29 May

Solving the Policy Management Challenge for Financial Services with AI and a Digital Workflow

Danny Ivatt


  • Across the financial services industry, policy management is a huge challenge.
  • We’re working with a global commercial bank focused on high value deals with governments, investment in national infrastructure and large institutions, meaning  the risk created by non adherence to policy is high. Our work enables front office teams to deliver growth while staying within risk tolerances. 
  • Currently, they rely on manual approaches to creating and maintaining policy lineage, making changes to policy, writing new clauses and ensuring this is updated across all documents. This is very time consuming and provides inaccurate results. 
  • Our AI-enabled approach creates the lineage from specific clauses and introduces a fully automated digital workflow for policy management in large enterprise organisations. 
  • The AI model writes new policy clauses and proposed changes on behalf of the user.
  • It bypasses the need to invest in and manually build policy repositories reducing administrative time from years and months to minutes, increases accuracy and ensures compliance. 

Policy Management in the Financial Services Industry is a Huge Challenge

In globally connected organisations, policy exists at multiple levels, from global, regional and division specific policies in areas such as cyber security, financial crime and operational resilience to category specific controls and implementation guidelines. Adherence to a current policy that represents both the organisational standard and regulatory requirements is essential for these organisations.

To achieve this, organisations need to maintain and update policy documents, associated guidance and checklists at a number of levels. Harmonising policy, making changes to reflect new standards and ensuring that teams adhere to them is complex. 

Traditionally, it relies on labour intensive work. Those responsible for policy need to keep it up to date. Those who need to work to the standards set by policy need to ensure they are always working to the latest version, and understand exactly when, where and how policy applies.

There is a considerable amount of manual work for different teams: 

  • Maintaining links to external standards and regulation
  • Updating how global, regional and sector specific policies and their specific clauses link together
  • Propagating changes and edits to policy
  • Ensuring this is up to date and accurate 

For those who need to work according to policy, simply understanding the latest version and its accuracy can be difficult.

Creating an initial policy repository and identifying the lineage typically takes months or years for a team. Maintaining this takes considerable effort for front, middle and back office teams. 

Failing to stay on top of updating policy standards heightens the risk of non-compliance to standards, lack of adherence to controls for risk, and poor and inconsistent customer experience. Many organisations have seen large fines as they have failed to work to the current standard. 

Simplifying the Process

Our goal is to make the policy administration challenge simple for organisations. Significantly reducing the amount of manual work, increasing accuracy and ensuring compliance and adherence to standards. This reduces the risk of fines and gives teams more time to focus on the strategic impact of changes.

Manually Expensive Approaches

Incumbent approaches focus on GRC platforms for policy management that require manual effort to maintain and update lineage and clauses in each policy. This is time consuming and often inaccurate. Lineage is rarely granular, down to the clause. 

Enabling at a Glance Understanding

Our approach uses generative AI as the key enabler for a full digital policy workflow. Lineage can be bootstrapped, down to individual clauses. This ensures that policy changes can be propagated across the system in seconds. Human elements of this work can focus on actioning suggested change, rather than understanding where change needs to be applied. 

  1. Our model extracts semantic meaning from each policy and automatically creates policy lineage, down to specific clauses. 
  2. Our first step is to understand priority domains, map out the policy management process, ingest documents, create lineage, develop and test user facing solutions that can transform how teams work.
  3. As part of a digital workflow, policy administrators can make a change to a policy and have the change propagated across every other related policy. 
  4. The digital workflow prompts policy owners to review and update their documents. 
  5. Our AI model writes new clauses, makes edits and proposes changes on behalf of the user.  
  6. Users can view the entire lineage for an area of policy or clause, with an at a glance understanding of its status.  

The digital policy workflow contains a full lineage between clauses and ensures that policy updates at all levels are transparent and actionable. 

Modern Policy Management Functionality

The AI-enabled digital workflow system also provides additional functionality: 

  • Scanning regulation documents and automatically writing policy clauses to respond to requirements.
  • Maintaining lineage with external requirements and regulation.
  • Allowing front office teams to upload documents and ask questions to understand which specific policy should apply and how.

The AI model composes suggested new clauses with calls to action and notifications for users. Complex policy and clause lineage is created by AI in minutes, rather than months of manual work. 

Efficient Policy Management, Powered by AI

This reduces the amount of manual effort required from months to minutes, as users simply receive notifications and suggested wording and are prompted to action the change. The drastic reduction in manual work allows teams to focus on strategically impactful activities. Accuracy and compliance is radically increased from the previous manual approach. 

Our approach creates multi million £ savings in the administrative time needed across an organisation to manage policy, and avoidance of fines through non-compliance. It gives confidence to teams who must work to standards as set by policy as they have an at a glance understanding of accurate, up to date guidance. 

This area contains huge opportunities for value to be created through AI, enhancing how teams across multiple domains engage with policy and ensure compliance. 

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