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Insurance analytics solutions for the digital insurance age

In today’s economic climate, insurance is a critical safety net for secured living. Insurers are using various instruments to modernize the scope of this life-affirming tool. Insurance analytics solutions are a classic example here. Over time, the use of analytics in insurance business has ushered in digital transformation in the insurance industry. And, the adoption of insurance data analytics software has helped speed up the process.

Let’s understand with an example. Suppose you run an up-and-coming real estate agency that rents/sells houses to people. To promote your business, you do some local, offline marketing. You also send your sales staff for door-to-door lead generation. But, this ends up involving a high cost & time commitment from your end. And, conversion also turns out to be sluggish.

Then your friend advises you to set up a website and develop a social media roadmap, i.e., go digital. The digital-first strategy helps you scale up in a short span of time. You then proceed to use web analytics to crack the buyer psyche and fuel your business forward. In insurance too, it’s much the same when you leverage insurance analytics solutions.

What are insurance data analytics solutions?

Insurance data analytics solutions are practices that identify, collate, and analyze insurance customer data. The idea is to optimize value & retention and minimize risk & cost for the insurers. Far removed from traditional practices, insurance analytics solutions have been a disruption for the insurance industry.

The COVID-19 pandemic has especially propelled digital insurance in the spotlight. The latter has a major role to play in ensuring holistic human & economic well-being. And, its effects are also far-reaching. From ensuring remote access and procedures to enhancing user security. It further helps insurers SWOT analyze emerging markets and develop crisis-proof continuity plans.

According to market research, the global digital insurance platform market size was valued at $96.34 bn in 2020. By 2030, the market is expected to reach $279.51 bn. This represents a CAGR of 11.3%.

Why does the digital insurance industry need insurance analytics solutions?

  1. Increased sales productivity
  2. Tailored policy marketing
  3. Improved insurance underwriting
  4. Accelerated claims management
  5. Strengthened fraud detection

Data analytics has forever been instrumental in driving insights from raw business data. Today, analytics is at the heart of almost every industry, and insurance is no exception. Smart insurers are shifting toward core processes digitization, cloud-native storage, and dynamic sourcing models. Given the economic climate, today’s insurers need to scale up toward this. And, insurance analytics solutions offer just that.

Here are 5 ways analytics spearheads digital transformation in the insurance industry:

1. Increased sales productivity

Conventional sales tactics like cold calling and door-to-door pitching do not always guarantee a sale. To address this, modern insurers are leveraging insurance data analytics software solutions.

CRM software, for instance, extracts insights from unstructured user data for data-driven prospecting. This, in turn, saves the insurer’s time and effort to be spent otherwise on qualifying leads.

Analytics today is fueling digital transformation in insurance. Did you know, acquisition is 5x costlier than retention in the insurance industry? Customers satisfied with faster service are thus more likely to renew their policies. Insurance analytics is delivering market share and profitability to insurers and tangible value to customers.

2. Tailored policy marketing

Customers like offerings tailored to their needs. Insurance data analytics software have the ingenuity to execute personalized marketing programs. Analysis of buying behavior, market trends, past investments, and even health information helps in the application of business analytics to insurance businesses. Personalized capabilities help businesses reach customers using the right channels and timelines. Predictive insurance analytics also enables them to run personalized upselling and cross-selling campaigns.

This makes insurers gain an edge over their competitors. Moreover, digital-first insurance is available 24*7 to enable seamless transactions. It becomes easier to garner customer engagement and loyalty this way.

3. Improved insurance underwriting

Underwriting is a vital process in insurance, stock markets, and banking. In insurance, underwriters evaluate risk and determine the feasibility of insuring a customer. They determine the insurance cover and premium using factors like the client’s income, age, medical conditions, vehicle type, property type, location, etc.

Smart insurance analytics software plugs in underwriting analytics for this. Take NLP (natural language processing) for example. NLP helps verify a customer’s digital presence. Such intuitive tools help insurers with a 360-degree view of clients’ creditworthiness and risk per policy ratio. More recently, insurance analytics solutions have also been helping in risk scoring and also premium & insurance coverage calculations.

