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Artificial Intelligence in Insurance

Take the next step in process automation and improving customer experience

Artificial Intelligence in Insurance

Take the next step in process automation and improving customer experience

AI automates claims handling and underwriting tasks previously reserved only for experts

Insurer challenges that can be solved by AI

Due to the virtual nature of insurance, the insurance industry is ideal for digitalization.

On the other hand, because of knowledge complexity, it has not been easy to automate.

Insurers wanted to apply predictive analytics and machine learning techniques to detect fraud for decades. However, the challenge was a small amount of structured data available, as the information was "hidden" in documents and heads of experts.


There is a great number of documents and pictures to analyse in claims handling and underwriting, and a lot of information to match with many conditions. That complexity requires many experienced employees. Moreover, with such an elaborate process complexity, a lot of mistakes may occur.

Insurance business is condition- and contract-based. Insurer’s representative needs to know how to effectively respond to regulatory inquiries or manage contract risk. For a call centre consultant finding a correct way to answer specific customer question plays a big role.

It is not easy for contact centre consultants to answer customer questions ad hoc while managing their emotions at the same time. It is challenging (if not impossible) for a supervisor to monitor the calls and intervene – a few against hundreds of calls.


It happens that a customer needs to type a lot of information during claim notification online, little hints. The same information may exist in documents he already attached. And then he is notified about missing information even a few days later and again – waiting for a proper reply.

Example areas where insurers are successfully applying AI for automation

car riding the wrong road
Claims handling of medical, house, car, TPL, marine insurance
lost documents
Underwriting of corporate insurance
document to be analysed
Analysis of contracts for compliance & risk management
chatbot answering customer question
Chatbots for clients for claim notification and customer service
human in the call centre
Realtime coaching of and supervision over call centre consultants

AI tools are very effective

but the right tool needs to be used for a specific problem.

For example, a typical success rate of intelligent document recognition is 80–95%.

Insurer’s benefits from AI

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Lower operating costs

AI automates repetitive human tasks up till now possible to carry out only by humans. Examples include analysing documents, pictures, and complex information.


human sitting in fron tof laptop human sitting in fron tof laptop
Lower claims paid

Humans make mistakes, which results in claim leakage, usually estimated by internal audits. Once trained, AI is consistent and independent of tiredness.


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Lower substitute costs in claims

AI automation can shorten the claims handling process, which may result in shorter rent of a replacement car or lower payments of business interruption claims.

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Better customer experience

AI enables new ways of interacting with customers. An immediate, empathetic and correct response from the insurer can have a positive impact on the customer's perception.

documents into catalogs documents into catalogs
Better analytics of frauds, tariffs, efficiency

Automatic AI recognition unveils data hidden in unstructured form in documents and photos that previously had to be manually processed by employees. Structured data is the fuel for predictive analytics.


three stacks of documents three stacks of documents
Improved contract visibility, compliance & risk assessment

AI allows for automatic search and analysis of different types of contracts. It enables insurers to respond quickly to regulatory inquiries and increases the visibility of contractual risk.



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Better employee experience

AI automation will reduce manual tasks and foster efficiency, allowing employees to focus on the higher-value creative aspects of work. Additionally, it will create exciting new jobs related to configuring and managing automated processes.


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Higher quality of human work

AI can augment the work of all employees, not just experts, leveraging features like analytical skills and scalability to unlock insight and efficiency. This enables faster decision-making, more precise problem-solving, and enhanced innovation across the organization.


AI components are easy to configure

You do not program an AI component, you teach it almost like a human.


So why do companies not adopt the AI revolution relatively quickly?
What's the crux of the matter?

Reasons why insurers may need some time to take advantage of AI automation

Think of the strategic perspective - critical capabilities of your organization to enable company-wide AI automation

Lack of AI automation knowledge


The lack of knowledge related to AI automation stops you from making the right decisions regarding automation planning

  • What automations should I consider?
  • There are many AI tools which one can I choose to solve my problem at a reasonable cost?
  • How to manage the increasing complexity of new business logic and redefined processes?
  • As an organization, how do we gain and manage knowledge related to AI automation?
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corporate building architecture

Managing complexity of corporate architecture


AI tools are only a small part of the overall landscape

  • Typically, AI automation introduces new data and business processes into current systems, which means the entire company architecture must be rethought to support it.
  • Otherwise, excessive implementation costs and architecture complexity can halt the progress of AI automation initiatives.
  • As an organisation, do we have experience in managing complex architecture change connected with business transformations?
Based on our experience, we can help you face these challenges – see our service offer

Sollers Consulting insurance services connected with AI

We are helping insurers in the whole journey of AI-driven transformation

Advisory about AI solutions

Sollers can support your team in learning AI tools to make the right decisions

  • Educational/inception workshops – your team will become inspired by what is possible with AI
  • Analyse as-is process to identify opportunities and realize the possible benefits of AI automation
  • PoC – verify AI tool against your actual process but out of production environment – no risk, little cost
ai insurance hand adding puzzle as knowledge sharing
insurance ai design options graphic

Design an AI transformation

Sollers can design and plan transformation of AI automation

  • Design process changes and assess their impact on your organization
  • Understand the scope of required AI tools
  • Plan the target architecture roadmap to optimize efforts
  • Define approach to governance to ensure ownership of new areas
  • Understand the costs and benefits of the transformation to make better transformational decisions

Implement the AI transformation

Sollers can help you to

  • Manage the transformation roadmap
  • Configure AI tools and business logic
  • Redefine business processes
  • Redesign UI for business users or clients
  • Implement changes to insurer IT core and front-end systems
ai insurance implementation handling

AI solutions for the insurance industry

At Sollers Consulting, we aim to support our clients in complete transformations of AI automation. We learn and test various AI tools available on the market. We are helping our clients make the best choices of AI tools to maximize value.

Cloud platforms with AI tools




The major cloud providers offer a set of various best-of-breed AI components for addressing different problems of automation. You can think of it as building blocks, which democratises the usage of AI.

Examples: AWS, Azure, GCP.



omni:us Digital Claim Adjuster




The solution enables end-to-end automation of the insurance claim-handling process. It comes with AI components, reference processes and preconfigured business logic.

SEND Smart Submission & Underwriting Workbench



Underwriting workbenches support the underwriter workflow in managing new business, renewals and endorsements. They have various automation features which enhance submission, risk selection, pricing, quoting and underwriting. Some of the features are AI-driven.

Intelligent Document Processing platforms



IDP platforms provide a complete set of functionalities, including AI and NLP, to streamline the entire workflow of extracting information from various types of documents.

Example solutions: ABBYY, Appian, Hyperscience, Indico Data, Tungsten.

Generative AI/LLMs




Generative AI/Large Language Models (LLM), like ChatGPT, can augment experts, perform complex tasks, and improve business processes. In Sollers Consulting, we leverage the capabilities of LLMs to fit the needs of insurers.

Examples: Amazon Bedrock, Google Gemini, OpenAI.

Predictive Analytics




Predictive Analytics employs statistical algorithms and machine learning techniques to analyse historical data, unveil patterns, and predict future events or trends, allowing organizations to gain insights, anticipate outcomes, and make informed decisions. These solutions are integrated into various AI cloud platforms and enterprise decision engine systems, among others.

Contact Us

Send a message
piotr kondratowicz contact
Piotr Kondratowicz
Business Architect

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