Harnessing the Power of Technology in Medication Management

Harnessing the Power of Technology in Medication Management

Many of us have been through phases where we missed our medication doses or took the medicine incorrectly because of the complexity in following instructions given by healthcare providers.

At the point of care, dealing with the logistics of handling a variety of medicines and providing dosages to patients can sometimes be overwhelming and time-consuming. These situations cause medication errors and thus a rise in mortality rate, increased hospital stay and higher medical expenses.

A survey from the Association of Medical Directors of Information Systems reported that over 80% of Chief Medical Information Officers (CMIOs) believe medication management initiatives positively impact patient safety. However, it was found that there is a 45% risk of error across all these medication management processes which could be minor with no real tangible impact on the patient. But these errors could cascade into serious errors that will put the patient at risk.

With the integration of clinical services and medication management technologies, the healthcare sector is transitioning from a paper-based medication prescription and administration model to a comprehensive medication management system.

Automation in medication management solutions and software is giving healthcare staff more face time with patients, provision of right dose of medicine to the right person at right time and increasing medication adherence for patients with overall quality of service. Assessment of patients, medication reconciliation, prescribing, dispensing and monitoring are the fundamental steps involved in these systems resulting in value-based care at reduced costs. For example, integration of electronic health records (EHR) of patients with the medication device at their bedside allows medication parameters from the EHR to be pre-populated into the device based on patient characteristics thus reducing the chances of programming errors.

 

 

Many global companies (Becton Dickenson, Omnicell, Philips, Swisslog, GE Healthcare, McKesson) have developed various types of medication management systems such as:

  • Automated/robotic dispensing systems/cabinets for handling, distributing and dispensing medications and supplies in hospitals and retail pharmacies
  • Medication management systems that interface and integrate with point-of-care information systems and provide rapid access to patient information and facilitate documentation
  • Embedded analytics software to monitor drug diversion and avoid redundant inventory management issues
  • Centrally located medication-management systems that replace or improve a manual system for filling unit dose carts

A new generation of artificial intelligence (AI)-powered (predictive analytics, machine learning) medication management systems are playing a key role in identifying and addressing the root causes of medication non-adherence. Systems that use a machine-based learning model can identify outliers in prescriptions from a pool of patients with similar characteristics and detect potential medication errors and logistics processes over time and prevent those errors from recurring. Using such AI-based systems, clinicians are also able to proactively detect potential side-effects of drug combinations or controlled substance overdoses at the prescribing stage, during medication administration and when patients move between health care settings. Leading healthcare organizations have deployed next generation analytics platforms to deliver actionable insights integrated into their EHR clinical workflows to empower their executives, clinicians, and nurses at the point of care (POC).

Patient-centric care is possible across the continuum of care with the use of these IT-integrated medication management systems that evaluate the dynamics of patients’ clinical, medication and related administrative information. A great collaboration is established between the patients, care teams, pharmacies and payers in the medication decision process.

Healthcare facilities and organizations should embrace and deploy medication management systems integrated with smart technologies as the focal point of their patient care. The ultimatum for the healthcare industry is to get the right medications to the right patients at the right time for the right condition while decreasing the burden of costs incurred.

 

OSG is a “catalyst” that helps our clients be the best at decoding their customers’ decisions. Our clients have seen a minimum 20% improvement in customer engagement by implementing smart insights delivered using our behavioral analytics products.

FinTech’s Impact on Traditional Banking

FinTech’s Impact on Traditional Banking

Financial technology or ‘Fintech’, with the help of technology-enabled products and services, is rapidly reshaping traditional financial services, making them faster, easier, cheaper and more accessible. Fintech empowers consumers to take charge of their financial decisions, leading to much greater financial literacy than ever before. In short, Fintech combines traditional financial services with the latest digital technology and Big Data products, making customers’ lives easier.

 

Different Financial Sectors that Fuel the Growth of Fintech

Whether we are purchasing at a local tea shop, going online and checking financial transactions or utilizing apps that track spending which allows financial institutions to make quick lending decisions, Fintech is all around us.

Fintech offers its services in First Wave Sectors (which scale quickly) and Second Wave Sectors (which scale slower and have more regulations and risks involved, with difficult customer acquisition).