4. Accelerated claims management

The claims settlement process is another critical step in insurance. Insurers must check off an extensive checklist before paying out the claim amounts. Traditionally, customers have always wanted this process to be faster and smoother.

Today – thanks to the application of analytics in insurance businesses – claims settlement has sped up. Analysis of claims and claim histories facilitates instant pay-outs, scoring, prioritizing, and processing claims basis experience and loss type. Insurance analytics also brings with it the automation of redundant tasks. This is particularly useful for handling client emergencies despite the ad-hoc analyses involved. Insurance analytics solutions can automate situation-specific responses and information extraction using advanced APIs.

Indeed, these measures are synonymous with the digital transformation of the insurance industry.

5. Strengthened fraud detection

Fraudulent claims, identity theft, and hacking attacks are commonplace in the insurance industry. Such erroneous filings cause financial losses to insurers and affect relationships with customers. A robust fraud detection and prevention mechanism is hence non-negotiable for insurance providers. Predictive analytics, a modern insurance analytics solution, is instrumental in detecting potential fraud. Its modeling algorithms (with ML & AI) along with BI tools have contributed to the digital transformation in insurance.

Insurance data analytics software essentially helps establish a rigorous process of passing claims. It cross-verifies each step with client history using data & text mining.

Welcome to the digital era of insurance

The insurance industry thrives on data. Insurers have to process and handle huge amounts of data every day. And, this is more so true in today’s age of big data. Toward this, insurance analytics solutions are engendering digital transformation in the insurance industry. Digital-first insurers today are future-proof.

An expert IT consulting firm that understands the insurance industry can help you dig deeper into the benefits of insurance analytics solutions.

Insurance analytics solutions are one of Estuate’s core specializations

Our team of certified SMEs has worked on 100+ digital insurance projects. These projects involved strategic use of insurance analytics software like Zendesk, AWS, and Java. We have advanced data management and analytics tools to help with process organization, mining, and engineering in the insurance industry.

If you are looking to leverage business analytics for your insurance business, please feel free to visit us. We are right here to help.

Do you think insurance analytics solutions are helpful compared to traditional insurance practices?

Top 5 data analytics service trends for 2022 and beyond

The 5 biggest data analytics service trends for 2022 and beyond

Big data stands at the focal point of most modern businesses. What it does for an enterprise’s growth, its analytics does for the business’s development. The boom of business intelligence platforms (BIPs) and BI software requirements bear testimony. Data analytics services today are incomplete without self-service business intelligence tools.

As 2021 begins to end, we must start monitoring data intelligence service trends that are going to dominate 2022 and beyond. Let’s look at the innovations that will soon be turning data into insights.

‘Veracity in versatility’ is the feature you should root for when looking for a BI SaaS tool in 2022. Smart analytics solutions help in driving insights and closing business decisions with adroitness. An efficient BI reporting tool also engages teams across your organization. Digital transformation becomes more of a culture change as a result.

According to Finances Online, 60% of companies feel that big data analytics improves process and cost efficiency.

In the digital COVID-19 world, 57% of C-suite executives have been exploring various data intelligence tools to stir business growth.

The years ahead are sure going to disrupt further roads to innovation. Here are the top 5 trends in data analytics services for 2022 and beyond.

1. Self-service analytics will strengthen man-machine partnerships

Modern data analytics service is the perfect blend of technical and human intelligence. And, self-service business intelligence tools are its manifestation. These tools equip you to glean actionable insights using a sound business intelligence platform. By generating real-time reports, they guide where to look and which areas to address first. The automation of data and analytics in recent times has made self-service BI tools even more pivotal in reducing costs of operation.

This process of fact-based decision-making is a smart business move. It’s going to stay around for some time now. It facilitates easy interpretation of data for your technical and non-technical teams alike. The rise of decision intelligence (hybrid of rule-based approaches and AI & ML-based modern analytics) is a classic case in point. So for the right analytical capabilities, make sure to opt for a self-service BI tool.

Big data will continue to be a big deal for businesses. Read how big data has been changing your industry.

