Geoffrey Lash professional photo

Geoffrey Lash

Vice-President, Consulting Services

The generative artificial intelligence (gen AI) hype machine has expanded across most industries, no less in banking and financial services. While generative AI can certainly assist with improving internal productivity and managing copious amounts of internal policies, procedures and client/employee documentation, additional uses of gen AI within risk and compliance management are emerging. While it’s essential for financial institutions to implement effective controls for gen AI’s use, it’s equally critical for organizations to develop and implement a gen AI strategy based on data sensitivity, operational risk, governance best practices and regulatory requirements. This article discusses considerations for how financial institutions can develop and execute an effective approach for using gen AI in risk and compliance management, including emerging applications and use cases. 

The benefits of gen AI for financial institutions

Gen AI can help financial institutions keep pace with continuous change, future-proof their businesses, and outperform both traditional and new competitors. Specific to risk and compliance management, gen AI can assist in improving internal policy and procedure management, internal control management (e.g., risk and control self-assessment framework), third-party risk management (TPRM), anti-money laundering (AML) and know your customer (KYC) obligations.1 Many organizations utilize established governance, risk management and compliance platforms (GRC) to manage risk and control inventories and associated activities (e.g., emerging risk identification and control deficiencies). Utilizing generative AI can result in various benefits, including:

  • Improved predictive analytics and prioritized risk assessments
  • Controlled testing patterns
  • Identification of duplicative risk, key controls and compensating controls
  • Uncovering risk, audit and control deficiencies (i.e., limitations and weaknesses)2


Accelerating the power of adaptive banking with AI

Generative AI has many practical advantages for financial institutions and accelerates the goals of adaptive banking, including:


Automate processes and decision-making to increase efficiencies and potentially reduce costs. Examples include:

  • Automated customer onboarding services
  • Credit decision-making
  • Straight-through payments processing



Gain insights on each customer's unique financial behavior, preferences and needs. Examples include:

  • Personalized services and proactive offers
  • Personalized financial advice by virtual assistants or agents


Risk management

Improve risk management and regulatory compliance. Examples include:

  • Fraud detection and prevention
  • Automate KYC process
  • Transaction monitoring
  • Credit risk assessment



Advance sustainability objectives by creatively finding solutions. Examples include:

  • Automated digital audits and sustainability reporting
  • Generation of corporate documentation



Maximize uptime for critical systems and infrastructure. Examples include:

  • Predictive maintenance
  • Automated failover
  • Risk assessment and forecasting
  • Simulation of bank stress tests


Building a generative AI strategy for financial institutions

For financial institutions pursuing an aggressive gen AI strategy, the benefits across their organizations are vast. Specific to risk and compliance, institutions are realizing substantial improvements across regulatory compliance, credit risk management, internal controls, documentation (i.e., policy) management and financial crime risk management.3 

Regulatory compliance

Institutions are using gen AI to identify and evaluate pending legislation, proposed rules and regulatory exam priorities/enforcement actions more accurately and effectively. Additionally, compliance functions utilize gen AI to automate the analysis of regulatory compliance and identify gaps and potential breaches.4  

Credit risk management 

Generative AI can assist in optimizing and accelerating banks’ credit life cycle by summarizing customer details to inform credit decisions. By analyzing factors such as credit history, income, employment status and source of funds, financial institutions can assess the creditworthiness of applicants leading to more informed decisions and reduced default risk.5  

Internal controls

Historically, the cyclical internal controls process was manual and defensive compared to automated and preventative. Financial institutions can leverage AI to more completely address rising regulatory scrutiny and emerging risk factors to understand the impact on their holistic risk appetite framework. Additionally, effectively utilizing AI will allow financial institutions to expand their data sample sizes, improve testing accuracy, increase testing frequency, and automate most components of data gathering and preparation activities.6  

Documentation/policy management

Institutions find it challenging to maintain a centralized repository of updated internal and external policies, procedures, frameworks and regulatory guidance. Additionally, compliance functions are inundated with duplicative and time-consuming data requests that increase the likelihood of oversight. AI can align regulations with existing policies and procedures and proactively detect policy gaps based on changing regulations to minimize the risk of non-compliance.

Financial crime risk management

AI technology is critical to collecting and analyzing customer information and transactional data to identify changing patterns and trends. AI can analyze data sets in more depth than merely remediating a suspicious alert – pulling data from customer information profiles, ongoing due diligence, sanctions and negative news sources to create a comprehensive KYC profile. Additionally, AI can automate and improve the accuracy of financial crime risk assessments.7   

Transforming the financial services and banking industries with AI

When utilized appropriately, AI will be transformative to the financial services and banking industries. From a risk mitigation and compliance perspective, the benefits of AI far outweigh its risks. Institutions should ensure they have up-to-date policies, procedures and guidance related to the use and application of AI, particularly to safeguard against ever-changing laws and regulations.  

Partnering with CGI means having a trusted partner and advisor to guide you through ever-changing requirements to support your compliance risk management programs. Financial institutions must ensure they have effective AI strategies to ensure regulatory requirements are met, both in the near and long term. Contact us to learn more about our AI and emerging technology solutions, capabilities, and experience to help your institution in a competitive and evolving market.

1 “Where AI will play an important role in governance, risk & compliance programs,” Thomson Reuters, Todd Ehret,, 24 August 2023


“Five areas AI could transform compliance and risk management,”, Moody’s, 31 October 2023

“How generative AI can help banks manage risk and compliance,”, Rahul Agarwal, Andreas Kremer, Ida Kristensen, and Angela Luget, 1 March 2024

“Generative AI: The Missing Piece in Financial Services Industry?, ”, 21 April 2023

6 “Modernizing risk management: How AI-powered automation is redefining audit and controls testing,”, Hincher, Bill. 20 February 2024

7 “Fighting Financial Crime With AI Is Not A Trend—It’s A Necessity”, Twomey, Niall. 07 February 2024.

About this author

Geoffrey Lash professional photo

Geoffrey Lash

Vice-President, Consulting Services

Geoffrey is a Vice-President, Consulting Services and heads the New York Metro Banking Practice. He has 15+ years of banking and capital markets experience, focusing on designing, managing, and delivering risk, compliance, and transformational programs to global, regional, and super-regional financial institutions. Before CGI, Geoffrey ...