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Digital Transformation in the Insurance Industry: Trends, Examples, and Growth Opportunities

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Last updated on
October 25, 2024

A QUICK SUMMARY – FOR THE BUSY ONES

Digital transformation in insurance: Key takeaways

  • Digital transformation should be a preventive measure, not a crisis response.
  • Outdated or incompatible systems hinder integration, scalability, and can threaten a company's survival.
  • Companies with sluggish, complex infrastructure will be outpaced by more agile competitors.
  • Emerging technologies used in insurance include: AI, predictive analysis, blockchain, Big Data, telematics, Machine Learning.

TABLE OF CONTENTS

Digital Transformation in the Insurance Industry: Trends, Examples, and Growth Opportunities

Introduction

Digital transformation in insurance industry is a fact, and the changes are vital – a lot can be gained, but also lost, very quickly. Many insurance companies experience financial problems because they are not digitally swift enough. They lose market share and growth opportunities, become more and more backward, and slowly get out of the business. Quite often, they look for help when it’s too late. The willingness to undergo digital transformation shouldn’t be a part of a crisis response but rather a preventive measure – as prevention is better than cure.

Keeping a tech stack that is obsolete or incompatible with newer systems, not only makes integration and scalability difficult but also poses a threat to the company’s existence. You won’t go too far with infrastructure and solutions that are overly sluggish and too complex to manage – there are other insurance businesses that will surely outrun you. 

Shifting away from obsolete systems may be a reasonable and inevitable move for any business, but many insurers, too conservative and overly cautious, tend to procrastinate. It’s only when outdated, inefficient, and costly processes eventually lead to a huge productivity decrease and money loss that they start to desperately look for a rescue. Hopefully, not too late.

Digital transformation – why it’s worth it

Digital transformation is way more than just switching to cloud computing and digital workflows – or replacing analog format with digital one (aka digitization). It is – or at least should be – a major, groundbreaking change, underpinning all the aspects of the company’s operations, functions, and processes it is involved in. It should transform and redefine the way an organization delivers value to customers.In brief, digital transformation:

  • makes the whole organization swifter and ready for further changes,
  • enhances product quality and customer experience,
  • fosters innovations,
  • enables or enhances remote working,
  • improves overall efficiency.

There’s a whole lot to get thanks to implementing digital technology, and virtually nothing to lose – provided the right company is in charge of the process.

Digital transformation in insurance – the current state & trends

InsurTech is on the rise, with year-over-year investments in this sector surging from $5.9 billion to $8.1 billion between 2022 and 2023, as KPMG’s Pulse of Fintech report showed. However, the average insurance business is not that eager (or ready) for the new, as nine out of ten find current legacy infrastructure, software, and platforms a barrier to going fully digital.

As for the insurance industry, emerging technologies currently in use include:

  • Artificial Intelligence,
  • Predictive Analytics,
  • Blockchain,
  • Big Data,
  • telematics,
  • Machine Learning.

Digital transformation enables data-driven development and provides insurance organizations with priceless, game-changing insights. Unfortunately, this industry has traditionally been reluctant to modernize. For example, PwC’s Global FinTech Survey showed that although three in four (74%) of insurance companies believed that some part of their business is at risk of disruption, only 43% already had FinTech at the heart of their corporate strategy. 

Currently, the gap between modern, innovative InsurTech companies and traditional old-school agents is only getting larger. Legacy systems still slow down innovation, although insurers do spend hundreds of billions of U.S. dollars on IT per year.

Artificial Intelligence and automation

Insurance companies are turning to artificial intelligence (AI) and automation to make things smoother and more efficient. AI-powered chatbots and virtual assistants are now handling customer inquiries and processing claims. This shift is making it easier for policyholders to manage their insurance needs on their own, resulting in a more customer-friendly experience overall.

AI will disrupt distribution, underwriting, claims, and service as core processes become AI-enabled, creating a “human in the loop” model that increases productivity and allows for higher-quality touchpoints with customers. - McKinsey

Who uses it?

Liberty Mutual: This company uses AI through its Solaria Labs initiative. One of their key AI tools is the Auto Damage Estimator, which uses computer vision to analyze claims photos and quickly assess vehicle damage, providing repair estimates post-accident.

Clearcover: Clearcover employs AI to streamline the claims process. Users can submit claims by taking a few photos and filling out a short form, after which ClearAI quickly processes the claims. This reduces the time and effort required for both customers and the company.

