With more data available than ever before, banks are facing unprecedented pressure – both internally and externally – for granular data and sophisticated analytics.
Sonia Dribek, Associate Partner, Management Consulting – KPMG Luxembourg
With more data available than ever before, banks are facing unprecedented pressure – both internally and externally – for granular data and sophisticated analytics. Success has long required speed and accuracy, but today’s complex ﬁnancial markets demand these attributes at levels beyond what humans can provide. Hence, the rise of artiﬁcial intelligence (AI). By Sonia Dribek, Paru dans l’ITnation mag de Juin 2017
AI’s value is that it can process multiple datasets concurrently and reliably. Unlike humans, AI engines are, if programmed well, unbiased; plus, machine learning means that systems improve over time. Paired with human intelligence, AI systems can learn even faster, resulting in a unique synergy of competences. BCBS 239 is a regulation focused on data governance and quality as well as on creating sustainable IT-architecture platforms in banks. Merely complying with it means huge investments alongside great efforts to change internal mindsets towards a “know-your-data” culture.
In reality, this regulation is a chance to compete by investing in sustainable data management and IT. Additionally, the Supervisory Review and Evaluation Process (SREP) requires banks to abolish the silo approach of their legacy systems, and instead take a holistic approach to managing liquidity, risks and business. This requires data that is veritable and versatile. Thus, AI is a natural desideratum: it provides sophisticated modelling, scenario analysis and predictive analysis. With it, banks could meet regulators’ demands by giving them more insight on risks to ﬁnancial stability, while honing the efﬁciency, effectiveness and results of risk and ﬁnance processes.
Indeed, increasing pressure by regulations like PSD2 will more or less force banks to use AI to manage their data. Robotics will surely become vital in ensuring security, mitigating risks and managing avalanches of data ﬂows. Banks are already eyeing RegTech tools and partnerships, seeking efﬁcient compliance solutions to current regulation; the proactive ones are looking ahead to AI. Key to consider is that bringing AI into a low-data-quality environment will do more harm than good, and that external data ownership issues may need solving.
Currently, global systemic banks are implementing BCBS 239. Many will ultimately succeed in turning a regulatory burden into a value-adding opportunity. However, some small and medium-sized banks hesitating to evolve, perhaps not seeing the value of doing so, might miss the opportunity.