  • First wave sectors include peer-to-peer (P2P) lending, capital raising (crowdfunding) and online/mobile payments

Peer-to-peer lenders – These match borrowers to investors, shortening the approval time to hours. Some P2P lenders include Upstart, Funding Circle, LendingClub, Prosper Marketplace and more nonbank lenders.

Crowdfunding – These help charities and entrepreneurs by raising small amounts of money from large groups of people. Some crowdfunding platforms include: Indiegogo, GoFundMe, Crowdcube, Kickstarter

Mobile payments – These help people transfer money from their mobile phones, without a need for bank accounts. Some services also convert currencies for much less than what banks charge. Venmo, Samsung Pay, PayPal, Apple Pay are some examples

 

  • Second wave sectors include international money transfer, asset and wealth management, insurance, investments (robo-advisors), digital security, Big Data analytics and Blockchain.

Robo-advising – Use algorithms to match portfolios to customer’s risk preferences. Giant BlackRock Inc., Nutmeg, Scalable Capital Ltd. are some examples

Blockchain and Bitcoin – Exchanges and banks are developing applications using blockchain, the free database that processes Bitcoin (electronic cash) transactions

Insurance – Traditional companies are investing in Insurtech start-ups, which cut the time taken to buy life insurance products, from weeks to minutes

Initially, fintech started offering services in first wave sectors with approximately 70% of start-ups falling under this category globally.

Quite recently, there is a rise of the second wave sector expanding the scope of financial technology even further. Blockchain-based services such as cryptocurrencies (a form of electronic cash) are still in its infancy with potential to transform technology that goes well beyond finance.

 

The Fintech Ecosystem:

In most cases, fintech products and services are developed by start-ups, which are young companies attempting to scale by creating opportunities in new markets or in established markets through a better value proposition. Therefore, fintech start-ups are small companies that aim to improve the way individuals and companies bank by collaborating or competing with established financial service providers.

However not all players on the fintech market are start-ups. Over the years, some companies have established themselves well in the sector like: PayPal, Alipay, Klarna, Square, BitPesa, Lending Club, OnDeck, SavvyMoney, Lendio, Credit Karma, LendingRobot, BTC and more.

 

Impact on Traditional Bank Branches:

A leading 2017 industrial report revealed that the branches continue to play an important role for a variety of services. Approximately 50% of those surveyed said they’d prefer to open a new deposit account or apply for a new loan in person. Furthermore, 25% said they wouldn’t open an account with a financial institution that didn’t have local branches.

Despite digitization, Physical channels – branches and ATMs – seem to continue playing major roles in banking, as:

  • Comparatively simpler transactions have migrated to digital channels, but branches remain relevant for more complex transactions
  • Stringent know-your-customer (KYC) and anti-money-laundering rules across various countries mandate personal contact for specific transactions, especially for first-time customers
  • Many customers prefer personal advice about products even after conducting research digitally
  • Similarly, many Millennials prefer to visit a branch to open a new account, learn about budgeting, understand retirement options, and to understand and apply for a mortgage
  • Security concerns: Branches provide a sense of permanence and security that is difficult for digital banks to match

 

Traditional bank’s strategies to combat FinTech – investments, partnerships and acquisitions

It was only in the second half of 2010 that banks started realizing the emerging threat of FinTech companies. As FinTech start-ups started gaining momentum, a fear set among banking institutions, which led to the rise of bank innovation teams to combat FinTechs through investments, partnerships and acquisitions.

  • According to MEDICI Research, nearly all FinTech Acquisitions in 2018 were led by American & EU Banks. And while American & EU FinTechs have been the major target of acquisitions, startups from Asia and other regions are also emerging as the preferred destination for acquiring FinTechs. Breaking down the total acquisitions by segment indicates that:
    • 38% of all acquisitions have been made in wealth management followed by
    • 19% in B2B FinTech
    • 14% in Lending
    • 10% in payments
  • Another industry study revealed that the number of FinTech deals rose sharply, from just over 1,800 in 2016 to nearly 2,700 in 2017, showing continued investment in banking, insurance and capital market start-ups
  • Global investment in FinTech companies between 2010 – 2017 reached more than US$97.7 billion, with the US start-ups accounting for 54% of all investments, followed by UK and India. Within this timeframe the FinTech deals globally, grew at a compound annual rate of 35%, with total funding growing at a CAGR of 47%