Yas.life: This company develops digital health services for traditional insurers and corporate health management companies. They use AI to create personalized health plans and incentives to promote healthier lifestyles among insured individuals.

Success story: Lemonade

Lemonade uses AI to streamline and enhance various aspects of their insurance processes, from underwriting to claims processing. Their AI-driven chatbot, Maya, handles everything from policy creation to claim management, providing a seamless and efficient experience for users.

Achievements:

  • Lemonade's AI can handle and approve claims in as little as three seconds. This rapid processing has significantly improved customer satisfaction and operational efficiency. For example, in one instance, Lemonade’s AI approved a claim for a stolen coat within three seconds of the claim being filed. This level of efficiency is unprecedented in the traditional insurance industry.
  • The use of AI allows Lemonade to offer personalized insurance policies and services. Customers can get insured within 90 seconds and have their claims paid in just three minutes. The AI-driven approach ensures that the process is user-friendly and transparent, which has contributed to high customer satisfaction ratings.
  • By automating processes, Lemonade has reduced operational costs. This allows them to offer competitive pricing and still maintain profitability. The company's innovative approach has attracted significant customer growth, expanding their user base rapidly.

Lemonade’s successful integration of AI has not only set a new standard in the insurance industry but also showcased the potential of AI to revolutionize traditional business models. Their approach has led to significant market disruption and has paved the way for more insurtech innovations.

Predictive analysis

Predictive analysis is increasingly being used by insurance companies to improve risk assessment, optimize pricing, enhance customer service, and streamline claims processing.

Who uses it?

Swiss Re for predictive underwriting: Swiss Re uses predictive analytics to enhance their underwriting processes. By analyzing large datasets, including medical records, lifestyle factors, and genetic information, Swiss Re can predict mortality and morbidity risks more accurately. This allows for better risk assessment and pricing of life insurance policies.

Allstate for predictive modeling for claims: Allstate employs predictive modeling to enhance their claims processing. By analyzing historical claims data, the company can predict the likelihood of claims fraud and identify patterns that indicate higher risks. This allows Allstate to manage claims more efficiently and reduce fraudulent activities.

Success story: Progressive Insurance

Progressive Insurance, one of the largest auto insurers in the United States, has successfully leveraged predictive analytics to transform its business model, enhance customer experience, and improve risk assessment.

Progressive's Snapshot program uses telematics to collect real-time driving data from customers. This data includes information on driving behaviors such as speed, braking patterns, and time of day the vehicle is driven. Machine learning algorithms analyze this data to predict the risk levels associated with different driving behaviors. This allows Progressive to offer personalized insurance premiums based on individual driving habits.

Achievements:

  • Customers appreciate the personalized approach, as it allows them to potentially lower their insurance costs based on their actual driving performance. This has led to higher customer satisfaction and retention rates.
  • By being a pioneer in using telematics and predictive analytics, Progressive has differentiated itself in a competitive market, attracting tech-savvy customers who value innovation and personalized services.

The success of the Snapshot program has had a significant impact on Progressive's business. The company has reported increased customer engagement and a better understanding of risk factors, leading to more accurate pricing models and a competitive edge in the market.

Blockchain

Blockchain technology offers several transformative applications for the insurance industry, enhancing transparency, efficiency, and trust.

How it can be used?

  • Smart contracts can automatically trigger claims payments when predefined conditions are met, reducing the need for manual processing and minimizing the risk of human error.
  • Blockchain’s immutable ledger ensures that once data is recorded, it cannot be altered, reducing fraud risk. This provides a transparent and verifiable history of transactions and claims.
  • This technology can provide a secure and efficient way to share and verify customer identities, reducing the risk of identity theft and simplifying the onboarding process.
  • With blockchain, companies can facilitate faster and more accurate data exchange between insurers and reinsurers, improving the efficiency and accuracy of reinsurance contracts.

Where it can be used?

  • contracts
  • fraud detection
  • identity verification
  • reinsurance
  • peer-to-peer insurance

Who uses blockchain?

  • AXA’s Fizzy, a flight delay insurance, uses smart contracts to automatically compensate customers if their flights are delayed.
  • Allianz is exploring blockchain to create immutable records of transactions to enhance transparency and reduce fraud.
  • MetLife is leveraging blockchain to streamline the customer verification process.
  • Teambrella uses blockchain to facilitate peer-to-peer insurance, allowing users to create their own insurance groups and vote on claims.
  • B3i (Blockchain Insurance Industry Initiative) is a consortium of insurers and reinsurers using blockchain to improve data sharing and contract management.

