Data is the new oil – the most valuable resource for today’s organisations.
Making sense of the large swathe of data that organisations possess will differentiate the winners vs. laggards of the future. Digital technologies like cloud and Al are playing a key role in helping organisations harness insights from the data. The Finance function of the future will be relied upon to leverage the suite of digital transformation technologies to drive process, efficiencies, product development and innovation within Finance.
Cloud has had a steady upswing in its adoption across the industry with all the potential to transform the banking organisations and the Finance function.
Cloud technologies are best seen as strategic enablers that will make Finance a simpler and more streamlined operation and carry Finance functions through the next chapter of digitisation.
Given existing stress testing requirements and the recently adopted expected credit loss (ECL) model under IFRS9, stress testing and IFRS9 reporting will put greater pressure on regulatory reporting and capital planning functions of Finance.
Cloud technology provides the opportunity for unlocking the potential of two key drivers: data and the deployment of AI technologies.
As Banks have grown in size and scale, the prevalent solution to manage data has been the ‘extract, transform, load’ (ETL) mechanism whereby data is extracted from multiple sources, batched, enriched and cleaned (transformed), and then loaded into data warehouses for use. Much of this data is historical due to delays and
data going through prolonged periods of development before use.
A single repository for storing and organising data, data lakes ingest both structured and unstructured data from internal and external data sources. Data lakes enable rapid process outputs and greater accuracy in activities. Such as
time-sensitive credit analysis and financial planning and forecasting by capturing real time operating, customer and market data.
With a unified data source, machine learning can be used specific to IFRS9 in forecasting; classifying the amount of ECL and interest income of existing financial assets to recognise based on key data sets, as well as unstructured data from sources such as calls with customers relating to their accounts / transactions. This will result in more accurate reporting of provisions, and support data driven future decision making to fuel growth and profitability across other functions within the bank.
Furthermore, machine learning algorithms can be used to test key portfolio risk drivers across credit, market and business portfolios by identifying bias associated with variable selection. This will result in more accurate models being used by Finance and an overall more transparent process.
KPMG have recently launched a cloud based managed analytics service provider solution to help financial institutions in Asia in achieving compliance with IFRS9 requirements, driving down total cost of ownership by 60% compared with in-house operation. Built around a ‘risk as a service’ subscription model with KPMG IFRS9 SMEs as part of the offering, the solution draws data from source systems and uploads this onto a secure KPMG cloud, hosted by Microsoft Azure, through a robust security layer.
The KPMG solution has the ability to produce a variety of regulatory reporting outputs in standardised templates, as well as leveraging KPMG SME support to provide insights and drive predictive scenario modelling. The offering highlights the reliability, robustness and vast potential of end-to-end cloud stacks, especially when underpinned by appropriate governance frameworks.
The cloud brings huge potential to the future of the Finance function. However, implementing cloud solutions as part of tactical technological solutions without marrying them to enterprise wide strategic business objectives will leave organisations failing to derive true value from these investments.
Investing time and resources into data architecture, incorporating cloud at the heart of digital strategy and effectively designing integration of cloud systems with existing infrastructures are important determinants to driving true business value from investment in cloud technologies.
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