2. Predictive analytics will disrupt BI SaaS tools

The modern business milieu will continue to hustle – not only to know what data says today but also to know what data might be saying tomorrow. Goes without saying, predictive analytics is the game-changer that will continue to influence decision-making in the times to come. In 2020 itself, 52% of companies across the world used predictive analytics to optimize operations as a part of business intelligence platform solution.

Analytic process automation (APA) has accelerated both predictive and prescriptive analytics. X Analytics (a term coined by Gartner) will be clubbed with AI and other techniques in the recent future for predicting business crises and opportunities. Such business intelligence platforms would work by leveraging varied structured and unstructured data.

A sound big data enterprise analytics provider will continue to offer the convenience of operational reporting. Fast data analytics auto-generates comprehensive reports so that your teams can focus on core routine activities. Self-service BI tools assemble data from multiple sources for dynamic dashboarding.

The 5 biggest data analytics service trends for 2022 and beyond
The 5 biggest data analytics service trends for 2022 and beyond

3. Cloud migration will be a key BI software requirement

The future belongs to cloud-native analytics. A sound BI solution provider must offer seamless data migration services from premise to your desirable SaaS cloud. The migration of legacy data should be equally coherent.

In the face of the pandemic, cloud operations will continue to be necessary for streamlining operations. According to Gartner, cloud-based AI will increase file-fold momentously by 2023. AI would be one of the top workload categories in the cloud. Cloud innovations from there on must complement your on-premise products platform/s.

Businesses will also go for in-memory computing for scaling data in real time and addressing storage limitations.

4. Advanced analytics will further the big data game

Present-day BI software requirements place prime importance on the inclusion of advanced analytics. Deliverables get optimized when your business intelligence platform supports advanced data management methodologies.

There are myriad advanced analytics modules that are going to frame the big picture in 2022. NLP & conversational analytics (that captures chatbot and audio data cues) and graph analytics (that leverages graphs) are some examples of this. Your BI software requirements must be in line with the latest analytical deployments.

5. Data will be more mobile and visible in Augmented Reality

On-the-go access to data analytics will be a key component of futuristic data analytics services. With bookmarks, widgets, and Face ID enhanced security, mobile data analytics will help close business decisions faster than ever before.

Additionally, the fusion of Augmented Reality would help in viewing datasets and dashboards in interactive real-world simulations. This would make working on smaller screens both convenient and intuitive.

Read what to look for in your mobile business intelligence tool.

Impact of data analytics services - some statistics to know for 2022 and beyond
Impact of data analytics services – some statistics to know for 2022 and beyond

Incorta is a modern and lightning-fast business intelligence solution

Incorta’s self-service business intelligence tool is the perfect mix of data visualization, reporting, and analytics. A simple Incorta integration helps to derive real-time business insights from complex datasets. With Incorta, you will be well-prepared for whatever the industry demands in 2022 and beyond – fast data loading, mapping, ETL processing, and more.

Watch Incorta’s expertise in big data analytics solutions.

Estuate is a premier Incorta implementation partner

Our Incorta engagement is driven by BI experts equipped with best-in-class partner support. We address 360-degree BI software requirements (from management to reporting). In the process, we support business journeys from being data-driven to being driven by insights. Be it for large digital transformation projects or smaller sandbox initiatives, our data analytics services are customizable for all.

  • 300+ data platforms, analytics, and ETL projects
  • 300+ archiving project rollouts
  • 30+ in-house Incorta architects and platform engineers
  • 20+ Incorta accelerators in visualization and analytics
  • 15+ Incorta implementations

Here is a crisp compilation of our capabilities in the business intelligence arena.

if you are looking for experts to help you with your business intelligence needs, we’re right here to help.

Which trend do you think will be the most significant for data analytics services in 2022?

Test Automation in Agile Product Development

The ongoing demand for user-friendly, cutting-edge technology business applications has compelled software companies to deliver stable, cost-effective products in shorter time frames. Aiming for extraordinary product speed without compromising product quality is often a challenge for most companies. As a consequence, when it comes to product development, businesses understand the value of test automation in achieving both product quality and a faster time to market. With an inevitable arbitrate between quality and time-to-market, test automation often outperforms conventional testing methods and helps businesses stay ahead of the competition.