Success story: AXA

AXA, a multinational insurance firm, has successfully incorporated blockchain technology to enhance its service offerings and operational efficiency. The company used blockchain in Fizzy - flight delay insurance.

Fizzy is an automated and blockchain-based insurance product that provides compensation for flight delays without the need for customers to file claims. AXA leverages Ethereum blockchain technology to record and verify insurance contracts. The blockchain ensures transparency, security, and immutability of the data. Customers purchase flight delay insurance, and the smart contract on the Ethereum blockchain tracks flight data in real-time. If a flight is delayed beyond the specified threshold, the smart contract automatically triggers a payout to the customer without any manual intervention.

Achievements:

  • Fizzy significantly improves customer experience by eliminating the need for filing claims and reducing the payout waiting time. The automation ensures that customers are compensated quickly and fairly.
  • AXA’s implementation of blockchain with Fizzy positions it as a leader in insurtech innovation. This has attracted tech-savvy customers and set a new standard in the insurance industry.
  • The success of Fizzy demonstrates the potential for scaling blockchain solutions across other insurance products and services, paving the way for further innovations in the industry.

The deployment of Fizzy has proven that blockchain technology can revolutionize insurance processes by making them more efficient, transparent, and customer-friendly. It has set a precedent for other insurance companies to explore and implement blockchain solutions.

Big Data

Big data is revolutionizing the insurance industry by providing deeper insights, improving risk assessment, enhancing customer experience, and driving operational efficiency.

How is it used?

  • By analyzing vast amounts of data from various sources such as social media, telematics, wearables, and IoT devices, insurers can create more accurate risk profiles.
  • Big data analytics can detect anomalies and patterns that indicate fraudulent activities, helping insurers reduce fraudulent claims.
  • By analyzing customer data, insurers can offer personalized products and services that meet individual needs and preferences.
  • Big data enables the automation of claims processing, reducing the time and cost associated with manual claims handling.

Where to use it?

  • risk assessment
  • fraud detection
  • personalization
  • claims processing

Who uses it?

  • Allstate uses its telematics program, Drivewise, to collect driving data and assess risk, allowing for more personalized insurance premiums based on driving behavior.
  • CNA Insurance employs big data analytics to identify potentially fraudulent claims by analyzing historical data and patterns.
  • MetLife uses big data to gain insights into customer behaviors and preferences, allowing for more personalized insurance offerings.
  • Zurich Insurance uses big data to streamline claims processing, resulting in faster and more efficient handling of claims.

Success story: Allstate

Allstate Corporation, one of the largest publicly held personal lines insurers in the United States, has successfully integrated big data analytics into its operations to enhance risk assessment, improve customer experience, and streamline processes.

Allstate’s Drivewise program uses telematics to collect data on driving behaviors, such as speed, braking patterns, and the time of day the vehicle is driven. The program utilizes big data analytics to process this information and assess individual risk levels. Drivers install a telematics device or use a mobile app that tracks their driving patterns. This data is transmitted to Allstate’s servers, where it is analyzed to determine the driver’s risk profile. Based on this analysis, Allstate offers personalized insurance premiums that reward safe driving behaviors.

Achievements:

  • By analyzing detailed driving data, Allstate can more accurately assess the risk associated with individual drivers. This leads to more precise underwriting and pricing, reducing the likelihood of losses due to mispriced policies.
  • The program also provides drivers with feedback on their driving habits, helping them improve their safety on the road.
  • Big data analytics streamlines the underwriting process by providing underwriters with comprehensive risk profiles. This reduces the time and resources needed for manual assessments and increases operational efficiency.
  • The innovative use of big data and telematics has positioned Allstate as a leader in the insurance industry. Their commitment to leveraging technology for better service and pricing has attracted tech-savvy customers and set a benchmark for competitors.

The successful implementation of big data analytics through the Drivewise program has significantly impacted Allstate's business. The company has reported higher customer retention rates, reduced operational costs, and improved risk management. The use of big data has enabled Allstate to offer competitive and personalized insurance products, enhancing its market position and driving growth.

Telematics

Telematics refers to the integration of telecommunications and information technology to monitor and manage remote objects, such as vehicles. In the insurance industry, telematics is primarily used to track driving behavior, providing insurers with detailed data that helps in assessing risk and personalizing insurance premiums.

How is it used?

