As financial institutions worldwide face multiple challenges – from tight regulatory compliance to emerging AI opportunities and challenges, the need for operational visibility around data with precision, speed, and expertise is key.

For example, the EU AI Act represents a significant legal stake in the ground, requiring the use of AI technologies to adhere to principles of justice, transparency, and accountability. This law, along with growing public and government pressure to take on more responsibility in adopting technology, will trigger industry-changing shifts in the world of finance.

It’s important for financial services IT and data leaders to take stock of their ability to effectively manage what is happening in and around the industry, from increasing data breach risks, competition pressures posed by disruptive fintech start-ups, and the demand for personalized and trustworthy AI apps. These are some of the issues we’ll discuss in a two-part series, detailing the challenges and how the Pentaho+ platform is well-positioned to support financial institutions in their efforts to manage complexity, make data-based decisions, and achieve compliance and visibility in their business.

Regulatory Crackdowns on Algorithmic Bias

In 2023, a U.S. bank was fined $25.9 million for applying a credit-scoring AI model that rejected minority applicants. Post-event research indicated a lack of bias-checking in the training data and a lack of transparency in decision-making.

Challenges:

• Bias Prediction: AI models often overestimate the historical bias in data and will produce biased decisions. Also, with data models being designed by humans, there needs to be a way to check data to avoid unconscious bias that might creep in with data selection processes.
• Accountability: Regulators expect to see evidence of bias mitigation and fairness evaluations. This includes safeguards across the board, from how the model was designed to the data that the models are trained on, and the new data sources that the models are being supported by in ongoing analysis.

How Pentaho Helps:

• Automatic Bias Audit: Pentaho Plus uses machine learning algorithms to continually scan datasets for bias and report anomalies in real-time.
• Data Lineage Tracking: All data sources, transformations, and decision points are traced to enable regulators to have comprehensive reporting.
• Easily Explainable AI Dashboards: Clients and auditors can visualize decision pathways for transparency and confidence.

Potential Industry Shift: Let’s say a bank can not only conform but actively promote its AI fairness solutions. Displaying a fair lending model provides a competitive edge and appeals to more socially aware customers.

Banking’s Rising Systemic Risk

The failure of a few mid-sized banks in 2023  exposed real flaws in risk modeling and stress-testing techniques. Supervisors are pushing for more accurate, faster reporting of risk exposure to ward off failures in the system.

Challenges:

• Data Separation: Risk data is often separated into silos, which can be challenging to map holistically. There is also the issue of how to blend structured and unstructured data to gain a clearer and more accurate picture of risk.
• Rapidity and Precision: Real-time reporting and predictive capabilities are crucial to find the weakness. Many banks still rely on manual processes, introducing time lags and errors that can weaken risk analysis and create the conditions for failures.

How Pentaho Helps:

• Unified Risk Data Model: Pentaho integrates disparate data, including structured, semi-structured, and unstructured data, into one holistic understanding of institutional risk.
• Predictive Analytics: With real-time simulations, firms can simulate stress conditions and predict the effects on liquidity and solvency.
• Real-Time Reporting: Automated, real-time regulatory reports ensure teams can meet evolving requirements.

Potential Industry Shift: What if banks leveraged real-time risk dashboards with regulators and stakeholders? This level of transparency could transform the relationship with the banking industry and define the norm.

ESG Reporting and Green Finance

ESG (Environmental, Social, Governance) continues to find support across the globe, and the EU’s Sustainable Finance Disclosure Regulation (SFDR) makes it mandatory for financial institutions to report on portfolio sustainability. In 2024, one major asset manager was criticized for greenwashing and misreporting ESG data.

Challenges:

• Data Integrity: Validating ESG data and being auditable. Even larger organizations have not prioritized clear processes on how to collect and verify ESG data. There is tremendous reliance on manual data collection and Excel spreadsheets in ESG reporting that introduce errors that limit reporting accuracy and reliability.
• Standardization: Reporting is inconsistent across ESG frameworks. The EU leads in this area; however, even if an organization is headquartered in other regions, after a certain financial threshold, they are held to the same reporting standards as EU HQ organizations. Without established policies and data collection protocols, financial institutions will struggle to meet these standards.

How Pentaho Helps:

• Golden Source ESG Data: Pentaho provides a central database for ESG data that remains consistent across all reports and analyses.
• Automated Data Validation: Algorithms within Pentaho validate ESG data against external benchmarks and standards, detecting discrepancies.
• Configurable ESG Dashboards: These allow portfolio managers to track and optimize sustainability metrics in real time.

Potential Industry Shift: Suppose you could not only be ESG compliant but also launch data-based green finance products. By delivering clear ESG performance metrics, institutions might lure eco-conscious capital and redirect funds to sustainable investments.

In our next blog, we’ll explore the issues around fraud detection and prevention, data sovereignty, cross-border compliance, and safely scaling innovative uses of AI in finance.

Discover how Pentaho supports financial services.