The FCA’s Consumer Duty regulation and what it means for brokers | NTT DATA

Mon, 07 August 2023

The FCA’s Consumer Duty regulation and what it means for brokers

The FCA’s Consumer Duty came into force on 31st July this year.

The FCA’s Consumer Duty came into force on 31st July this year. In this blog we will explore how a good data strategy is a key pillar to support compliance.

This is the second blog in our data and broking series. If you missed the BIBA Conference 2023, catch up with our four powerful takeaways from the event here.

 

What does Consumer Duty mean for brokers?

This regulation is likely to cover any broker working directly with an end customer (i.e. B2C) but not speciality brokers whose clients are typically businesses (i.e. B2B). To comply, firms need to deliver better outcomes for consumers whilst proving their full understanding of these rules and how these outcomes are being met. The more advanced your data management capability, the easier this will be as you extract more high-quality insights about your customers.

 

Why is effective data management the key?

An effective data strategy helps compliance in a number of ways. Here are five key outcomes to support compliance with the Consumer Duty that an effective data solution is fundamental to.

 

1. Customer understanding for personalised offerings

By maintaining accurate and up-to-date records about consumers and their financial products and services, brokers can meet client expectations whilst providing a personalised experience, demonstrating their commitment to meeting regulatory requirements.

 

2. Transparency

The Consumer Duty places significant importance on transparency in communications. AI-powered data analytics can help present complex policy terms to customers in an easily understandable manner – building trust and allowing customers to make informed decisions.

 

3. Monitoring and Compliance

Data analytics tools enable firms to monitor and identify potential financial harm to consumers, such as overcharging or miss-selling products. This means brokers can proactively reach out to clients as things change, ensuring that their policies remain relevant and suitable over time.

 

4. Providing value for money

Firms need to ensure their products are priced correctly and reflect the benefits they bring to the end client. They also need to ensure there is a ‘reasonable relationship between the price charged and profitability’. Using data analytics, brokers can keep pricing fair and provide on-demand evidence to regulators.

 

5. Scalability

An effective data strategy gives firms the repeatability and scalability needed to iterate and build their capability. Getting the foundation right is critical, allowing firms to add value at a regular cadence in line with the organisation’s aspirations.

 

How to build a tailored approach

Firms must approach their data strategy step-by-step, laying out objectives and ideal outcomes at the outset. There are three primary stages in this process.

 

Case for Change

Firms must first map out the objectives and benefits of exploiting their data, building the Case For Change. This may involve qualitative data capture via 1-2-1 interviews with senior leadership, online surveys, and competitor research.  This is the time for firms to define their KPIs and measure their baseline and target for the future state.

 

Data Maturity and Data Quality Assessment

A Data Maturity and Data Quality Assessment will highlight any gaps in capability. Using NTT DATA’s maturity matrix, we would assess various attributes, for example, Data Ownership, Standard, Data Dictionary and Flow, Lineage, and many more.

NTTD would source this data via facilitated workshops, structured interviews, and document reviews. Results are then consolidated and analysed to identify key themes and exceptions.

 

Roadmap and Data Governance Operating Model

Finally, firms should lay out a Roadmap of changes and an associated Data Governance Operating Model for compliance. This takes four parts.

 

  • Discover: understand the existing data governance model.
  • Analyse: using the NTT DATA reference model, identify capabilities gaps and the effectiveness of existing controls.
  • Design: define your target operating model to address gaps and issues.
  • Implementation: Prioritise initiatives based on benefits, cost, and risk of delivery. Communicate your vision and plan to gain support and buy-in.

 

Our work

Firms are under increasing pressure with each coming year. AI is being adopted across the insurance industry, but this new wave of Generative AI is more disruptive than any AI tech that’s come before. Watch out for the next blog in this series, explaining how brokers can successfully adopt AI to extract the most value from their data.

We work closely with brokers and other insurance industry participants to ensure they are aware of the latest regulation and support them through the entire compliance process. If you’d like to know more about our work in this area, take a moment to get in touch and arrange a 45-minute consultation

 


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