Banks Challenged in Data Collection for AI Infrastructure Investments
Data security in AI-driven financial services is still an important matter that needs to be developed, in addition the need for increased investment in banks data systems is crucial at this point.
The presence of big data in the financial services industry can revolutionize predictive modeling, enhance risk assessments, and improve customer experiences, but it all needs good data governance.
AI integration in Financial Services
For years, important financial institutions like Citi and JPMorgan Chase have invested in IT systems modernization. Citi invested billions to infrastructure upgrades after 2020 Federal Reserve Board enforcement action highlighted deficiencies in its data and compliance risk management.
CEO Jane Fraser explained that these upgrades, which included migrating workloads to private cloud infrastructure, reversed years of underinvestment and improved data management.
JPMorgan Chase also made data management in financial services a priority. The bank launched a suite of AI-powered tools this year, making it an early mover in AI adoption for the banking industry, per the Evident AI Index released in October.
Data security in AI-driven financial services is growing with the financial sector. According to Digital Realty, nearly two-thirds of financial services companies have IT infrastructure spread across up to 10 global locations. More than 75% of those firms plan to add more AI in banking/ financial services, as many as five more in the next two years.
Despite this global push for AI applications in financial services, many institutions still have their own struggles. More than 60% of respondents to Digital Realty’s study said they lacked the infrastructure in place in key locations to accomplish key AI objectives.
On the other hand, the huge amount of data within banks forms a challenge itself, called Data Silos. Digital Realty indicates that as data accumulates, it brings more applications and services, forming a “virtual cycle” that complicates its movement.
A recent study from Publicis Sapient, a technology consulting firm, states that approximately one-third of senior banking executives indicated that budget was the major inhibitor in modernizing AI and data analytics in banking and financial services.
The need for increased data security in AI-driven financial services is critical. Digital Realty’s survey revealed that 56% of IT leaders in financial services firms felt their organizations had not invested adequately in data systems and analytic tools.
Without data governance in financial services, banks have limited ability to fully exploit AI technologies and other emerging tools.
Future of Data Governance in Financial Services
As financial institutions are improving their IR infrastructure, overcoming the data silos challenges for effective investments in analytical tools will be critically important to their success. Solving these data security issues in AI-driven financial services issues will place banks in an enviable position to unleash the full power of their information, better risk management, and improve customer experiences.
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