AI in Finance and Insurance

Artificial intelligence in finance is driving growth and efficiencies

AI technology is being adopted by teams in every function, across every industry. At Fifty One Degrees we believe one of the most powerful applications is generative AI in Finance and Insurance. A recent UK Finance report expects value creation to increase by more than 50% within five years due to finance AI.

Why is AI in financial services so effective?

AI in finance and insurance are transforming these industries. They are perfectly placed to benefit from the recent advances in artificial intelligence technology because they are consumer-focused, complex, highly regulated and reliant on multiple sources of data.

What are the top use cases for AI in financial services and insurance?

Improve team member experience and increase efficiency

Generative AI ‘assistants’, trained to any specialism within your financial services business, provide instant support to your team members enabling them to produce more and increase the quality of their work. This technology ingests vast volumes of information and documentation and then provides precise insights and responses based on that information instantly. The result is accelerated projects and processes, improved customer experience, and the creation of resource efficiencies.

Increase automation and conversion in customer onboarding using finance AI

Financial services and insurance firms have inherently complex customer onboarding requirements due to their requirement to manage risk, mitigate fraud, pull and analyse multiple data sources, and comply with detailed regulations. AI in finance has made it possible to automate once-manual decision-making, therefore reducing referrals. Given that fully automating customer fulfilment can double conversion, this process can significantly increase revenue while simultaneously reducing the workload for manual teams.

Customer enquiries answered instantly with chatbots and generative AI in financial services

Serving existing customers is also benefiting from automation. It is possible to use technology and financial AI to instantly fulfil almost any customer enquiry, meaning you can save human interaction for where it’s needed, and use technology to resolve mundane enquiries. We believe there will always be a need for some human involvement in delivering amazing customer experience, but it should be limited to situations where a customer will value the personal touch.

Automated AI financial advice and planning

Generative AI (GenAI) powered by Large Language Models (LLMs) ingest large amounts of information and then serve it via human-like interactions. A perfect use case for this is financial planning and advice, where much of the information customers need is already available via reams of documentation, but the customers are often unwilling to trawl through to find the information they need. Tax advice. Inheritance planning. Investment information. Retirement planning. Finance AI can answer the majority of customer enquiries instantly.

Quality control and regulatory compliance monitoring using AI tools

Analysing voice or text-based customer interactions with AI tools is enabling financial services and insurance firms to monitor and QA 100% of interactions, while also reducing the volume of QA cases requiring manual intervention. The same artificial intelligence technology can also drive training requirements for team members, and identify opportunities for complimentary products and cross-sale.

AI fraud detection and prevention

The UK is experiencing a fraud epidemic leading many financial services firms to manually intervene where they ordinarily wouldn’t. The ability to ingest data from multiple sources into a fraud detection AI model provides an effective solution to this issue, identifying fraudulent transactions while also increasing efficiency for your manual teams.

What should be considered for my strategy to adopt AI in finance?

Fifty One Degrees advises companies on how to adopt AI. We recommend creating an AI strategy, within which you will manage your adoption of AI in a structured and considered way. The steps we recommend are:

  1. Assigning responsibility and creating a project team

  2. Analyse each area of your business to understand the most appropriate use cases

  3. Define your AI strategy, including objectives, governance and reporting

  4. Apply an agile software development approach to identify an initial project

  5. With your first project live, create and roll out a roadmap to apply AI across your business, prioritising based on expected impact and implementation complexity

Case study: Using Generative AI in insurance or finance for FCA regulatory compliance

Project objective – increase the bandwidth of the compliance function while also reducing compliance related friction for other projects across the business.

Project budget – the project must generate savings to cover the cost of the build process within 6 months from its delivery.

Solution – 

  • Build a GenAI Chatbot trained on FCA sourcebooks to automate the review and instantly respond to at least 50% of compliance tasks. Chatbot tool is called ‘FCA Regulatory Compliance Advisor’.
  • Use OpenAI’s GPT-4 to enable review of images, photographs and designs, not just written text.
  • Create Slack, Microsoft Teams and/or Google Chat integration so the tool can be used within the normal working environment. 
  • Create proprietary website integration to be launched within an internal customer management site.
  • Implement training tailored to marketing, product, technology, compliance and risk, finance and operational teams.

Project delivery

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