Need for Automation Testing

Product creation is a time-consuming process. When it comes to software development, we absolutely cannot ignore testing because it is such an essential part of the process. Though the agile method of product development is a quicker, less expensive, and better approach, it is vital to automate the testing processes, which saves time and offers insight into errors that manual testing methods might not be able to detect. Automation has more tremendous advantages than conventional testing methods, enabling businesses to develop high-quality products faster and with fewer defects. Companies that use agile development methods employ automation testing to handle continuous development and deployment.

Automation Testing Benefits in Agile Development

Automation testing serves as the basis of Agile software development methodology because of the benefits that it offers. Automation enhances the revenue, brand recognition and retention of customers.It aids companies in meeting industry standards, establishing market authority, and ensuring the timely delivery of high-quality software or applications.

Here are some substantial benefits of implementing automation in agile development.

Quicker Go To Market

Automation enhances the overall efficiency of the product development. Since testing is performed at each stage of the agile process, any issues or bugs detected are corrected early. This saves significant time and reduces the software’s time to market. Automated tests are quick to complete and can be repeated any number of times. Automation testing allows for more frequent updates, faster app improvements and enhancements, a shorter product development cycle, and faster time-to-market delivery.

Accelerated Speed & Accuracy

Test automation reduces human errors dramatically, resulting in more accurate test outcomes. Automated test cases are reusable, meaning they can be run several times in the same or different ways. Automation allows test practitioners to focus on more complex, case-specific assessments while automated software performs routine, often redundant, and time-consuming tests. Automation thus reduces time and effort by delivering results more quickly.

Higher Test Coverage & Performance

Automated software tests vastly increase software quality by increasing the scope and depth of testing. It allows for more detailed analysis and evaluation of various software components, which is rarely possible through a manual testing approach. With automated testing, you can quickly build a large number of test cases, even complicated and lengthy ones. It enables you to execute hundreds of automated test cases at once, allowing you to quickly test the app across various platforms and devices. This is something you can’t do if you decide to test the application manually. Furthermore, automatic tests can be performed with little human intervention, resulting in greater resource efficiency.

Cost Reduction

In the long run, automated testing is less expensive because once you’ve developed the test scripts, you can reuse them at any time without incurring extra costs. Although automated agile testing is often seen as an expensive endeavor, the initial investment in automation will pay off quickly. The return on investment is measured by the number of automated tests; the higher the count, the higher the ROI. Furthermore, defect documentation in each sprint and routine repository maintenance contribute to early defect identification, which decreases post-production failures and, as a result, project costs.

Test Automation Challenges

Despite the numerous advantages of an automation framework, implementing test automation is not easy. While there are multiple advantages to product engineering automation, there are numerous challenges when it comes to implementing automation testing in an agile environment. The most significant barrier is the upfront expense, which includes training, tooling, configuring, automating, and so on. Also, legacy applications may not be compatible with newer DevOps and Test Automation tools. Since Open Source tools are widely used for automation, a number of security concerns are raised. As a result, a well-organized test automation process may help mitigate these issues.

Agile practices lead companies to better and more advanced software development. The approach to automation testing in an agile environment is determined by the project’s requirements, as different projects need different automation tools. To get the most out of agile automation testing, we suggest that businesses looking to automate should find a strategic partner with prior experience in product engineering automation to increase their chances of success. One can find many IT service providers who excel in automation testing services, and Estuate is one among them. Consult our experts to learn how to increase efficiency and productivity with a well-thought-out automation strategy.

Another Mega Data Breach. This Time It’s Quora

Quora says 100 million users hit by a malicious attack. Here are the facts.

2018 was the year of massive technology advancements. From where we started this year to where we have come, the progress has been phenomenal. We saw some of the most breakthrough technology trends, such as Artificial Intelligence, Blockchain, Natural Language Processing and Internet of Things making it big in the business world. But at the same time, 2018 has also been a year of some of the most shocking and alarming cybercrimes.