Telematics devices, often in the form of a plug-in device or a mobile app, collect data on various driving behaviors, including speed, braking, acceleration, and the time of day the vehicle is driven. This data is transmitted to insurers, who analyze it to assess the risk level of each driver. Based on the collected data, insurers can offer personalized premiums that reward safe driving habits and penalize risky behaviors. This leads to more accurate pricing of policies.

In the event of an accident, telematics data can be used to reconstruct the incident, providing detailed insights into the circumstances of the crash. This helps in accurate and faster claims processing.

Telematics data can identify inconsistencies in claims, helping insurers detect and prevent fraudulent activities.

Who uses it?

  • Progressive Insurance: Progressive’s Snapshot program is a well-known telematics-based initiative that collects driving data to offer personalized insurance premiums. The program rewards safe driving habits with lower insurance rates.
  • Allstate: Allstate’s Drivewise program uses telematics to monitor driving behaviors and provide personalized feedback to drivers. Safe drivers can earn rewards and discounts on their premiums.

Success story: Allianz SE

Allianz SE, headquartered in Munich, Germany, is one of the world's largest financial services groups, providing insurance and asset management services.

Allianz’s BonusDrive is a telematics program that uses a smartphone app to collect data on driving behavior, including speed, braking, and acceleration patterns. The app provides feedback to drivers and scores their driving habits. Policyholders download the BonusDrive app and consent to have their driving monitored. The app records driving data and provides real-time feedback to help drivers improve their habits. Safe driving behaviors are rewarded with premium discounts.

Achievements:

  • By collecting detailed driving data, Allianz can more accurately assess the risk profile of individual drivers. This leads to more precise underwriting and fairer pricing.
  • The BonusDrive app offers personalized feedback and tips to help drivers improve their driving skills. This not only enhances safety but also increases customer engagement and satisfaction.
  • Telematics data provides an objective record of driving behaviors and incidents, making it easier to detect and prevent fraudulent claims. This helps reduce costs associated with fraud.

By offering a telematics-based insurance product, Allianz differentiates itself in a competitive market. The innovative use of technology attracts tech-savvy customers and enhances the company’s reputation as a forward-thinking insurer.

Machine Learning

Machine learning (ML) is transforming the insurance industry by providing advanced analytics, predictive modeling, and automation.

How is it used?

  • Machine learning algorithms analyze historical data and predict future risks, enabling more accurate underwriting and pricing.
  • ML models can automate the claims process by analyzing claims data, identifying patterns, and making decisions about claims approval or denial.
  • We can detect unusual patterns and anomalies in claims data, which helps to identify fraudulent claims.
  • Machine learning also analyzes customer data to provide personalized insurance products and recommendations based on individual needs and preferences.
  • We can power chatbots and virtual assistants that can handle customer inquiries, provide quotes, and assist with claims, improving customer service and engagement.

Who uses it?

  • Zurich Insurance leverages machine learning to analyze extensive datasets and enhance its underwriting processes, leading to more accurate risk assessments and pricing.
  • Lemonade uses its AI chatbot, Jim, which incorporates machine learning to process claims quickly and efficiently, reducing the time taken to settle claims and enhancing customer satisfaction.
  • GEICO's virtual assistant, Kate, powered by machine learning, helps customers with policy inquiries and claims, improving customer service efficiency and engagement.

Success story: Helvetia Insurance

Helvetia Insurance, a leading Swiss insurance company headquartered in St. Gallen, has successfully implemented machine learning (ML) to enhance its operations and customer service.

Helvetia uses machine learning algorithms to automate and streamline the claims processing workflow. By analyzing historical claims data, the ML system can predict and assess the validity of claims, expedite processing, and detect potential fraud. The ML system processes incoming claims data, identifying patterns and anomalies that help in deciding whether to approve, reject, or further investigate claims. This significantly reduces the time required for claims assessment and increases accuracy.

Helvetia employs ML to analyze customer data and provide personalized insurance recommendations. The system evaluates customer behaviors, preferences, and risk profiles to tailor insurance products to individual needs.

Achievements:

  • Helvetia has significantly reduced the time needed for claims processing through automation. The ML system's ability to quickly analyze data and make decisions reduces the administrative burden and speeds up the claims resolution process.
  • By automating routine tasks and improving accuracy in claims processing and fraud detection, Helvetia has achieved significant cost savings. This allows the company to allocate resources more efficiently and improve profitability.