 

The 2017 growth in the sector was majorly driven by:

  • Huge new investment flows from China, Russia, the Middle East and other emerging economies
  • Huge investments in FinTech start-ups operating in payments and lending sector
  • B2B FinTech models, where they help banks & other financial institutions upgrade their technology
  • Rapid leap of ‘insurtech’ ventures offering advanced insurance-related services

 

FinTech to become the Driving Force of Future Banking:

Rise of Digital-Only Banking Consumer: A 2017 Digital Banking Consumer Survey provided significant insights into the rapidly changing behaviour of the banking customer:

  • Around 46% of consumers use only digital channels (omni-digital customers) in 2017, a rapid increase from 27% share seen just four years ago in 2014
  • More than 80% of consumers own a smartphone, amongst which 60% reported using mobile banking in 2017, up from 36% in 2012
  • The segment of customers who used a variety of channels including both digital and physical (omni-channel customers) has been significantly shrinking over the past four years (57% in 2012 to 45% in 2017), being replaced by the “omni-digital” customer
  • Human-interaction channels continue to shrink, falling from 15 to 10% during same period

 

Rise of Millenial generation:

  • The most prominent factor that helped FinTech to become a disruptive force in the financial world, is the millennial population. Millennials are highly demanding and less loyal expecting personalized products and services at their convenience. They tend to check for information/ financial products/ advice online instead of following traditional ways of finding information
  • As per a report for Millennial Disruption Index (MDI), 1 in 3 millennials change their bank in every three months in hope of getting desired experience, which in turn is increasing the need for FinTech solutions (which provide customized products and services as customer’s convenience)

 

Conclusion:

In this FinTech era, the financial institutions need to adapt to the digital trends as early as possible, understanding the unmet needs of a digital customer in a better way. The growing expectation from Financial institutions is to shift from product-based models to customer-based models, equipping themselves to offer “real-time”, “easy to use”, “personalised products and services” to the digital customers through “customer’s preferred channel”. By finding the right blend of acquisitions, partnerships and investments, traditional banks have a leverage to come up with innovative solutions to address the evolving needs of their customers in this tech-first era of financial services.

This will also open doors for the banks to get exclusive rights to the advanced technology which could provide a competitive edge over others, rapid expansion into new markets, and even a new customer base.

OSG is a “catalyst” that helps our clients be the best at decoding their customers’ decisions. Our clients have seen a minimum 20% improvement in customer engagement by implementing smart insights delivered using our behavioral analytics products.

Harnessing Consumer Emotions: Recharge your Brand and Fuel Growth

Harnessing Consumer Emotions: Recharge your Brand and Fuel Growth

In the age of advanced technology and the informed consumer, it is becoming increasingly difficult to stand out from the crowd and firmly plant your brand’s image in consumers’ minds. Better products lead to more imitations and as such, competition is at an all-time high. So how do you differentiate yourself from your competitors? By harnessing consumer emotions and using them to provide your brand with a fresh new voice that genuinely connects with your customers.

 

It is an age-old idea that consumer emotions drive brands. Several academic publications and practitioner research that have been conducted over the years corroborate the same. Studies have shown that emotions play a big role when it comes to decision making, more so than logic. By tapping into the powerful behavioral effects that emotions have, you can fuel growth. Having understood the primacy of consumer emotions, what can you do to revitalize your image? Here are some tips to utilize emotions to grow your brand:

Defining the tone of your brand

The first step towards harnessing consumer emotions is to understand broadly what tone you want your brand to convey. It is important to recognize the different types of emotions that are generally applicable to your product or service, and hone in on one that you find most suitable. Think about your previous experiences with similar products/services to help you out. As you grow your business and gain customers, you can use their opinions to help guide what emotions your brand should relay.

Furthermore, you can use this information to develop guidelines for tone of voice, visual design concepts, and documents such as brand books and more. Having these guidelines in place will ensure that your company has a consistent tone. There may be times where your tone will have to shift, such as creating content that is focused on real world events. While it is fine to alter your tone at those particular moments, you need to ensure that it does not impact your brand’s overall voice. Be sure to always refer back to your established guidelines to stay on track.

