Categoría: Technology

More than 9,000 executives, entrepreneurs and investors from around the world gathered at the largest insurtech event in Las Vegas for ITC 2022, a unique opportunity to connect, understand the industry mindset and learn where the market is headed

Over the course of three days, the insurance community came together to showcase the innovations that will transform the industry by increasing productivity, reducing costs, and, ultimately, enriching the lives of policyholders. 

World’s largest insurtech event

For the first time, LISA Insurtech was part of the exhibitors in this, the world’s largest insurtech event. In booth #2879, we were happy to share with many insurance decision makers how we are helping carriers worldwide deliver a better, faster, and simpler claims experience to their customers. 

In addition, our team, led by Gino Volpi, CEO & Founder of LISA Insurtech, had the opportunity of exploring commercial relationships with companies from all around the world and met with investors from across the globe. 

“The conference was a unique experience, jam-packed meeting with current clients, prospects, and investors! ITC is a one-of-a-kind event where you can meet and learn from so many different perspectives in the industry», said Michael Jarrett, Growth Lead of LISA Insurtech.

Main challenges

The first edition of ITC was in 2016, and the industry has definitely come a long way. Last year’s insurtech funding, which approached $15 billion, was double that of the year before. This year, though, is showing a decline in funding, forcing insurtechs to refine their strategies and focus on growing profitability. 

LISA’s model is all about helping insurance optimize its efforts with artificial intelligence and cutting-edge technology.

Today we have more than 50 collaborators in different parts of the world and 19 clients in America and Europe. And this is just the beginning: “ITC2022 was full of good vibes and handshakes with future clients, investors, and colleagues. It was amazing to show what LISA is able to do in the industry with cutting-edge tech and being innovative”, said Cristian Maturana, Head of Sales of LISA Insurtech.

After sharing with the top-notch of the industry, we can’t help but feel very excited about all that is to come.

“These are amazing times for insurtechs and the insurance industries. Digital transformation is a must for carriers. They can’t keep doing what they have done for the last decade and expect different results. They need innovation and technology, but more importantly, they must understand that they must put their customers at the center of everything they do. They need to give insurers a better, faster, and easier experience”, says Gino Volpi, CEO of LISA Insurtech. 

If you want to know more about how LISA Claims can help your insurance deliver a better, simpler, and faster claims experience to their customers, check out this video or schedule a demo with our team.

Once it has been understood that the future of the insurance industry lies in Digital Transformation, it is time to understand a series of new terminologies that are associated with it.

What is an InsurTech?

Etymologically, it is the union of the English words Insurance + Technology. Thus, it is the grouping of companies that move from the traditional business model to the model of the digital era where the Internet rules.

Insurtechs rely on a series of platforms and technological models that help them to reach their ultimate goal, massively expand their coverage and thus reach more and more clients in less time and with more attractive responses and proposals.

What are Startups?

Emerging or new companies that are in an initial phase of growth and development. It is a term that applies to any type of industry.

But what does this have to do with an insurer that has been in business for decades? Well, no matter how long a company has been around, it can become a startup. Why?

When a company moves from the traditional model to the digital era, it turns out that there are so many changes to be made that it is considered a new company from the digital point of view.

The greatest economic impact for a company that changes its way of operating is really at the beginning of the process, that is, at the moment of hiring new human resources specialized in the development of this type of business models.

Over time, there is a latent expense that will always exist because it requires a constant investment. However, the profits will be seen faster than with other types of traditional businesses.

How does LISA Insurtech contribute to the digital transformation of insurance?

With our flagship product, LISA Claims, we transform the slow and tedious claims process with our artificial intelligence solutions.

LISA Claims advantages

• Shorten the liquidation process by 80%.
• Reduces operating costs by 60%
• Increases NPS up to 20%.

As we explained in the previous article, the digital transformation process is not something simple and does not represent an economic cost, at least at the beginning. But it is worth it.

