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Insurtechs are Thriving with Machine Learning. Here’s how.

Modern Insurance is only around 250 years old, about when the necessary statistical and mathematical tools to underwrite a business venture came to be. But statistical models, even the most advanced ones, need a very specific type of enriched data-diet for it to work optimally. Since then, the industry has always had to rely on data for ensuring its long financial health. For insurers to take on considerable risk, regardless of size, it draws on the reassurance of statistically-sound data that underpins the coverage needed (for issuance) to a fixed number. This ‘number’ will influence the amount of coverage (or claim) provided to the insuree and consequently the amount of premium to be collected.

Such is the reliance on data, that even the slightest erroneous mistake in the underwriter’s predictions could bankrupt, at times, even the economy. We’ve seen it before — when banks took on unqualified risks and approved subprime mortgage loans to borrowers with poor credit, creating the imploding housing bubble of ‘08.

The nature of risk simply evolves and devolves; while Insurers learn progressively with each individual case, adsorbing enormous amounts of data into their carefully crafted risk-models. These models then naturally aid in the manual effort of several hundred data scientists (in the case of large insurers) poring over immense amounts of psychographic, behavioral and environmental attributes for evaluating an entity’s risk profile. Yet, even with these measures, the risk is unquantifiable if the data scientist doesn’t have a large or clear enough picture to make sense of all the inbound information. 

In the age of machine intelligence, data is prime fodder for these advanced algorithms. They are designed to thrive on large datasets — in fact the larger the size, the better the system learns. How could it not? An AI system is decidedly 1000x faster than human computing, raising accuracy levels to near perfection and improving straight-through processing to nearly one in every two decisions made without human intervention, today.


Source: Accenture Report — Machine Learning in Insurance

20.4 billion things will be connected by 2020 creating an unprecedented level of data handling & insight derivation capacity, as BFSI companies alone will spend US$25 billion on AI in 2020 (as reported by IDC research). Since 2012, more than $10 billion has been invested in insurtechs.

For 2020 and beyond, customers will come to expect better personalization from their insurance policies, especially millennials and younger. While the incumbent, slow-moving giants of traditional insurance should surprise no one as being the last to innovate — new insurtechs like Flyreel are changing the paradigm by piloting Machine Learning projects that directly translates to critical business goals.

According to McKinsey, digital insurers are already achieving better financial and efficient go-to-market results compared to traditional players.

Here are three ways, insurtechs are gaining ground with Machine Learning (specifically where learning from data is involved):

  1. Risk Prediction
    Predicting and evaluating risk is insurance’ oldest use case, and research reveals it will continue to be so. With ML and advanced algorithms, insurers can process big data from multiple data points such as policy contracts, claims data, weather parameters, crime data, IoT and sensor data.
    By Analysing existing data, identifying anomalies, tracking recurring usage patterns and then delivering accurate predictions and diagnosis through vertically-tuned algorithms — ML-based platforms can identify risk ratios and risk profiles that enable insurers to customize policies for individual customers in real-time. This differs from ‘off-the-shelf’ platforms which can only be utilized to solve a narrow set of problems.

  2. Customer Lifetime Value (CLV) Prediction
    CLV is a complex metric that represents the value of a customer to an organization as the difference between the revenue gained and expenses incurred – all projected onto the entire relationship with a customer, including the future.
    Insurers can now predict CLV using customer behavior data that allows them to assess the customer’s potential profitability for the insurer. Behavior-based learning models can be applied to forecast retention or cross-buying, all critical factors in the company’s future income. ML tools also help insurers to predict the likelihood of particular customer behavior – for example, their maintenance of the policies or surrender.

  3. Personalization Insights Engine
    User data from AI, machine learning and behavioral and social sciences can provide actionable insights in real time. For example, simulation and learning capabilities allow companies to discover new customer groups, to help companies personalize customer engagement, risk assessment, and forecasting by combining data from multiple sources.
    A common challenge is capturing data from multiple sources and turning the data into insights that can inform business decisions across many functions. With machine learning, insurers will be able to underwrite, adjust customer journeys, resolve claims and adapt offerings.

ML-based solutions bring back real value to insurers — either delivered as a standalone product or as a part of an embedded process/service. The key for insurers is to pilot ML projects of smaller scale that can bring about cost and time savings across the organization almost immediately and then improve in easier iterative sprints for more future-ready permanence, rather than taking on the task of a complete enterprise makeover from day one!