Branded content

If you want to create an emotional connection with your target audience, you need to have a steady stream of content. The aim of this content cannot just be about simply getting “likes”. It needs to go beyond that and tap into an underlying emotion that may not be obvious at first. While this is no easy task, it is imperative that you get this right to truly connect with your audience.

Content consumption has drastically changed over the years. These days anyone can make content, not just massive organizations with large resources. This means that you need to work even harder to reach your audience, which is why tapping into emotions is so vital. A leading business review reports that customers who are ‘fully connected’ emotionally are 52% more valuable to brands as compared to those who are just ‘highly satisfied’.

Refine your content targeting

Think about who you are trying to build an emotional connection with, and what that connection is. In today’s world there are several touchpoints with your customers, and it’s fairly easy to get your messaging mixed up. Not having a clear messaging strategy can mean that you lose the opportunity to connect with some of your target audience. This is why the first point of this article is so crucial, it defines who you are going to connect with and how. Brands nowadays simply do not have the luxury of satisfying a variety of emotions, as competition in terms of content consumption is at its peak.

You need to narrow down which particular emotions you are chasing as much as possible. This may involve not even targeting all your current customers.  Rather than trying to please everyone, it is better to instead target a smaller and more defined portion of your audience. Put your efforts into learning their underlying motivators and discover the emotional triggers that you would integrate into your content strategy and overall tone of voice. Having accomplished this, you will be able to thrive in the niche you have discovered. Furthermore, as people interact with and share your content, your reach will grow organically to consumers who relate to the emotions you convey but were previously not your target audience. Growing in this way is easier and more sustainable than using a one-size-fits-all strategy, where you are trying to capture everyone’s attention with a generic emotion, and inevitably end up failing because you were not able to truly connect with anyone.

Using data to help you

There are several ways in which data can help you hone in on the emotions your customers relate to. One example is using text analytics. Text analytics refers to the process of converting unstructured text data into something that is meaningful for analysis. It gives insight into your customers’ minds, helping you understand elements like their opinions, feedback, reviews etc., all of which can help further define the emotions you should focus on.

With text analytics, you can carry out exercises such as sentiment analysis, social media monitoring, concept extraction, understanding relationships between entities, understanding voice of customer, learning about your customers’ experiences and more. All these exercises will allow you to truly put yourself in your customers’ shoes. Having this ability positively impacts the content you create as it will be more relevant, and in turn will bring out desired outcomes such as increased reach, revenue and growth.

Other ways data can help you can include techniques such as voice and facial analysis. Remember that these exercises are iterative and will have to be carried out periodically for sustainable benefits.

 

How can OSG help?

At OSG, we are focused on creating experiences that help you understand your customers better. Our AI-driven big data analytics platform, OSG Dynamo™, can be a trusted partner on your journey towards harnessing consumer emotions. Dynamo can help capture the key messages which are unique and resonate with your target audience. Furthermore, Dynamo can also help ensure that these messages will reach the largest audience, as well as change consumer behavior in a way that positively impacts your business.

ASEMAP™, our bespoke behavioral analytics engine, uses a trade-off methodology to test various messages among your audience. This process ensures that messages are prioritized in terms of impact on consumer, thereby providing your business with a optimal messaging strategy that leads to growth.

Start your journey of harnessing consumer emotions by contacting us.

OSG is a “catalyst” that helps our clients be the best at decoding their customers’ decisions. Our clients have seen a minimum 20% improvement in customer engagement by implementing smart insights delivered using our behavioral analytics products.

Behavioral Analytics for a Structured Approach to Storytelling – Understanding Customer Journeys in a Hyperconnected World

Behavioral Analytics for a Structured Approach to Storytelling – Understanding Customer Journeys in a Hyperconnected World

Today’s dynamic, digital age demands that business metrics should be strongly linked with customer satisfaction metrics. When customers are not just connected but hyperconnected through a multitude of devices such as wearables, phones, laptops, desktops and much more, it is difficult for brand to differentiate themselves over competitors. Personalization is the need of the hour. So, what can organizations do to effectively connect with their customers over competition throughout the customer journey?