Now we want to explain other relevant aspects of the digital era that must be taken into account by insurers who want to revolutionize and be competitive today: 

1. Mobile: New contracts in minutes

Just as people make purchases of all kinds from their cell phones at home or on the street without having to move to another site, insurers, to join the transformation of the digital age, must offer this type of service.

Therefore, through their web portal, the most recent insurance companies allow the acquisition of their services in a few minutes, without loss of time or unnecessarily long procedures, but without losing their legality.

In the modern world, people want to be able to acquire what they want quickly, so this type of advantage undoubtedly greatly increases the assets of an insurer.

2. Data: Information for progress and development

Many insurers operate in a standard way due to a lack of real and current information on their audiences and new market demands. This may be due to the cost of collecting the information, or because of the difficulty of knowing how to use it to improve various aspects of the products offered by insurance companies.

Nowadays there are tools and systems that facilitate the collection and integration of data.

3. Customization: Everyone hires what he/she needs

In the beginning, insurance companies, since there was reduced market, were able to offer services to each person on an individual basis.

This important characteristic was lost over time and that’s why standard packages and programs were created.

Nowadays, new clients give great weight in their opinions to those services that are highly personalized, since, again, it is another way of getting closer to the clients and their real needs. That is why new offers must be specific to each person.

4. More Customization: Pay for what you use

One of the most striking features of the customization of services offered by insurers is the reduction of premium costs for end users by paying only for what they use and not for complete packages that they will not get the full benefit of.

Finally…

​​It is important to remember that the impact of this digital era has a very large socio-cultural component, and this is something that is constantly changing.

What is fashionable today, or what customers prefer, will be different in a few years, so entering the digital era means opening the doors to a new world of constant and very dynamic changes.

In the case of insurance companies, the one that gets more customers and achieves greater success is the one that adapts to modernity first than the others. Do you want to transform your insurance company and don’t know where to start? Contact us and schedule a DEMO.

The digital era itself is inevitable. However, part of this abrupt and marked change is due to the fact that the new target that is being incorporated into the labor market are people who were born in the technological era.

The Digital Era has a series of aspects that must be evaluated with a great dedication by any of the insurance companies that want to join this time of changes and get a good position in the market. That’s why it’s convenient to carry out a proper review of the most important aspects of the era.

Before starting, it is key to remember that the process of digital transformation is not simple and it’s definitely not something economical. To enter this competition it is necessary to invest a lot of money in studies and human resources if you really want to make it work.

On the next points, we have broken down the most important aspects of the Digital Era that every insurance company should think when transforming:

1. Social: An interconnected world by applications and social networks.

The world is highly interconnected by applications and social networks. If a company wants to start participating in e-commerce it is importan that it first enters the world of social networks.

2. Social: Channel’s Dynamism

The social networks should also serve as interactive channels so that people can express all their doubts before contracting any service, and for this, human personnel are needed to take charge.

The dynamic of social media allows to win followers and have people engage in their publications, which help the company communicate with their potential customers in a direct or indirect way.

3. Mobile: Availability at all times

Most of the people in the world who are active at work have a smartphone or cell phone, which allows them to perform many operations in a few minutes without moving or leaving their homes.

This implementation of the digital era has been joined by large industrial platforms such as banks that allow the movement of money to pay for services or receive it without going to the branches. To this end, they have developed Internet portals and applications that serve as channels between the customer and the company.

The same has already happened with several insurance companies worldwide, as they offer their services and allow instant communication to solve problems in a few minutes.

4. Mobile: Temporary solutions for claims

Through the cell phone and with the help of the appropriate channels, a customer will be able to provide a large amount of data on the claim in real time, such as location, type and magnitude.

In this way, the insurer will be able to offer temporary solutions to its customers, such as a vehicle for the person to travel from the site of the claim in the event of a vehicle collision.

