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Home » Why aren’t finance teams using AI to leverage real-time data?
AI in Finance

Why aren’t finance teams using AI to leverage real-time data?

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Artificial intelligence and real-time data are poised to disrupt financial services operations, according to a new industry study. researchconducted by ActiveOps, found that 81-84% of operations leaders believe that real-time data enabled by AI would significantly improve key areas such as customer experience, employee engagement, operational performance and decision-making.

As institutions grapple with outdated systems and data challenges, this widespread optimism signals a potential turning point for the sector.

The financial services industry has long recognized the importance of data-driven decision-making. However, the ActiveOps study, which surveyed more than 850 COOs, CFOs and COOs across seven countries, reveals a stark reality: many organizations are struggling to effectively harness the power of their data.

Despite the recognized importance of data, 91% of respondents say it takes significant effort to extract insights from their operational data. Even more alarming, 94% of them are not using real-time data in their operations.

This data gap has a tangible impact on decision-making processes: 97% of executives face difficulties in making operational decisions. Many of them base their critical decisions on data that is several weeks or even months old, which potentially compromises the accuracy and speed of their strategies.

The promise of AI

Amid these challenges, there is a palpable sense of optimism about AI’s potential to transform operations. The 81-84% who believe in the transformative power of real-time data generated by AI foresee improvements in multiple facets of their operations:

  1. Customer experience: Real-time data could enable more personalized and responsive service.
  2. Employee engagement: AI could streamline processes, reduce tedious tasks and allow staff to focus on higher value-added activities.
  3. Operational performance: AI-driven insights could identify inefficiencies and optimize processes in real-time.
  4. Decision making: Access to real-time data processed by AI could support more informed and faster decisions.

However, AI adoption in financial services operations is still in its early stages. The study found that 49% of organizations are just beginning to use AI or are not using it at all. Only 15% report using AI at an advanced level, indicating significant room for growth and improvement across the industry.

The Path to AI Transformation

As financial services leaders look to the future, they anticipate several key benefits from adopting AI:

  1. Enhanced cybersecurity control (39% of respondents)
  2. Improved real-time decision making (39%)
  3. Access to more in-depth information (35%)

However, the path to AI transformation is not without its challenges. As many as 98% of respondents face challenges in adopting AI. Key concerns include:

  1. Job displacement (37%)
  2. Ethical considerations (36%)
  3. Lack of infrastructure (29%)

These figures highlight the need for a balanced approach to AI implementation that takes into account both technological and human factors.

The Future of AI-Driven Operations

Despite the challenges, AI’s involvement in operations is growing. 36% of executives say they want AI to take action based on predictive insights, while 40% want AI to provide suggestions based on those insights. This shift toward more autonomous AI systems represents a significant evolution in how financial services operations could operate in the near future.

However, the key to harnessing AI’s potential lies in data readiness. Organizations must prioritize developing a robust data infrastructure and ensuring data quality to take full advantage of AI’s capabilities. This may involve investing in data management systems, training staff, and developing clear data governance policies.

Why now?

For CFOs and senior executives, the message is clear: Investing in AI and data infrastructure is not just about keeping pace with technology trends, but about positioning your organization for future success.

Those who successfully make this transition will likely find themselves at the forefront of the industry, while those who lag behind will struggle to catch up. As you consider the future of your organization, ask yourself: Are you ready to harness the power of real-time data generated by AI?

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