 

One of the most impactful ways to engage customers at every step of their purchase journey would be through stories that resonate with them. However, it can’t be a cliched, one-size-fits-all story. It must be storytelling that dives into the collective customer mindset/choice pattern to determine how best to influence their purchase behavior. This is where behavioral analytics comes into play.

Let’s take the example of Storytelling Inc., a fictitious company. Storytelling Inc.’s marketing department was trying to develop effective marketing to acquire new customers for one of their product offerings. The team put together a plan to run campaigns with the goal of increasing acquisition numbers.

At the monthly marketing meeting where numbers were reviewed, it was reported that while branding outreach improved slightly, and a few clients were acquired, overall customer acquisition numbers were much less than expected. However, in an unrelated departmental meeting, an analyst specializing in customer behavior noticed a significant increase in customer retention. The analyst reached out to the sales team to determine if there had been any strategy change to drive this trend and found that wasn’t the case. After some digging, it was determined that the campaigns which Storytelling Inc.’s marketing team ran to acquire new users ended up informing existing clients instead. With existing customers now aware of new product features, Storytelling Inc. inadvertently ended up upselling their product. This win would very nearly have been missed because Storytelling Inc. was so focused on their acquisition goals rather than the bigger story – they missed out on the advantage of anecdotal analytics.

What is anecdotal analytics?

Every successful business is constantly trying to learn more about their customers. They sit on vast quantities of customer data, and often predict how they will react accurately throughout the customer journey. However, they don’t use this data to weave stories for customers that might influence their purchase choices. Why? When will we include the power of storytelling to our business growth narrative? In today’s world where customers don’t need to reach out to businesses before purchasing products, all businesses can do is tell stories through data to influence customer choice. If data-driven stories or anecdotal analytics are included at every stage of the customer journey process, it may be possible to connect more with your customers in this hypercompetitive world.

Imagine if we could tell data-driven stories, powered by behavioral analytics, at every stage of the customer journey:

  1. Awareness

As your audience knows nothing about your brand or product at this stage, your story should be around your previous successes. By letting potential customers know the tangible impact you have had on other customers, you are drawing attention to the power of your brand and your customers’ faith in you.

  1. Consideration

As your audience already knows of your existence at this stage, your stories should be focused on how you are doing better than your competitors. By drawing focus to your strengths over competition, you enable customers to consider you for their purchases.

  1. Purchase and Use

At this stage, your customers have already chosen you over competition. Your story should emphasize your latest product offerings and feature updates, so that customers know how to use your offerings to the maximum extent possible. Enable them with handy tips and tricks, to use your product better.

  1. Advocacy

Now that your customers have used and liked your product, it is time for them to recommend it to friends and family. Don’t hesitate to ask for their help when it comes to your brand or product advocacy. After all, you need their voice and their stories to build your narrative. Create content that asks for their support to spread the word and say something positive about you.

Let us take the case of Storytelling Inc. once again. Only this time, they are aware of the power of anecdotal analytics in customer journeys. Storytelling Inc. already has a vast quantity of customer data available. When the behavioral analyst looks at this data, he comes across a gap in the market for upselling the product to existing customers. By collaborating with the marketing team, a different plan is put together to create campaigns targeted at these existing customers. These campaigns run content in the form of stories interspersed with facts, to inform customers about new features, handy tips and tricks, and much more. Customers who are already using Storytelling Inc.’s product now have a chance to try out these updates, thus increasing product sales more effectively. Now, the monthly review meeting has a different story to tell – that of success and improved customer satisfaction metrics.

Ultimately, don’t let your business goals take away focus from what is truly vital – customer centricity. Your business and your stories are only as important as your customer connect.

 

How can OSG help on your anecdotal analytics journey?

OSG Dynamo™, OSG’s AI-driven, big data analytics platform can be your partner on the journey towards creating data-driven stories. With its bespoke behavioral and cognitive analytics platform, Dynamo can identify needs gaps in your customers’ journeys and provide robust recommendations on how to connect with them better. You can then weave better stories to improve brand outreach and business growth.

We hope this information has been valuable and interesting to you. Please do feel free to share it with colleagues and others in your network. We welcome discussing this topic further with you and understanding your specific challenges.

OSG is a “catalyst” that helps our clients be the best at decoding their customers’ decisions. Our clients have seen a minimum 20% improvement in customer engagement by implementing smart insights delivered using our behavioral analytics products.

