Tag: indus net technologies

Targeting for Success: Customer Segmentation and Retention Strategies for BFS Companies

Targeting for Success: Customer Segmentation and Retention Strategies for BFS Companies

May 26, 2023

The importance of proper customer retention and customer segmentation is unparalleled in the banking and financial services sector. Retention is crucial since it is always more beneficial to retain more customers who not only add to the BFS company’s revenues and recommend it to others, but are also not as costly to retain in comparison to the acquisition of newer customers. Satisfied and long-term customers are not only more amenable towards price or other fluctuations, but are also more likely to engage in word of mouth recommendations. With proper segmentation, BFS firms can target customers better, depending on their specific needs. Customer retention strategies for BFS companies Here are a few customer retention strategies that BFS firms can use: Customer segmentation and how it is essential for BFS firms Customer segmentation is crucial for banking and financial services firms. Before venturing into data analytics, you should undertake segmentation on the basis of behavioral patterns. This will be influenced by things like preferences for rewards/loyal programs/promotions/deals and also buying patterns, overall frequencies for purchases, and other parameters. This will help you roll out targeted marketing and recommendation campaigns for various segments/groups based on these insights. Customer segmentation involves tailoring your content for ensuring the delivery of more relevant and useful marketing campaigns for specific customer groups in place of choosing generic messaging for everyone. Here are some segmentation strategies that you should follow: Segment-wise communication and engagement strategies, along with tailoring messaging for every segment will help you create better personas of your targeted customers. You can then leverage insights to come up with the best marketing campaigns tailored to customer requirements. FAQs 1. How can BFS companies effectively identify and define their target customer segments? BFS firms can more effectively identify their targeted customer segments and define them better through proper segmentation. They can do this on the basis of data analysis, helping them classify customers on the basis of parameters such as age group, buying habits, patterns, products/services most required, life stage or life cycle in the customer journey, and so on. 2. What are the key benefits of customer segmentation for BFS companies? Customer segmentation helps BFS companies in several ways, enabling them to target specific groups better with tailored marketing campaigns, recommendations, and products and services. BFS firms can know which target groups require specific solutions and offer the same accordingly. 3. What challenges or obstacles do BFS companies face when implementing customer segmentation and retention strategies? BFS companies face a few obstacles in the implementation of customer retention and segmentation strategies. These include the absence of technological expertise, compatibility and integration issues along with the inability to leverage data analytics for enhancing customer experiences and satisfaction alike. 4. How can BFS companies measure the effectiveness and ROI of their customer segmentation and retention initiatives? BFS companies can track the ROI and effectiveness of customer retention and segmentation initiatives by undertaking data analytics relating to parameters such as sales growth across segments, changes in consumer patterns, customer feedback trends, churn rates, and so on.

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Harnessing the Benefits of Hashgraph-Association

Accelerating Business Growth: Harnessing the Benefits of Hashgraph-Association

May 24, 2023

Accelerating business growth with decentralised networks and consensus algorithms is possible with the Hashgraph association. Enterprises require solutions like Hashgraph association for overcoming hurdles in terms of transforming themselves towards developing more Web 3.0 based use cases and using institutional solutions. Some of these potential use cases include developing secure and flexible smart contracts, data privacy mechanisms, decentralised finance, real-time supply chain visibility, innovative loyalty programs, targeted and automated content creation, diverse usage of augmented reality, and a lot more. Blockchain-based transactions and assets are fast becoming more effective ways of doing business for enterprises and this is where they require effective solutions like Hedera Hashgraph. The Hashgraph association is a boon for enterprises in several ways, helping them find ways to explore solutions on Web 3.0. More and more enterprise use cases can be accelerated for development and deployment alike, throughout a proven and efficient framework on the Hedera network. Companies can now build for the future with decentralised and more advanced applications. Why Hashgraph Association? Hedera is one of the most innovative and enterprise-grade public ledgers for a completely decentralised economy. It is also a sustainable solution for enterprises. The Hashgraph Association is a non-profit and independent entity that focuses on developing a better ecosystem for enterprises, startups, and Government institutions worldwide, tapping Hedera Hashgraph capabilities for the design and development of decentralised applications and other solutions. The network at Hedera is developed by a global community on the network that is governed by a council of top industry players including Avery Dennison, Chainlink, Boeing, DLA Piper, Deutsche Telekom, DBS Bank, LG Electronics, Tata Communications, Shinhan Bank, Nomura Holdings, Wipro, and University College London, among many others. Here are some other points worth noting: The management team includes industry experts like Co-Founder & Co-CEO Mance Harmon who has previously served as the Head of Architecture and Labs at Pig Identity, while founding two technology start-ups. Co-CEO and Co-Founder Dr. Leemon Baird is the inventor of the Hashgraph distributed consensus algorithm and the co-founder at Hedera. He has more than 20 years of experience in the technology and startup space, while having been a Professor of Computer Science at the US Air Force Academy and founding multiple startups. A little more about the Hedera Hashgraph Association The Hashgraph association offers grant funding to start-ups, enterprises, and Government programs for developing and executing solutions powered by Hedera. At the same time, there are HBAR grants and other venture development programs for helping create projects with future potential through the Hedera network. The association also assumes the role of a co-investor in big-ticket projects, while empowering enterprises for competing in the digital assets and decentralised finance segment throughout various business areas. There is also an initiative to reach out to Government organisations and backing national blockchain-related initiatives for the promotion of the higher adoption of DLT solutions and contributions towards economic growth. The Hashgraph Innovation Program taps the worldwide network while collaborating with trusted partners. There are ideation and professional training workshops for building the right perspectives required for competing and adapting in the decentralised economy. Other initiatives include design-thinking and modelling proof-of-concepts based on several use cases as explored through the ideation workshops. The Hashgraph association also looks into the development of MVPs or minimum viable products along with integrating Hedera-backed solutions into enterprises. Hence, businesses can benefit greatly from the Hashgraph association with regard to turbocharging and accelerating future growth in a decentralised economy with robust solutions and support with easy implementation throughout the ecosystem.

