Banks are investing in new technologies such as machine learning and artificial intelligence, blockchain and digital identity systems as key drivers to transform the financial and retail banking sector.
AI is the epicentre of this transformation, particularly in identifying risks and eliminating fraud. AI adoption in the banking and financial services sector is becoming more prevalent, and necessary in risk management processes.
Arguably, the most important application of AI in the financial services sector is risk management to spot potentially fraudulent activities and prevent data theft and loss. Machine learning adoption contributes to better handling and analysis of unstructured data, which can save time and money, leading to better identification of risk concerns, and boosting revenue.
Also, the implementation of AI in banking risk management can significantly reduce operational, regulatory and compliance costs, which consume a major piece of corporate budgets. It can also provide reliable credit scorings for credit decision makers, and contribute to generating more value for the customer, as it gives access to consumers’ behaviour and needs.
Our SHEQX (Safety, Health, Environment and Quality) management solution, part of the XGRC product range, is an integrated management system that aggregates SHEQ data in a single, auditable database, to manage analysis and reporting effectively.
In financial services and banking, AI developments are not just about automation, process efficiency and cost-cutting. New intelligence models are changing business strategies, pushing new data initiatives and visualisation tools for services ranging from trading to wealth management.
The relentless competition between traditional banks and agile FinTechs and digital-only banks, which attract customers with state-of-the-art digital services, is only going to deepen.
Extracting additional value and intelligence from increasing big data is becoming a competitive advantage in the industry, which poses risk challenges in securing the information with high-level encryption.
The key drivers transforming retail banking and financial service companies, big data and analytics, are now requirements for an agile architecture to support digital ecosystems, enforced by enterprise-level security.
As customers become more digital and tech-savvy, the end-to-end digital transformation of banks and financial services is necessary to leverage the latest technologies and innovative approaches in a highly competitive market.
Enterprise Risk Management (ERM), part of the XGRC Software product range, enables the methods and processes to achieve your strategic objectives.