For more information about how we can help enterprises begin their ML transformation, reach us on hello@mantralabsglobal.com

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Virtual health: Delivering care through technology

8 minutes, 52 seconds read

Virtual Care, Telehealth, Telemedicine, etc. are terms used very synonymously. Indeed they are interrelated, however, Virtual Care is a broader term in which healthcare providers use digital tools to communicate and deliver care to their patients. Telehealth and Telemedicine are a part of Virtual Care where doctors deliver care to their patients, remotely via phone, video, or instant messaging. Virtual health includes care delivery beyond video consultation where hospitals provide services using technology such as wearables for remote monitoring, instruments for post-op care and second opinions, e-pharma services, and medical information, etc. 

The outbreak of the COVID-19 pandemic gave an impetus to Virtual Care, but even in the Pre-COVID time, the Healthcare sector was slowly gearing up for this next wave in care delivery. What COVID-19 did was, help patients get acclimatized to the digital health tools and services. 

What does Virtual Health help with?

The pandemic has brought the burning issues of the healthcare sector to center stage. Patient experience and access to healthcare services are key differentiators for people while choosing a healthcare provider. Let’s take a look at some of these issues addressed by technology in the healthcare sector-

The increasing number of patients

Apart from the pandemic, there’s already been a rise in the number of patients due to drastic changes in lifestyle and food habits, an increase in pollution levels, increase in new types of viruses, etc. This has caused undue stress on healthcare institutions and workers and has led to the deterioration of the quality of patient care. Virtual Health technology such as mHealth apps, EHR (Electronic Health Record), video conferencing, etc. has helped reduce the pressure on hospitals.

Difficulty in traveling for old patients

The pace of life is increasing at a rapid rate. It is getting insanely difficult for the elder population to navigate through the traffic and commute long distances for a check-up. Many times, they have to depend on their family members to take them to hospitals. Moreover, they are at risk of exposure to viruses in hospitals and clinics. Now that they have had the experience of virtual consultations, they prefer care delivery at home rather than going to hospitals.

Chronic Diseases treatment

The number of people above the age of 45 face health issues. Some patients are suffering from chronic diseases regardless of age. Regular monitoring of their vitals is very important. Moreover people now prefer Virtual healthcare services which are easily accessible and save a lot of time, effort, and money. Now that people have found these services effective, they will opt for online consults rather than frequent in-person visits. 

Post-op Care

The duration of post-operative care is quite long and tedious. If given a choice, people will lean towards wearables which will help keep doctors posted on the status of the treatment. Many times, the cost of post-op care is more than the actual treatment and sometimes is not covered under insurance. Virtual care-delivery services will help reduce the financial burden of people going through these treatments.

Follow-ups/Second opinion  

Some health conditions need multiple follow-ups and second opinions to figure out the right approach to treat the issue. It is much easier for patients to do follow-up consults virtually rather than going through the tedious process of appointment booking, commuting, and waiting for their turn. It helps reduce the queue outside the doctor’s office as well. Some health issues need a second opinion, sometimes both by patients and doctors. Virtual Healthcare technologies make it possible for them to take second opinions from doctors all over the world. With electronic records and image sharing, doctors can diagnose the problem better.

What does Virtual Health include?

Virtual Health can be broadly divided into below applications-

mHealth Applications

mHealth applications have widespread use. From symptom checkers to appointment booking, from fitness trackers to uploading medical records, from video conferencing features to chatbot integrations, mHealth apps are on a rise mainly because of easy accessibility for the tech-savvy customers. According to a study by NCBI, among the 22 selected mHealth apps operating in India, Practo, mfine, DocsApp, 1mg, Netmeds, Lybrate, MediBuddy, and Medlife were found to be the eight most popular ones with over a million downloads and on average four-plus user rating out of five. All the above apps are mainly being used for online consults. This just goes about showing that people prefer having homecare services instead of stepping out. 

E-Triage Tools

The rising number of patients with different stages of COVID symptoms was a task to deal with. E-triage software here enables hospitals to triage patients into different sections when there’s an overload of patients at a particular time. Now, in the case of home care, e-triage tools help patients to access the gravity of their health condition and notify the healthcare provider accordingly. Such tools help reduce A&E waiting time and improve NHS performance. Many companies are building healthcare software integrating the E-triage module within EHR, telemedicine, clinical decision making, billing, etc. In India, Persistent Systems’ cutting edge platform has a Nurse Triage system that enables nurses to see the queue of patients and triage via phone calls. Once the calls are done, a triage report is generated and sent to care providers. Many leading doctors feel that AI in image triage will see a boost in near future.