Although the Facebook data breach made the most news, there were bigger cyber security incidents at several other top business houses including Panera, Under Armour and even Aadhar and Marriott International to name a few. These data breaches are believed to have compromised personal information of hundreds of millions of users and customers. And now, the hackers are back with a major data breach; this time at Quora.

Launched in 2010, Quora is an online community where people can post questions related to over 400,000 topics and get answers/advice from others. Over the years, Quora has grown to become the biggest online Q&A portal with at least 300 million monthly users and 300 million unique monthly visitors.

The company recently disclosed a mega data breach stating that nearly 100 million users were affected by unauthorized access to one of its systems by a malicious third party. The breach is said to have occurred on 30th November, 2018. Soon after the incident was confirmed, the Quora team notified its potentially affected users through an email.

“On Friday we discovered that some user data was compromised by a third party who gained unauthorized access to our systems. We’re still investigating the precise causes and in addition to the work being conducted by our internal security teams, we have retained a leading digital forensics and security firm to assist us. We have also notified law enforcement officials”, the email stated.

According to the initial investigation, the hackers could have possibly gained access to the following information.

  • Account and user information including name, email address, IP, user ID, encrypted password, user account settings, personalization data

  • Public actions and content including drafts, such as questions, answers, comments, blog posts, upvotes

  • Data imported from linked networks like contacts, demographic information, interests, access tokens

  • Non-public actions, such as answer requests, downvotes, thanks, etc.

“It is our responsibility to make sure things like this don’t happen, and we failed to meet that responsibility. We are continuing to work very hard to remedy the situation, and we hope over time to prove that we are worthy of your trust”, the email further stated.

Quora hasn’t disclosed any information about who the hackers might be. However, as an immediate corrective action, Quora invalidated the accounts of all the affected users and suggested them to reset their passwords.’

What does it teach us?

With each incident we’re reminded that we’re not completely secure. Every data breach is an alarm; a signal to never let your guard down. There are hidden lessons for us in every major data breach. They teach us that

  • Implementing modern technology comes with potential risks and these risks should be acknowledged with appropriate measures.

  • Cyber-attacks can have huge repercussions and can lead to major reputational loss. Building cyber resilience is not a good practice anymore, it is a must-have.

  • Insider threats and minor negligences can lead to huge information leakages; hence every data privacy practice must be followed with due diligence.

In conclusion, data breaches can occur anytime, anywhere, regardless of the information security measures we take. The best probable way to prevent cyber-crime or contain the impact of an attack at your enterprise is to keep your data privacy software updated, employ multi-layered, more reliable cybersecurity solutions and remain extra-vigilant, more than ever before!

How to avoid a data breach at your enterprise?

Data breaches can happen anytime, anywhere. How well are you prepared to fight one?
As technology continues to drive businesses, it also continues to make them vulnerable to cybercrime. Data breaches at huge business groups such as Equifax and Facebook literally shook the IT world. Now, Equifax is the third largest credit reporting organization in the US, and Facebook needs no introduction. Who would have expected a mega-breach at such reputable enterprises?

But that’s what has startled companies across the globe. Little negligence is all it takes to cause a security incident and to shatter your brand name in the market. The aftermaths of a security breach can be devastating. They can bring down your reputation awfully, put a dent on your finances, and leave you juggling with legal actions and lawsuits.

CEOs and CXOs are realizing that data breaches can happen in any organization, big or small; and feeling totally secure about their data could be a huge mistake. Here are some measures that can help you avoid a data breach at your enterprise.

Internal Awareness

First things first, ensure that your management and employees are totally aware of the potential cybersecurity risks that your industry and company is vulnerable to, and the repercussions that a data breach can have. Building internal awareness includes developing standard security guidelines, clear BYOD policies, and ensuring that all employees are making prudent use of sensitive business data.

Secure Networking and Updated Software

We just cannot deny the significance of a strong and secure enterprise network. Invest in a trusted corporate VPN that ensures safe encryption of sensitive data at source. Another key concern is that data driven organizations are subject to constant software and technology advances. The older your software, the more vulnerable it is to data breaches. Keeping up with software updates through strong data security solutions will keep you fairly outside the radius of a data breach.