Finally…

The digital era is much more complex than it seems at first glance; it is not simply a matter of digitizing the platforms or the insurance company’s operations.

It involves a process of development and continuous study by people specialized in the subject, since constant innovation is the key to success.

We invite you to read the second part of this interesting topic! Expect it soon.

Applying technologies has been a long overdue process for insurance companies.

Just getting the «house» in order is not easy since there are manual processes and strict government regulations within the house.

However, the 2020 and the pandemic have opened the eyes of the insurance industry. They began to employ digital technologies thanks to investments in insurtech, which has allowed the sector to evolve.

In this article we tell you about some of the most relevant technological applications that will be present in insurance in 2022.

Automation

According to the Mckinsey study, 25% of the insurance industry will be automated by 2025 thanks to artificial intelligence and machine learning techniques.

In fact, the industry is full of bottlenecks and manual processes such as claims processing, fraud detection, customer service, among others.

Some tangible automation use cases include:

• Claims processing

First this processing has several layers, such as review, investigation, adjustment, forwarding or denial of the claim.

For each layer, insurers must process a large volume of documents that can be automated.

With document automation, insurers can extract data from documents, identify fraudulent claims, among others.

Automation with LISA Insurtech

At LISA Insurtech we use AI to interpret images of automobile accidents and estimate repair costs.

In fact, we do the same with damages in the household line of business. 

As a result, claims can be settled quickly and insurers respond up to 10 times faster.

To conclude we can say that there is no doubt that applying technology, although it is not something simple, is an opportunity for growth and revolution.

Although the insurance industry is one of the oldest, it has many opportunities when going digital.

This not only applies to making life easier, but also to making your customers much more satisfied.

Now stay tuned! In our next article you will learn about other important applications that will set a milestone in the insurance industry this 2022.

Expect it very soon!

The insurance industry is one of the oldest sectors in the world and as the years have passed, it has gone through a rather slow metamorphosis. This has led it to stagnate, unlike other companies.

Digitization has been a difficult process for insurers. This is due to the fact that within it there are complicated manual processes to digitize and strict government regulations. 

Despite this, insurance companies began to take advantage of data and digital technologies thanks to investments in insurtech companies.

In that sense, this allowed those digital transformation efforts to result in the evolution of the sector.

Why is digital transformation necessary in insurance?

First of all, we already know that the insurance industry is one of the oldest in the world.

However, new players, business models and demanding customers are forcing insurers to adopt digital technology.

In a second place, this urgency has become more pronounced since the emergence of the pandemic caused by Covid-19.

Next, we find the following two important points to understand the urgency of transforming the insurance sector:

• Increasing importance of being agile at scale:

As competitors implement new solutions, insurers are expected to quickly launch pilots and implement them.

• Customized products and services:

Customer experience is increasingly the key factor for a company to differentiate itself from its competitors.

In addition, according to the 2019 TechSee survey, customers want to quickly manage policy quotes, bill payments and communication.

Why digitize your insurance company with LISA Insurtech?

Certainly and being an insurtech, we are in charge of nurturing the traditional insurance industry with Artificial Intelligence. This in order to accelerate their traditional processes.

Therefore…

We guarantee efficiency, speed, cost savings, security in all processes and we also increase the satisfaction of our policyholders.

Learn how we do this with our flagship product LISA Claims !

Nowadays, artificial intelligence and all that is derived from it, has made possible a great change in companies, since it facilitates their way of operating in more effective and simple ways.

One of the subset techniques of artificial intelligence, known as Natural language processing (NLP), has revolutionized the last few years. It is used to bridge the communication gap between computer and human.

What is PLN?

PLN is a branch of artificial intelligence that helps computers understand, interpret and manipulate human language.

Its first steps

It all started with the idea of creating a translation machine (TM), which was born during the Second World War, in the 1940s. The original idea was to convert one language to another, but using the brains of computers, however, after that came the idea of converting human language into computer language and vice versa.

