compliance processes. They need to adopt advanced analytics solutions that are multi-tenancy in terms of risk management use cases and cover the entire risk management process, from data management, risk analytics and reporting, to meeting governance and controls requirements.
Their technology should help them quickly adapt to regulatory changes, promote enterprise-wide collaboration in risk management activities to enhance risk management strategies, uncover new revenue streams, manage costs and improve their customer service.
CHARLES NYAMUZINGA is Senior Business Solutions Manager, Pre-Sales Risk Practice SEMEA, SAS
– CAJ News
By CHARLES NYAMUZINGA