AI in financial services: Innovation without the risk

Artificial Intelligence (AI) is transforming financial services, offering smarter decision-making, automation, and enhanced customer experiences. Yet, despite the opportunities, many financial institutions hesitate. Why? Because AI brings more risk than ever before—from compliance challenges to concerns about explainability and governance.

This blog draws on insights from a recent roundtable event hosted by 2i and the follow-up report, Growing Financial Services with AI. Senior technology leaders from across the industry, concluded: successful AI adoption isn’t just about technology - it requires strong governance, rigorous testing, and a proactive approach to compliance. The solution isn’t to avoid AI but to adopt it responsibly.

Here’s how financial institutions can balance innovation with risk management to unlock AI’s full potential - without jeopardising security, reputation, or compliance.

Start with governance, not just innovation

Financial leaders are under pressure to innovate, but AI without governance is a liability. Regulations like DORA (Digital Operational Resilience Act) and the EU AI Act set new standards for responsible AI adoption. The key is building governance into AI initiatives from the start, ensuring financial institutions can scale AI without unexpected regulatory roadblocks. Immediate priorities should focus on:

1. Aligning AI with existing risk management frameworks - AI should not exist in a silo - it must follow the same governance, cybersecurity, and risk management policies as other financial systems. Establishing AI-specific oversight ensures compliance from the start.
2. Ensure AI decisions are explainable - Regulators and stakeholders demand transparency. AI models must provide clear, auditable decision-making processes to meet regulatory scrutiny and build customer trust.
3. Prepare for regulatory audits - Regular third-party audits and clear documentation of AI usage help institutions stay ahead of compliance requirements and avoid unexpected legal challenges.

"Regulators want us to demonstrate we’ve got robust controls in place." 
Paul Colam, Head of Operations, GB Bank.

Test first, deploy later

AI models are only as good as the data and testing behind them. Financial services operate in a high-stakes environment. Untested AI can lead to compliance breaches, security flaws, and reputational damage. Leading firms are embedding AI-powered testing into their development cycles to catch risks before they become problems.

1. Simulate real-world scenarios before deployment - AI models should be stress-tested under various market conditions, transaction volumes, and security threats to prevent failures in live environments.
2. Monitor AI performance over time - AI systems evolve as they process new data, which can lead to unintended drift. Continuous validation ensures models remain accurate and aligned with compliance standards.
3. Use synthetic data to safeguard privacy - Testing AI with synthetic datasets prevents exposure of sensitive customer information, ensuring robust model performance.

“Many clients are figuring out solutions and making mistakes, which is okay – but, when you’re making mistakes with something so critical to your future, that becomes problematic.”  
Vikas Krishan, Chief Digital Business Officer, Altimetrik.

Turn compliance into an advantage, not a burden

Many financial institutions consider compliance a cost, but AI can turn it into a competitive advantage. By integrating AI into compliance processes, organisations can reduce manual workload, lower costs, and accelerate approvals.

1. Automate regulatory reporting - AI can analyse and generate compliance reports faster and with greater accuracy, reducing manual effort and regulatory risk.
2. Enhance fraud detection - AI-powered systems can detect anomalies in transactions in real time, identifying fraud patterns that traditional rule-based methods often miss.
3. Improve data governance and auditability - AI ensures financial institutions maintain clean, structured, and traceable data, making audits more efficient and reducing compliance risks.

"If you can use AI to make compliance more efficient, you free up budget for value-added innovation." 
Pauline Smith, Chief Operating Officer, 2i

Trust is the differentiator

Customers, regulators, and investors are all asking the same question: Can we trust AI-driven financial services? AI is only as valuable as the trust placed in it - ensuring transparency, fairness, and explainability is essential for long-term success.

1. Make AI decisions transparent and understandable - Customers and regulators need to understand how AI-driven decisions are made. Clear, auditable AI models build confidence and reduce regulatory scrutiny.
2. Ensure fairness and remove bias - Unchecked AI models can introduce bias that leads to unfair financial decisions. By implementing fairness testing, institutions can ensure AI-driven processes are ethical and compliant.
3. Partner with trusted AI governance specialists - Working with experts in AI testing and governance helps financial institutions implement AI responsibly and stay ahead of regulatory shifts.

AI has the power to transform financial services, but success isn’t about moving fast - it’s about moving with control. The institutions that stay ahead will be those that embed AI into governance, rigorously test their models, and build trust through transparency, ensuring predictable outcomes at every stage.

Want to learn how industry leaders are balancing AI innovation with control? Download the full 2i roundtable report for insights on how financial institutions are achieving AI success without the risk.

Or, are you looking for a proven approach to AI governance, testing, and compliance? Get in touch to discover how 2i helps organisations deliver predictable, risk-free AI adoption.