The company has reported higher efficiency, reduced costs, improved fraud detection, and enhanced customer satisfaction. The use of ML has allowed Helvetia to stay competitive and continue providing high-quality services in the rapidly evolving insurance market.

Other trends that can help your business fly

Digital transformation in insurance has many facets and layers and can be performed on many levels. There are a lot of examples of interesting and useful solutions in this area that turn the insurance or finance-related businesses into modern, or even innovative, entities.

When it comes to general trends in the insurance industry, it’s good to keep in mind that, nowadays, clients want to actively participate in the insurance process. Also, they want the claims procedure improved and shortened – and InsurTech is a perfect means for that.

One way to reduce the time to process applications is using online questionnaires – which also lets insurers’ clients monitor their application status online. Another is choosing remote operations and online consultations instead of in-person visits and inspections. Drones are very useful in that regard, doing claims evaluations and inspections, and reducing claims processing times greatly.

Another breakthrough is digital documents that use optical character recognition (OCR) technique which lets add and check data electronically. Also, a data-driven approach helps insurers understand market trends and customer preferences better, and reduce costs, e.g. due to process automation.

Digital transformation is also marked by a shift toward multi-cloud solutions and environments. Its use covers everything from chatbots and applications for faster processing of claims, complaints, and returns through fraud detection and risk management to lead generation tools.

Legacy insurance system modernization

One of the aspects that often makes a huge difference for the insurance companies, is simply shifting away from the obsolete systems. Legacy systems, often outdated and inflexible, hinder innovation, efficiency, and customer satisfaction.

API adoption

Integrating new technologies with existing systems through APIs allows insurers to extend the functionality of their legacy systems without a complete overhaul. APIs can enable legacy systems to communicate with new digital platforms, facilitating the adoption of customer portals, mobile apps, and other digital services.

Cloud migration

Migrating legacy systems to the cloud offers scalability, reduces infrastructure costs, and improves data accessibility and security. However, there are various cloud migration challenges businesses need to be prepared for.

Example: AXA moved its legacy applications to the cloud, resulting in improved system performance, cost savings, and enhanced disaster recovery capabilities.

Microservices architecture

Breaking down legacy systems into microservices allows insurers to update and deploy individual components independently, increasing agility and reducing downtime.

This architecture improves scalability, flexibility, and the speed of deployment. It allows for continuous integration and continuous delivery (CI/CD), reducing downtime and enhancing the ability to update specific parts of an application without affecting the whole system.

Example: Allianz adopted a microservices architecture to modernize its claims processing system, enabling faster updates and more efficient handling of claims.

Robotic Process Automation

RPA can automate routine tasks, such as data entry and processing, reducing manual workload and minimizing errors.

Example: Zurich Insurance implemented RPA to automate policy administration tasks, leading to increased efficiency and reduced processing times.

Data modernization

Modernizing data infrastructure by creating data lakes and using advanced analytics helps insurers gain insights and make data-driven decisions.

Example: MetLife transformed its data architecture by implementing a data lake, enabling advanced analytics and better customer insights.

Continuous Integration and Continuous Delivery implementation

Implementing CI/CD pipelines allows for automated testing and deployment of code changes, reducing the risk of errors and speeding up the release cycle.

Example: State Farm has adopted CI/CD practices to streamline the deployment of updates to its legacy systems, resulting in faster and more reliable software releases.

Infrastructure as a Code

IaC enables the automation of infrastructure provisioning and management, making it easier to replicate environments and ensure consistency across deployments.

Example: Allianz uses IaC to manage its cloud infrastructure, enabling rapid provisioning and scaling of resources as needed.

Success story: Helvetia insurance

Modernization approach:

  1. Cloud migration: Helvetia migrated its core applications to the cloud, enhancing scalability and reducing infrastructure costs.
  2. API integration: The company implemented APIs to enable seamless communication between legacy systems and new digital platforms.
  3. Data modernization: Helvetia created a data lake to consolidate data from various sources, enabling advanced analytics and real-time insights.
  4. Automation: Implemented RPA to automate repetitive tasks, such as policy administration and claims processing.

Benefits achieved:

  • Automation and cloud migration reduced processing times and operational costs.
  • Improved digital services and personalized offerings led to higher customer satisfaction.
  • The company could quickly adapt to market changes and regulatory requirements.
  • Reduced maintenance costs and improved resource utilization resulted in significant savings.

Why transitioning to the new tech stacks is worth it?

