To compete in an ever-changing environment, Property and Casualty (P&C) Insurance companies rely on their Finance teams for strategic insights and operational resilience. However, Finance functions have yet to reach their full potential and often fall short of driving significant strategic value.

Challenges can stem from growth through acquisition, complex legacy architectures, disparate teams, and decentralized data and processes. Additionally, the General Ledger might hold data in aggregation, but the business lacks a real-time view of payables and receivables.

Finally, complex product portfolios and subsidiary landscapes can make it difficult to see how capital flows through the business.

In this eBook, we’ll show you how HSO & Aptitude Software have helped P&C Insurers avoid expensive, big-bang transformation programs with a best of breed technology approach while unlocking data, digital automation and AI to help Finance teams deliver strategic business value.

To better understand where CFOs and their teams are in their journey to Autonomous Finance, Aptitude, Microsoft and HSO, commissioned third-party research that surveyed Finance and IT professionals across the globe. The focus was on understanding current priorities and challenges, AI usage, time associated with various tasks and overall approach to transformation. The answers placed teams on a continuum ranging from Traditional to Autonomous Finance.

Here, we’ve pulled out Insurance-specific results and indicated how they compare to their peers in Banking, Media, CPG/Retail, Manufacturing and Platforms.

In the Benchmark study, nearly 70% of surveyed Insurers placed their finance function at either the Traditional or Integrated stages, which means they have a long way to go to reach Autonomous Finance.

When looking at their AI usage compared other industries, Insurance came in dead last. They fared better in comparison in their Automation efforts, coming in at number two and were in the middle of the pack when it came to Data Readiness.

• Operational restructuring was reported a challenge for financial stability at a much lower rate by Insurers. 18% compared to the global score of 26%.
  
  
• 22% of Insurers indicated that AI is not currently used in financial operations. This is higher than the global score of 16%.

• Only 13% in Insurance say that data is fully integrated with machine learning to flag quality issues. The global average is 21%.
  
  
• In the Insurance sector, 23% say they are still in the very early stages of digital transformation at an
  organizational level. This is much higher than the global score of 13%.

• Who should lead the AI strategy:
  Finance & IT combined
  
  
• The top three benefits of AI investment:
  1. Efficiency
  2. Audit & compliance support
  3. Better accuracy
  
  
• Average tech project time to value:
  3-4 years

• Self-reporting availability:
  Majority reporting available as self-service
  
  
• Time to complete period end close:
  1-5 days
  
  
• Data processing frequency:
  Weekly

• Multi-GAAP & regulatory compliance
  Ability to manage concurrent financial reporting under multiple accounting standards (e.g., US GAAP, IFRS, statutory accounting).
  
  
• Dynamic continuous close
  Real-time financial consolidation and on-demand statement generation to support faster decision-making.
  
  
• Centralized accounting & subledger management
  A unified system for tracking and managing financial transactions across multiple lines of business, geographies, and regulatory environments.
  
  
• Claims and premium accounting
  Accurate and automated processing of premium revenues, claims payouts, and reserves to ensure financial integrity.
  
  
• Reinsurance accounting & settlements
  Streamlined handling of ceded, assumed, and retrocession transactions with automated settlement and reconciliation.
  
  
• Producer compensation accounting
  Provides automated accounting for producer compensation commissions and events.

• Insurance accounting calculations
  Pre-defined accounting calculations for Insurance business activity to accelerate new offerings to market.
  
  
• Liquidity & capital management
  Robust cash flow forecasting and capital allocation to ensure solvency and optimal investment strategies.
  
  
• Auditability & control
  Strong governance, audit trails, and internal controls to enhance financial accuracy and regulatory compliance.
  
  
• Integration with policy & claims systems
  Seamless data flow between core insurance platforms and finance systems for real-time reporting and reconciliation.
  
  
• Automation & AI-Driven insights
  Leveraging AI/ML for fraud detection, reserve adequacy analysis, and financial forecasting.

Maximizing capital investment

Managing liquidity, or “float,” is a major challenge for Insurers. While investing this float can generate significant revenue, traditional systems delay critical data, leaving CFOs with narrow windows for investment decisions. By the time policy and admin systems complete calculations, it’s often too late to make effective investment decisions.

Modern finance platforms like Fynapse provide real-time data processing, enabling Insurance companies to capitalize on midday trading opportunities. With a real-time finance data management platform, CFOs can see midday positions and determine if they have extra liquidity that can be invested immediately, maximizing revenue generation.

Real-time, granular data

Another common issue for Insurance CFOs is the lack of granularity in financial data. P&C Insurers typically receive highly summarized information from their policy and administrative systems. Delayed or batch processing means it’s often too late to act on, making it difficult to quickly identify anomalies, emerging risks, or opportunities in specific geographies or segments.

A modern finance data management platform can change this narrative. These platforms allow for detailed, real-time data analysis, providing finance teams with the ability to pinpoint trends, risks, or opportunities as they happen. This empowers the office of the CFO to act swiftly, mitigating risks and seizing opportunities without waiting for the end-of-period data reconciliation.