Similarly, the original language was English and Russian. But the use of other languages such as Chinese emerged in the early period of the 1960s.

Later, there came a dark period for MT/NLP during 1966. This was supported by a report of ALPAC (Automatic Language Processing Advisory Committee), according to which MT/NLP almost died because research in this area did not have the pace at that time. 

However, this condition improved again in the 1980s when the MT/PNL-related product began to deliver some results to customers. After reaching an almost dying state in the 1960s, PLN/MT gained a new life when the idea and need for Artificial Intelligence emerged.

In the 1980s, the area of computational grammar became a very active research field that was linked to the science of reasoning for meaning and the consideration of user beliefs and intentions.

In the period of the 1990s, the pace of PLN/MT growth increased. Grammars, tools and practical resources related to this technique became available for a wide range of industries.

Fun fact!

The history of PLN cannot be considered complete without mention of ELIZA, a chatbot program that was developed between 1964 and 1966 at the MIT Artificial Intelligence Laboratory. It was created by Joseph Weizenbaum.

This was a program that was based on a script called DOCTOR that was arranged for the Rogerian psychotherapist and used rules to answer user questions that had a psychometric basis. It was one of the chatbots that were capable of taking the Turing test at the time.

Incredible, right? We will tell you more about NLP in the next article! Stay tuned

In other of our articles we have explained the great importance of being able to collect data and make decisions based on the study of them, but to get to that point, we must first go through the analysis of that data. That is why in this article we will tell you everything you need to know about it.

So without further ado, let’s get started!

What is data analysis?

It is a process that consists of analyzing information to extract meaningful data from a given set. This analysis technique is carried out with Big data in most cases, although it can be applied to any data set.

The main objective of data analysis is to help people and organizations to make decisions based on patterns, behaviors, trends or preferences, thanks to a collection of data.

A clear example of this is that companies can use analytics to identify customer preferences, buying habits and market trends and then build strategies to address them and manage changing market conditions.

What are the types of analytics? 

According to the bcm.com article, there are multiple analysis methods and techniques for data analysis, but there are four types that apply to any data set:

1. Descriptive: refers to understanding what happened in the data set. As a starting point in any analysis process, descriptive analysis will help users understand what happened in the past.
2. Diagnostics: Consider descriptive analysis and rely on it to understand why something specific happened. It thus allows users to gain insights into the exact information about the root causes of past events, patterns, etc.
3. Prophetic: Predictive analytics will predict what will happen in the future. This will combine descriptive and diagnostic analytics data and use ML and AI techniques to predict trends, patterns, problems, among others.
4. Prescriptive: this takes predictions from predictive analytics and goes a step further by exploring how the predictions will happen. This can be considered the most important type of analytics, as it allows users to understand future events and adapt strategies to handle any predictions effectively.

Finally, we can assure that data is the future, which is why everything related to it, such as big data, data analytics and data science, will help people and industries to deal with a large amount of data and extract valuable information from it.

As data is understood to be very important, it will become essential technology components for any industry.Want to learn about all the things we can do with data? Click here

In our previous article, we gave way to one of the most talked-about topics in recent years. It is data mining and its impact on decision making in many companies.

But to understand much more about what this important topic is all about, it is necessary to know its key concepts:

Getting the best results from data mining requires a variety of tools and techniques. Some of the most commonly used functions include:

• Data cleaning and preparation: here data is transformed into a suitable format for further analysis and processing (such as identification and elimination of errors and missing data).
• Artificial intelligence (AI): these systems perform analytical activities associated with human intelligence (such as planning, learning, reasoning and problem solving).
• Association rule learning: these tools are also known as market basket analysis and are responsible for finding relationships between variables in a data set, such as determining which products are typically purchased together.
• Clustering: is the process of partitioning a data set into a set of meaningful subclasses (called clusters), the purpose of which is to help users understand the natural structure or grouping of the data.
• Classification: This technique assigns elements in a dataset to target categories or classes with the objective of accurately predicting the target class for each case in the data.
• Data analysis: this process evaluates digital information into useful business intelligence.
• Data warehousing: is a large collection of business data that is used to help an organization make decisions. It is the fundamental component of most large-scale data mining efforts.
• Machine learning: This computer programming technique uses statistical probabilities to give computers the ability to «learn» without being explicitly programmed.
• Regression: A technique used to predict a range of numerical values, such as sales, temperatures, or stock prices, based on a particular set of data.

