A calculated approach to actuarial transformation

As the insurance industry faces rising competitive pressures, stricter regulatory demands, market volatility, and stretching consumer demands, carriers are searching for ways to create new products and drive operational efficiencies that deliver profitable margins and ensure growth. One opportunity for actuaries to contribute to growth is to take advantage of the explosion of data available to the industry and capitalize on an evolving global risk portfolio and consumer shifts in the market. With this opportunity, however, comes a complex web of internal and external data sources to navigate, meaning leaders must formulate and act on a clear vision of how to monetize data assets.

Actuarial functions are ripe for modernization. Although reserving methods haven't changed significantly over time, the risks they underwrite are unrecognizable and regulatory demands are constantly changing. There are four forces for change:

Building future talent: Insurers need to augment existing actuarial talent with advanced data and analytics skills to anticipate and respond to rapidly changing market and regulatory conditions. The insights to help develop new products and understand customers better from analytics and data science are emerging as a game changer for the industry, and insurers must have the right blend of skills to take advantage of the new sources of data and technologies.

Data infrastructure: Disparate systems that limit data innovation and the integration of new sources of data and analytics plague current actuarial functions. Insurers should pursue a robust data consolidation and simplification program that builds a single version of truth and timely access to data in a consistent fashion to better respond to changing regulatory requirements and use data-driven insights for better decisions. This program should include all internal and external sources and explore the value of third-party data.

Regulatory changes: The increased complexity and disclosures of global regulatory requirements are adding to actuarial costs and workloads. First, we had companies adopting Solvency II compliance, now we have ORSA and IFRS 17 accounting standards, and LDTI changes on the way. With each new regulation, insurers need increased focus on streamlining data, models, and disclosures and cost-effective solutions to build additional analytics capabilities.

Target operating models: Actuaries are spending 20–25% of their time on data wrangling rather than actuarial analysis and strategizing. Finding value through process efficiencies such as automation and aligning these with broader enterprise transformation programs mean actuaries can add value through more actuarial consulting rather than data-gathering and curation. Redesigning the actuarial target operating model (TOM) will optimize processes for a better customer experience and reap productivity benefits.

So how should insurers tackle actuarial modernization and generate data-driven insights that manage costs while enhancing their value proposition in a tough market? They must ensure they're using all the key levers of a successful actuarial transformation program that span the customer experience, architecture, and talent. This includes:

• Reimagining the TOM
• Building the right data foundation
• Process transformation
• Analytics and digitization
• Actuarial centers of excellence
• An agile and innovative execution approach

Clear, visible senior leadership and robust change management practices should support these.

Insurers should choose a transformation partner that combines process and industry expertise and can tackle a broad range of actuarial challenges such as fragmented data, broken processes, inefficient controls, and resource issues. Processes must align with other functional processes such as finance, underwriting, sales, and external regulators, as well as end customers.

This is Genpact's take on how to transform the actuarial function.

1. Reimagine the TOM

The starting point to transform the actuarial function into a more strategic business partner is to design the right TOM. This should factor in right-shoring, right-skilling, process excellence, and digital technologies to drive effectiveness and profitability. Removing low-value activities enables the function to focus on creating strategic insights that support product innovation and accurate reserving. Though this is niche work in the overall value chain, it impacts the internal as well as external environment. A small multidisciplinary team of actuarial domain experts, data scientists, project specialists, and reengineering experts should deploy for a three- to six-month period to determine the key transformation initiatives and timelines for implementation. Their remit should cover data, processes, people, modeling, and projects to ensure robust data reconciliation, and process dependencies.

2. Move from data strategy to best-in-class data infrastructure

Insurance carriers should accelerate their data program by simplifying access to information through consolidation of the data environment.

The starting point should be to create a single source to store inputs and outputs to provide consistency, enhanced analytics, and visualizations. This journey should start by assessing the current state of upstream and downstream process dependencies and technology maturity.

This comprehensive approach ensures alignment with the overall enterprise data strategy by evaluating the current infrastructure and mapping it to future needs, building a roadmap to a better data foundation that is ready to move to the cloud.

3. Process transformation: simplification and alignment of processes

Insurers are under pressure to find process efficiencies and cost reductions through the standardization, automation, and enhancement of processes. This can be achieved through a mix of cross-functional collaboration, design thinking, and Lean Six Sigma principles to find the right processes to improve process mining. To achieve best-in-class processes, insurers need to determine the interventions required to optimize the actuarial process flow. This includes:

• Mapping end-to-end processes to identify challenges and opportunities
• Applying digital tools such as robotic process automation (RPA) to low-judgment and rule-based processes
• Root cause analysis to understand pain points and potential solutions

When this is complete, next steps can be classified into two categories:

• Quick-win or short-term initiatives that will immediately boost productivity. These projects typically impact one or two steps within the process
• Transformative or long-term projects that involve restructuring processes. These will improve overall process efficiency and effectiveness, thereby reducing costs

4. Analytics and digital technologies

Advanced data analytics and digital accelerators can generate substantial cost savings, boost actuarial productivity, and support quicker, more accurate business decisions. Data science and analytical tools like Python, machine learning, and Microsoft's Power BI can deploy to automate downstream processes to handle and aggregate modeled outputs in a more efficient manner.

5. Actuarial centers of excellence

As more insurers consider outsourcing actuarial tasks, partnering with someone who has deep domain expertise of unique actuarial processes is crucial. It's a complex area that requires a holistic approach in terms of knowledge transfer, building capabilities, and resource management. A robust transition plan coupled with an effective training engine will ensure the knowledge management and availability of skilled staff. Actuarial centers of excellence deliver the levels of skills and staff required for an effective outsourced function.

6. An agile and innovative execution approach

Agile delivery pods execute projects faster and deliver transformation within agreed timelines. These cross-functional teams should bring together domain, business unit, data engineering, and data science expertise to build successful shared outcomes.

A strong governance and communications framework builds visibility and transparency throughout the engagement. There should be a three-tier governance framework that includes operations owners and subject matter experts, the leadership team, and a steering committee.

The actuarial profession must evolve as it faces increasing demands to transcend traditional roles with bolder data strategies, wider adoption of advanced analytics techniques, and embedded insights into enterprise processes. Any actuarial modernization program must acknowledge these realities and build on a bedrock of the right operating model.

The starting point is to assess and benchmark processes against industry norms and peers to identify areas for improvement. This includes reviewing the current state of processes, data, applications, and systems.

Next, agree what the ideal future state looks like. This should reflect the market and regulatory environment and include solutions that bring together technology and actuarial capabilities and models to realize value faster. This TOM will then provide the vision that insurance leaders need to guide actuarial transformation.