For finance teams, the financial close process is one of the most critical – and often one of the most challenging – responsibilities. The speed of your close not only determines when results are available but also directly impacts the CFO’s ability to make timely, informed decisions that drive capital investment and business decisions.

According to the 2024 Global Autonomous Finance Benchmark, a striking 58% of finance leaders revealed it takes up to 5 days to close their books, while only 7% have achieved a continuous close. These findings highlight the urgent need for solutions that simplify and accelerate the close process.

With Fynapse, you gain confidence and efficiency in your financial operations, redefining what’s possible for the close process.

• Speed and automation: Automates repetitive tasks, integrates data seamlessly, and eliminates inefficiencies to simplify workflows.
• Faster reporting: Speeds up the process of generating accurate, insightful reports, enabling timely decision-making.
• Continuous close: Provides real-time updates on your financial position, so you’re always ready to act with confidence.
• Strategic impact: Minimizes manual workloads giving your team the capacity to focus on strategic priorities.

Automating repetitive tasks

Traditional finance teams spend countless hours on manual processes like reconciliations, report generation, and compliance checks. These tasks, while essential, consume valuable time and resources that could be better spent on strategic initiatives. Automation tools can help address these inefficiencies. Key capabilities include:

• Automated reconciliations: Microsoft Dynamics 365 Finance & Operations can handle complex reconciliations with ease, flagging discrepancies and suggesting corrective actions.
• AI-driven compliance: Tools like Aptitude Fynapse ensure that financial reports meet regulatory standards without manual intervention.
• Streamlined reporting: Pre-built templates and customizable dashboards reduce the time required to generate accurate reports.

Enhancing collaboration

In the Autonomous Finance survey, 50% of global respondents stated that Finance self-service reporting was either non-existent or limited to a small group of users. In the Insurance sector that number was even higher with 56% reporting no or limited access to self-service reporting.

Modern finance isn’t confined to the accounting department - it intersects with sales, operations, and other business units. Unlocking digital capabilities improves cross-departmental collaboration, enabling:

• Real-time sharing of financial insights.
• Seamless integration of finance, business and CRM systems for a holistic view of customer profitability.
• Dynamic forecasting that incorporates inputs from multiple stakeholders.

Customizations with Copilot Studio

No two organizations are alike which is why companies need the customization capabilities of Microsoft’s
Copilot Studio. By tailoring AI functionalities to specific business needs, organizations can:

• Automate unique workflows.
• Develop industry-specific analytics tools.
• Create personalized dashboards for different user roles.

Scaling AI Adoption

Unlocking AI is not a one-time initiative—it’s a journey. Aptitude and HSO help organizations scale their AI
capabilities over time, ensuring that systems remain adaptable as business needs evolve. This includes:

• Training teams to leverage AI tools effectively.
• Continuously refining AI models based on new data.
• Integrating AI into broader enterprise strategies

• Improved Compensation Management:
  Fynapse will underpin a Producer Compensation Hub by holding all policy details and providing full visibility into settled accounts. The Insurer can now apply the correct percentage allocation for each involved party, set percentages at the deal level, resolve disputes and execute producer payout.
  
  
• Automation:
  Azure AI will automate the previously manual carrier statement and payment matching process with the data passed to Fynapse to post the accounts receivable adjustments and close AR accounts out with the cash settlement process.

• Streamlined revenue recognition:
  Fynapse will support complex revenue recognition requirements by taking required data and creating accruals for expected accounts receivable, updating with settlement information and performing all required revenue amortization. Balances will be summarized to the General ledger using the Microsoft Dynamics 365 Finance and Operations connector with the post/reverse netted out, leaving them with a clean, incremental revenue recognition feed to the GL.
  
  
• Enhanced Analytics:
  Improved visibility into transaction-level data to support the company’s master data management strategy.

Automating data activities

Many finance transformation projects stall due to incomplete data preparation, which can account for 80% of the effort. Solutions like Fynapse that use Extract, Load, Transform (ELT) accelerate progress by allowing raw data to be enriched within the system, reducing time to value. Automated regression testing and AI-driven configuration further streamline the process, minimizing delay

Configure faster

Rapid finance solution configuration accelerates time to market, enhances agility, and cuts implementation costs. Faster, even automated, setup enables businesses to adapt quickly to market shifts, regulations, and growth opportunities while optimizing workflows and gaining critical insights sooner.

However, large ERP systems often lack finance-specific capabilities, requiring extensive IT-led configuration that slows progress. Reducing configuration complexity—both at setup and throughout ongoing adjustments—lowers implementation time, frees finance resources, and empowers finance teams to manage the system independently, giving them greater control over business direction.

Iterative change

The market is lacking a viable alternative to large ERP systems. Organizations need composable, modular solutions that support small, iterative projects and allow finance teams to quickly show success and win buy-in. Solutions that support quick changes and the ability to see results in real time are faster and less risky and can win over leadership teams that were previously intimidated by large scale change. In fact, when smaller use cases are delivered more quickly, adoption tends to increase, and excitement around the new system is sustained.