Disrupt Demand Forecasting by Reading Your Customers’ Minds

Disrupt Demand Forecasting by Reading Your Customers’ Minds

Decades ago, in the 1970s and 80s, businesses were bewildered by the complexities that demand forecasting presented. With the onset of enterprise computing at the time, there wasn’t enough customer data available to draw insights on demand. This resulted in massive losses when projected demand didn’t meet actual demand. Between 1980-81, a staggering $500 billion was invested by the petroleum industry in infrastructure and services, as they were anticipating a higher demand for oil. However, when the demand didn’t materialize, massive losses were suffered triggering an industry-wide price collapse.

The current scenario

Today, every business has vast amounts of data at their disposal – something that was unimaginable in the 1980s. You would expect forecasting demand to be easier theoretically, but businesses have still suffered. While we have improved from before, the age-old, simplistic business rules and reliance on outdated historical data works against us. Our current problem is dealing with the huge inflow of big data to create real-time interventions that are effective and profitable.

Forecasting demand with precision

With behavioral analyticsartificial intelligence and machine learning, businesses are poised to revolutionize demand forecasting:

  • Behavioral analytics focuses more on future-looking customer data rather than historical data, to derive insights into choice patterns and buying decisions. By focusing on the “how” and “why” of customers’ actions, you can get a more accurate reading on expected buying behavior. Combining behavioral analytics with business intelligence can help you take seemingly unrelated data to extrapolate, predict and decipher future trends in customer choice patterns.
  • Artificial intelligence (AI) helps businesses come to strategic interventions with little to no human input. When it comes to forecasting demand, AI enables financial and demand planners to extract knowledge from huge datasets assembled from various external and internal sources. By testing and refining advanced models, AI can go far beyond traditional demand forecasting to predict demand accurately. AI also adapts to changes in supply chain, competition, new products and channels, all in real-time. Machine learning, an application within AI, helps to draw insights and trends that generally go undetected, unlike human-created forecast algorithms. Machine learning allows systems to automatically learn against some measure of truth and improve without being explicitly programmed. By running through vast quantities of data, self-improving algorithms can be created that accurately forecast demand.

Future of demand forecasting

Through a combination of behavioral analysis, AI and machine learning, “intelligent automation” can be applied to enhance existing demand forecasting models. Using applications that leverage AI and machine learning, algorithms can self-learn by examining outputs against a measure of truth to constantly update themselves and evolve. It’s no wonder that 55% of organizations are looking to make major investments in AI over the next two years when it comes to supply chain management, according to a leading industry report. By leveraging future-looking data to run these algorithms, organizations can aim to predict demand more accurately than ever. By using transformative technology, you too can go beyond traditional forecasting!

How OSG can help forecast demand

OSG’s bespoke behavioral and cognitive analytics platform Illuminate, can help you predict demand accurately. Using a combination of historical data and future-looking metrics, Illuminate offers one of the most powerful forecasting methodologies. With Illuminate’s behavioral analytics, historical, transactional and sales data can be modeled with forward leaning behavioral measures. By combining our powerful AI and machine learning algorithms, we can help your business arrive at accurate, real-time forecasts in localized geographies of your choice.

OSG used Illuminate’s forecasting capabilities to help an American seasonal products company optimize their product shelf stocking with one of their channel partners at a store level. By analyzing data from over 4500+ channel partner stores across 1600+ SKUs, OSG was able to forecast that an additional $10 million could be earned in revenues by increasing product availability across channel partner stores.

We hope this information has been valuable and interesting to you. Do feel free to share it with colleagues and others in your network. We welcome discussing this topic with you further by understanding your specific challenges.

Start the conversation by contacting us.

OSG Steps to Success

OSG is a “catalyst” that helps our clients be the best at decoding their customers’ decisions. Our clients have seen a minimum 20% improvement in customer engagement by implementing smart insights delivered using our behavioral analytics products.

