The critical role of data in the insurance industry

I’ve been looking more closely into the insurance industry, especially into the East African insurance markets and there are some ideas that I believe may contribute to further discuss the critical role that data must play in the incoming challenges caused by ongoing market disruptions, reflected directly on lower premiums and higher claims.

The business landscape is changing for good. To remain competitive, insurers must act now and start or accelerate their data-driven transformation to drive enhanced digital experiences and reduce costs.

It’s easy to identify the critical role data plays in this transformation, a journey into data-driven organizations, nurturing a data culture among their workers, enabling the capabilities for data driven decision processes, product and services developments and customer engagement.

Since the beginning data has always been the core of the insurance industry, a data culture is already embedded in the all the business processes, in an industry where statistical analysis is at the central part of the business itself, where data has always been used to inform underwriting decisions, price policies, settle claims or prevent fraud. Looking closer it’s clear that every crucial insurance process relies on clean, high-quality, and real-time data.

Act Now

The transition that needs to occur is to allow data into new dimension, walking into a more data and digitally driven industry, where data plays a new role as a business asset, creating value to the organization, but also to its customers and employees.

• This is the moment where Insurance companies need to understand the value of their data as a key business enabler.

• This is the moment to see the added value of data governance, data quality or more specific solutions as master data management or data catalogues.

• This is the moment to understand that these are prerequisites for all data related initiatives, from data collection to analytics, to the use of AI or ML.

• This is the moment is to tackle the challenges posed by data ecosystems where data is spread across a wide variety of applications, and data ownership is scattered across the business and IT.

• This is the moment to avoid falling into the temptation of jumping forward implementing reporting tools, analytic tools, and repositories — with all the tools that go with them.

• This is the moment to focus on data quality, data management, data policies, and the data dependent processes.

• This is the moment to assure organizations have reliable and consistent data, available to the right people in the right time.

Act How

This transition into a data-driven organization can only be achieve when is grounded on a strong data foundation.

This transition can only be achieved when we can successfully combine people, processes, and technology to create business value from data.

Data strategy is business strategy

As any other asset in the organization data’s purpose is to create value, so any data strategy must be oriented towards the organization's strategic priorities and key business objectives.

Business Cases

From here it is possible to identify how data may be used to deliver those priorities and objectives. These will be the business cases for the data strategy. In an early stage, for effectiveness purposes, there should not be more than five business cases, all with clear, achievable objectives and stakeholders that are aware of the importance and impact of data.

Start small, think big

Always aligned with the data strategy start with a small, targeted initiative, where the impact and value of data can be clearly identified and working with a business stakeholder that can passionately and effectively articulate the impacts of data in their business processes and that will be eager to defend the project.

Measure and communicate

Setting up a set of metrics that can be linked to data governance and communicating them across the organization, a success story, that even at a small scale will create the awareness and act as a motor to leverage the replication of that story in other business units.

Business on the driver seat

All the program and initiatives must be driven and oriented by the business units. Data governance is not an IT function, it is a business function, it is the business who better knows what their problems and objectives are. The role of IT in this process is to find the right technology and support the business units in this journey.

Agile mindset

Apply an agile development mindset to all this process, start with a minimum viable solution and iterate, allow those visible results are presented in short time lapses.

Integrate

Isolated data initiatives will fail due of inadequate data quality and governance, and these are only a part of the process of managing the organization’s data assets, it must be integrated with other initiatives, as Master Data Management (MDM), data quality, data stewardship workflows, data catalog, business glossary and metadata management.

Data Minimalism

All the data being collected and processed in the organization within a specific context, either operational, regulatory, and its collected and analysed with an end in mind, sustained by a business case and aligned with the business objectives.

Transformation Journey

Insurance companies focused on taking advantage of these opportunities need to develop their strategies around the creation of innovative, customer focused products, channels, and services, in other words, making digital transformation a top priority.

Becoming a data-driven organization and building a data culture is a difficult and long process.

Delivering business value and removing corporate culture friction are the main challenges and the chosen approach to this process, will determine the chances for success.

This requires a critical shift of mindset, the driver for this transformation can’t be IT, as traditionally is. All the program and initiatives must be driven and oriented by the business units. Business must be on the driver sit.

Becoming a data-driven organization is a long-term process that requires persistence and determination. Every data initiative can be a step in the right direction, but the focus must be on the business purpose, not in data itself.