  • Modern tech stacks allow insurance companies to rapidly adapt to changing market conditions and customer needs, fostering innovation and competitiveness.
  • Advanced technologies enable personalized and seamless customer interactions, enhancing satisfaction and loyalty.
  • Automation, cloud computing, and microservices reduce operational costs and improve efficiency, enabling insurers to allocate resources more effectively.
  • AI, ML, and big data analytics provide valuable insights that inform strategic decisions, improve risk assessment, and enhance underwriting accuracy.

Digital transformation in the insurance industry: who can help you

Digital transformation is not a piece of cake – and should be taken care of by professionals with the right amount of expertise and experience. This is a meticulous process that requires proper work ethics, versatility, and being detail-oriented from the very beginning till the successful end.

For this reason, the digital transformation project should be handled by companies rooted in Western culture. Poland is a Central European country that belongs to the West in geographical, political, and civilizational terms. Overall, the highlights of Poland include:

  • a great number of brilliant software engineers, 
  • business-friendly tax regime, 
  • skilled labor force with superb knowledge of English, 
  • high standards of work, 
  • good institutional framework,
  • employment flexibility (e.g. project-based, long-term, temporary, B2B contracts),
  • easy travel and great infrastructure, with a vast highway network and 12 international airports.
  • political stability,
  • membership in renowned international organizations (such as the EU, NATO, UN, and OECD),
  • adhering to EU standards and regulations, including GDPR.

All of these features make Poland a perfect place for investors and businesses. They can benefit from Western qualities and save a lot of money when compared to Germany, Switzerland, or Austria. No wonder Poland was ranked 8th globally and 3rd in Europe on the list of the world’s best countries to invest in or do business for 2024.

Another thing western companies most often excel at, is software delivery.

Here's how it should be approached:

Digital transformation for insurance wrapped up

Changes in the insurance market are rapid, so it’s good to take the bull by the horns and stop putting things off for later because later it may be too late. The stake is very high, and losing growth opportunities is only one of many problems that may arise.  These days, there’s no way out of the digital transformation. The examples of IKEA, LEGO, Microsoft, and Audi show that the process can bring tangible business results and readiness for future developments and market changes. And what’s the alternative?

More than half of employees have reported dissatisfaction in the workplace due to outdated, obsolete, and unnecessarily complex systems. These systems can involve additional hidden costs via staff turnover, recruitment, and training. – (State of Software Modernization 2024 Report)

And these costs, truly staggering, can overburden and ruin any insurance business:

It is estimated that legacy systems cost businesses across the globe $2.6 trillion every year. 70% of IT budgets are consumed by this maintenance requirement alone. – (State of Software Modernization 2024 Report)

What’s worse, issues related to skipping digital transformation tend to accumulate, which inevitably leads to further problems:

Legacy code, a strategy of quick fixes, or IT demand outstripping supply, often leads to an unintentional accumulation of technical debt within organizations. As this debt builds, it becomes more complex to resolve. – (State of Software Modernization 2024 Report)

However, it’s not impossible. There are many cases when Brainhub helped businesses of various sizes and industries modernize and get on the fast track to success in the digital era. If you, too, are looking for a breakthrough, go for the digital transformation for insurance.

<span class="colorbox1" fs-test-element="box1"><p>Don't embark on the path to legacy modernization without proper, qualified help. Our team prioritizes rapid iterations and extensive, automated testing. If this resonates with you, let's talk software.</p></span>

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Authors

Olga Gierszal
github
IT Outsourcing Market Analyst & Software Engineering Editor

Software development enthusiast with 7 years of professional experience in the tech industry. Experienced in outsourcing market analysis, with a special focus on nearshoring. In the meantime, our expert in explaining tech, business, and digital topics in an accessible way. Writer and translator after hours.

Leszek Knoll
github
CEO (Chief Engineering Officer)

With over 12 years of professional experience in the tech industry. Technology passionate, geek, and the co-founder of Brainhub. Combines his tech expertise with business knowledge.

Olga Gierszal
github
IT Outsourcing Market Analyst & Software Engineering Editor

Software development enthusiast with 7 years of professional experience in the tech industry. Experienced in outsourcing market analysis, with a special focus on nearshoring. In the meantime, our expert in explaining tech, business, and digital topics in an accessible way. Writer and translator after hours.

Leszek Knoll
github
CEO (Chief Engineering Officer)

With over 12 years of professional experience in the tech industry. Technology passionate, geek, and the co-founder of Brainhub. Combines his tech expertise with business knowledge.

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