Remote Patient Monitoring 

There are multiple benefits such as reduced post-op expenditure, time wastage, less exposure to other diseases, etc. The global remote patient monitoring devices market is expected to expand at a CAGR of 7.1% during the forecast period (2019–2027) according to Coherent Market Insights. Some of the top players in this space are Biotronik, Boston Scientific Corporation, CAS Medical Systems, CONTEC MEDICAL, Dragerwerk, GE Healthcare, Guangdong Biolight Meditech, Medtronic, Mindray Medical, Nihon Kohden, Philips Healthcare, Spacelabs Healthcare, Abbott. Companies such as GE Healthcare and Philips Healthcare have done a great job with building remote patient monitoring systems within the hospital premises as well as homecare for COVID patients. The main goal was to reduce the exposure of healthcare workers to at-risk patients. 

Synchronous and Asynchronous Telehealth

Synchronous telehealth, in other words, Telemedicine is where there is a live conversation between the patient and the doctor. Asynchronous telehealth involves the exchange of recorded data e.g. images, video, medical reports, pathology reports between patients and doctors, at times between doctors as well. Similar to mHealth space, companies like Practo, 1mg, Lybrate, Medlife, and Portea Medical in India are some of the top players in telehealth and telemedicine. Lybrate’s USP lies in CMS (Clinical Management System) which helps doctors with tedious tasks of managing patients and providing better care. Meanwhile, Portea Medical’s home consults and pharma delivery have more relevance with the audience as it combines technology with a touch of personalization. 

Digital Therapeutics

Digital Therapeutics delivers evidence-based therapies with the help of software which can be used both as a preventive measure as well as treatment application. The effectiveness of the medication and lifestyle changes on patients are monitored by leveraging technology. In India, major non-communicable diseases that account for 62% of the total mortality rate are CVD, diabetes, respiratory conditions, and cancer. Prominent global players in this space include Noom (US), Livongo Health (US), Omada Health (US), WellDoc (US), Pear Therapeutics (US), Proteus Digital Health (US), Propeller Health (US), Akili Interactive Labs (US), Better Therapeutics (US), etc. Omada Health is the pioneer in the DTx (Digital Therapeutics) that focused primarily on diabetes and pre-diabetes but now is branching out in the mental health space as well. In India, Altran (a part of Capgemini) is into building personalized DTx applications for clients. Whereas a start-up called Wellthy Therapeutics has ready solutions catering to multiple diseases.

Future of Virtual Health

Undoubtedly, there has been a massive increase in the adoption of Virtual Health technologies as people have gotten accustomed to the ease of certain services at home. In the coming future, mHealth apps, remote patient monitoring, and Digital therapeutics see a surge in demand from the customers. According to a study by Markets and Markets, “The global digital therapeutics market is projected to reach USD 6.9 billion by 2025 from USD 2.1 billion in 2020, at a CAGR of 26.7% during the forecast period (2020–2025).” A study by Fortune Business Insights, “The global mHealth market size is projected to reach USD 293.29 billion by 2026, exhibiting a CAGR of 29.1% during the forecast period.” A Research and Markets report says, “The remote patient monitoring market is expected to reach US$31.326 billion by the end of 2023.” Apart from the above, development in digital infrastructure such as virtual health stations where doctors can provide consultations globally, mobile ICUs, MRIs, X-rays, ultrasound equipment, the establishment of rural virtual care units reaching the remote areas of the country are some of the trends which will gain momentum. The focus would always lie upon the personalization of the virtual care experience for patients driven by data exchange and interoperability. 

Indeed, there are certain challenges to the implementation of these technologies, lack of infrastructure, and digital literacy amongst elders and lower strata of society. Many healthcare institutions still have inhibitions while investing in digital technologies fearing rejection from the customers. It will be crucial for care providers to choose the right partner for implementing these technologies and create awareness amongst people to adopt them.  

In a Nutshell

The success of virtual care relies on how well the digital experience is designed for the patient. “By 2025, as many as 95 percent of all customer interactions will be through channels supported by artificial intelligence (AI) technology” – Microsoft. The use of algorithms and AI for personalizing these experiences will be the key. 

Find out more about unchartered territories in ‘Blue Ocean’ of Digital Health. Join our webinar hosted by Parag Sharma (CEO, Mantra Labs) as he shares his insights on untapped opportunities using digital self-care tools within behavioral healthcare & emotional wellness.

Save your spot! 

Further Readings:

  1. Reimagining Medical Diagnosis with Chatbots
  2. HealthTech 101: How are Healthcare Technologies Reinventing Patient Care
  3. What will be the state of the healthcare industry post pandemic?
  4. Healthcare Chatbots: Innovative, Efficient, and Low-cost Care
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