Using Cloud Based Technology

Cloud servers tend to have an extremely high level of security, and are encrypted and monitored by expert teams which can inspect and identify malicious attacks immediately. Top companies around the globe are moving to cloud software solutions to safeguard their businesses from security breaches. Using cloud based technology to save your firm’s sensitive data and client information will give you a better control over your enterprise data and back you up in times of emergency.

Vulnerability assessments and Regular Security Audits

It is important to keep a check on vulnerability of your business data and regularly monitor areas which may be exposed to malicious activities. A regular security audit brings out the clear picture of your data and acts as a checklist to work towards data protection. It highlights the areas where real problems exist, and helps you take the correct measures to prevent cybersecurity attacks.

Information security is a highly sensitive area for all businesses because it has a massive impact on what matters the most; the customers. In a world of hacks, scams and cyber security breaches, a little negligence can cost you dearly. But with the right firefighting tools and effective data privacy measures, you can prevent cyber-risk from making a catastrophic impact on your business.

What to look for in your Mobile Business Intelligence tool?

Selecting the right Mobile Business Intelligence tool is essential for outstanding business growth. Here are 4 key factors to consider while choosing a mobile BI tool for your enterprise.

Information is power today! However, since most of this information is scattered and raw, businesses need tools and methods to turn this data into actionable insights and make profitable decisions.

This has multiplied the importance of analytics and business intelligence for data-driven businesses. There are several factors that urge businesses to invest in Business Intelligence. It improves visibility of data, enables clearer decision making and brings businesses closer to established goals.

In the recent times, Business Intelligence paradigms have increasingly shifted toward equipping more employees with critical information. The proliferation of mobile technology has helped facilitate this trend, resulting in new considerations for BI software. There are literally hundreds of mobile BI tools that have emerged over time, which is why it is important for companies to approach BI procurement with a clear framework. Here are some key features to look for in your mobile BI tool for a profitable business growth.

Architecture

Your tool should be accessible and properly formatted on all mobile devices and operating systems, including smartphones and tablets. This becomes primarily important because users of business information are spread across various devices and technologies, and every user must be able to make use of BI insights effectively. Many BI vendors are now offering customized mobile intelligence solutions to cater to varied business specifications.

Usability

Accessing BI on a mobile device implies the user’s expectation for simplicity and convenience. Particularly as businesses find more use for predictive analytics, mobile BI should have robust tools for generating new reports as well as sensible dashboards, making viewing and searching business information easily. Look for a tool that has a clear, easy-to-use design, and is able to offer the convenience of using a web-based dashboard on a small screen with minimum effort.

Integration

Companies benefit most with BI tools that integrate with device-specific features such as GPS and other mobile applications. Touch gesturing, integration with cameras, messaging and social media applications and geo-locational functionalities are some common integration features that most businesses seek in modern mobile BI tools. The ability to integrate BI software with other critical applications allows businesses to expand usability of information beyond analysis.

Visualizations

Analyzing raw data is crucial, but user-friendly reporting is equally essential for successful BI implementation. Effective BI tools transform key information into graphs, charts and other visualizations so users can easily make sense of it. Greater visibility leads to better understanding and improved decision making for employees and other stakeholders.

IT Assistance

Another key consideration before selecting a mobile BI tool is the availability of support services at all times. Mobile applications seldom undergo performance failures and breakdowns. Your BI vendor should be able to assist you with any issues and be available for immediate troubleshooting.

Pricing

When multiple BI tools with promising features and competitive prices are available in the market, selecting an ideal tool becomes a challenge. The pricing of a BI tool varies depending on the specifications required and business size. Go for a tool that delivers the maximum business value and fits your budget. An overpriced tool might increase your business cost and a cheap tool might not deliver the desired business benefit.

Mobile technology is growing at an unbelievable pace and so is Mobile Business Intelligence. Industries and businesses of diverse nature are now adopting mobile BI to attain a competitive edge, improve workflows and grow with technology. If you’re looking forward to blending the smartness of BI tools with the convenience of mobility, you know what to look for in your Mobile Business Intelligence tool.

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