How does data mining work?

A typical data mining project starts with asking the right business question, collecting the right data to answer, and preparing the data for analysis. Success in the latter phases depends on what happens in the former.

Data mining professionals generally achieve reliable and timely results by following a structured process involving these six steps:

1. Business understanding: develop a thorough understanding of the project parameters, including the current business situation, the main business objective of the project and the criteria for success.
2. Data understanding: determine the data that will be needed to solve the problem and collect it from all available sources.
3. Data preparation: preparing the data in the appropriate format to answer the business question, addressing any data quality issues such as missing or duplicate data.
4. Modeling: use of algorithms to identify patterns within the data.
5. Evaluation: determining whether and to what extent the results delivered by a given model will help achieve the business objective. 
6. Implementation: making the results of the project available to decision makers.

Why is data mining so important to us? Thanks to this technology at LISA Insurtech we are able to empower the insurance industry by detecting fraud, segmenting policyholder preference, among many other things!

If you want to know how do we work, click here

The unstoppable digital transformation landed in a wide variety of industries, making them learn from data analysis and its benefits. This is a breakthrough without borders for the insurance industry, which, although it was not prepared for this metamorphosis, has a thousand and one opportunities.

The insurance industry is a competitive scenario among companies, where they seek to attract the clients of those competitors who have not adapted their businesses to the new needs.

If there is one thing we can say for sure, it is that today’s consumers demand new practices and tools to improve their experience. It is therefore normal that there is a flight of customers to companies that do offer immediacy, technology and modernization.

1. Decisions based on data analysis: more effectiveness and lower costs:

 What does this mean?

Transforming data into information to generate knowledge and, in turn, optimize intelligent decision making in business, is a necessary and appreciated tool, because:

It allows us to measure the effectiveness, efficiency and consumer satisfaction in every interaction.

According to the 7puentes.com article, it is known that currently, data is the gateway to the development of new products and services. In the case of the insurance industry, data analysis makes it possible to categorize users and identify what type of services to provide to each of them according to their needs.

Seeking support in machine learning will enable insurance companies to accelerate the risk assessment of a potential policyholder, which is a differentiating factor.

Machine learning techniques support the decisions that underwriters must make:

• Establishing a risk scoring of the new contracting: in this way, the necessary precautions can be taken in the case of a customer with a high risk of suffering an accident, for example. Also to avoid fraudulent applications.
• Defining the variables of greater weight in the valuation of a service with the possibility of risk, without falling into an eventual loss.

This results in reduced costs and improved effectiveness of the insurers’ services. This also offers competitive prices in the market which, in turn, makes it easier to cover indemnities.

2. Customer retention and capture

This point is very relevant because, as we mentioned in the introduction, industries face the great challenge of keeping their users loyal in a competitive and changing environment.

Specifically in the insurance sector, the increase in competition and the emergence of insurtech companies (with lower costs and faster processes than large insurance companies) have led to an increase in customer churn in recent years.

Did you know that incorporating new clients costs up to three times more than retaining current ones? That is why it is essential to anticipate the eventual loss of our clients and proactively seek to retain them.

3. Crosselling and upselling: customer acquisition

The insurance industry has resorted to these two techniques to attract new customers and retain current ones, which favors the personalization of offers.

To achieve the success of these strategies, it is essential to take Big Data into account.

There is still more! Stay with us! We will soon upload the continuation of this interesting topic.