Artificial Intelligence in Insurance – Powering You to Effectively Manage Business Risk

Artificial Intelligence in Insurance – Powering You to Effectively Manage Business Risk

Artificial Intelligence (AI) has transformed industries through its evolved predictive capabilities and superior decision making. Whether we talk about retail, hospitality or healthcare, AI has driven exponential growth in each industry. By leveraging app-based AI and machine learning technologies, businesses can be enabled to interpret situations, adapt to changing scenarios and predict outcomes in real-time with nearly no human intervention. This will have a plethora of uses in various industries – including insurance.

AI and the Insurance Industry

Today, the insurance industry is at the cusp of a big paradigm shift. While most sectors are making a relatively seamless shift to AI-driven processes, insurance is struggling due to its unstable nature and high associated risk.

Some of the greatest concerns in the insurance sector today include slow economic growth, limited technological innovations, need for regulations and subdued premium rates among others. Intense market competition is also a big challenge facing insurance giants today. With new InsurTech entrants constantly emerging in the market, traditional insurers need to integrate AI and technology to not get left behind.

AI-powered Opportunities

According to a leading report, AI is set to trigger a 10 – 40% increase in labor productivity in eleven western industrialized countries and Japan. These countries are set to double in economic growth by 2035, according to the projected study. While this seems like a tall order, there’s no denying the positive effects on growth that come with AI. The insurance industry is on track to reap these benefits too. In fact, AI can and is being applied to many facets of insurance, namely:

  • Insurance covers for smart factories, driverless cars, losses due to cybercrime and smart sensors
  • Optimizing processes like risk calculation and prevention, asset management and claims analysis
  • Handling investment decisions with precision, thanks to the vast quantities of unstructured data that companies currently sit on
  • Selection of better investments based on customer preferences, risks and spending patterns
  • Seamless integration with ATMs, mobile payments, and online claims processing so that digitally connected individuals make better decisions by improving transparency in data interpretations

Integrating AI in Insurance Seamlessly – Identifying Challenges and Bridging the Gap

While there are abundant opportunities to leverage AI in insurance, there are some real-world challenges that make the integration rocky. Some of these concerns along with how insurance companies can tackle them are listed below:

  • Negative mindset towards analytics: Insurers are sometimes opposed to fully committing to capable analytics. There is an aversion to adopt technology because of the risk of data leaks. However, to truly leverage AI to its full potential, customer behavior analysis, segmentation and predictive modeling are a must. They are the drivers to set data-powered technologies in motion. Without robust analytics and dashboard visualizations, insurers cannot expect AI to provide deep, strategic insights and decisions. In addition, AI-driven platforms are enabled with stringent security measures to avoid data leaks.
  • Threat of new entrants: Lean and agile InsurTech players are entering the insurance market with affordable, intuitive solutions that reach and serve customers quickly and effectively. To keep up with them, traditional insurance firms must learn to step up their AI-game. We are clearly moving towards a transparent, data-driven, digital world and insurance companies, with their vast amount of data, can become powerhouses if they leverage AI. In fact, according to a leading industry report, insurers are responding positively to this challenge as 67% of leaders believe that AI-driven possibilities and innovation will be critical to their growth.
  • Stakeholder resistance: Very often, insurance companies face resistance from agent channels and distributors to implement AI technology. Due to misguided inhibitions, these stakeholders anticipate risk and are fearful of syncing machine and human labor to maximize productivity. It is therefore essential to alleviate this tension by having a clear proposition on how AI-integration will simplify mundane tasks and improve customer experience. Insurance CEOs are stepping up and helping with this issue as 61% believe that synchronized human and machine functioning will help their businesses gain a competitive advantage.

How can OSG help?

OSG’s bespoke behavioral and cognitive analytics platform can help you manage business risk every step of the way. Powered by OSG Dynamo, our AI-driven big data analytics platform, we can help you analyze your customers’ behavior and choice patterns to deliver superior engagement, lower risk, lower claim and increase engagement exponentially. By identifying sources of fraud and detecting noise to signal ratio, OSG can lower your costs, thereby delivering superior outcomes.

We hope this information has been valuable and interesting to you. Please do feel free to share it with colleagues and others in your network. We welcome discussing this topic further with you and understanding your specific challenges.

OSG Steps to Success

OSG is a “catalyst” that helps our clients be the best at decoding their customers’ decisions. Our clients have seen a minimum 20% improvement in customer engagement by implementing smart insights delivered using our behavioral analytics products.