Analytics apps allow banks to adapt faster to regulatory changes, cost reduction—SAS
Leading technology group, SAS Risk & Finance Analytics has carried out a Roadshow in Lagos, underscoring the fact that for banks to survive form the competitive advantage of FinTech regime, and be innovative on risk assessments during new product development in serving their customers, analytics applications are a must.
Explaining more during the show, the group averred that subscribing to Analytics will help banks reduce compliance costs, improve efficiency and effectiveness in risk management processes.
According to the Senior Business Solutions Manager, Pre-Sales Risk Practice, SAS, Charles Nyamuzinga 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.
He argued that “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”.
While stressing that just like banks all over the world, banks in Africa should ordinarily be compliant with the new IFRS 9 accounting standard, which changes the way they calculate expected credit loss, he made it clear that “There is also 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.”
In his further submission, Nyamuzinga revealed that 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.
Continuing, he averred that “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.”
Besides, SAS Sales Manager, West Africa, Babalola Oladokun, noted that “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”.
He said “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 whether banks like it or not.