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Insurtech Revolutionises Insurance with Personalised, Faster, and Affordable Solutions

May 23, 2023

Insurtech is the latest phenomenon that is revolutionising insurance across the spectrum. The insurance industry is innovating with the use of technology with an aim towards making products, services and solutions more affordable, personalised and quicker for customers. Here are some of the digital technology offerings that are playing a major role in this space: AI (Artificial Intelligence)- This is one of the biggest innovations contributing towards automating the processing of claims, enabling better detection of frauds and also enhancing customer service. AI enables more accurate and improved pricing and assessments of risks. It helps insurance companies manage risks better while lowering costs simultaneously. It also ensures that customers get more personalised and cost-effective insurance offerings. 2. IoT- The Internet of Things is another aspect which enables cost reduction and personalisation alike. It also boosts customer experiences greatly. The insurance industry is leveraging IoT devices for collecting information on consumer behaviour and environments, including home security, driving habits, health, and so on. This is facilitating accurate assessments of risks and pricing, while helping develop new products tailored to customer needs. For example, IoT devices may be used to develop insurance products where customers are charged on actual driving distance and usage. 3. Blockchain– This digital technology functions through distributed ledgers, enabling transparent and secure transactions without centralised intermediaries. It is being used in insurtech for streamlining the processing of claims and lowering frauds along with enhancing overall data security too. 4. Mobile Apps- Insurtech also functions through new-age mobile apps for boosting customer experience and making claims processing simpler. Customers are getting more personalised recommendations and higher control over their policies. Mobile apps are also being used for tracking the status of claims, managing policy data, and getting personalised advice on products based on their behaviour and specific requirements. 5. Telematics- It is already being used for gathering data on customer driving behaviour and performance, enabling more accurate assessments of risks along with better pricing strategies. Products are thus tailored to meet the needs of customers in a more personalised manner. Why insurtech is gaining ground in the insurance industry These are some of the chief reasons behind the rising popularity of insurtech solutions throughout the mainstream insurance sector. FAQs 1. Can Insurtech solutions replace traditional insurance providers? Insurtech solutions can be replacements for conventional insurance offerings. However, they will not replace traditional providers completely. Rather, these companies will work closely with insurtech players to come up with better products and services for their customers. 2. Are Insurtech solutions regulated? The insurance industry is one of the highest-regulated sectors in the world. Insurtech is also similarly regulated since it is used by insurance companies for carrying out many of their functions. 3. How does Insurtech impact the insurance industry? Insurtech positively impacts the insurance industry by helping it reduce costs, automating manual and repetitive tasks, personalising customer experiences, scaling up overall efficiency, and making products/services more affordable for customers. Customers get more control over their journey with the insurance company and wait times are reduced considerably as well. 4. How can Insurtech solutions improve claims processing? Insurtech solutions can automate claims processing, thereby saving time and money for the company. They can gather data and verify the same minutely in quick time, while also eliminating frauds alongside. This leads to more accurate processing of claims without any risks of losses/fraud.

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The concept of DAOs: Decentralized Autonomous Organizations

The concept of DAOs: Decentralised Autonomous Organisations

May 16, 2023

Decentralised autonomous organisations (DAOs) have been making waves lately, throughout the technology spectrum. DAOs are specific management structures leveraging blockchain technologies for automating a few aspects of transaction processing and voting. There is no central legal entity involved in decentralised autonomous organisations (DAOs) that holds responsibility for the regulation of the projects. There is smooth governance and transparency ensured through the decentralisation mechanism and distributed ledger technology. Smart contracts are made and tested for ensuring that vital details are not missed. Tokens are used as incentives for all validators in DAOs, ensuring their active, swift, and fair participation. DAOs have wide applications throughout the blockchain, including cryptocurrencies and Web 3.0 which is the proposed new-generation web architecture driven by decentralisation. The future blueprint here is that decentralised autonomous organisations or DAOs may enable easier creation of decentralised entities that respect stakeholder interests outside any one party’s control. They may be used for raise funds for specific purposes/projects while forming newer business mechanisms. They may also enable future automation of several financial steps and processes on blockchain platforms, making sure that stakeholders get compensation as per universally-agreed rules, while automating shared votes based on specific support, investment levels, or even engagement. How it could pan out for decentralised autonomous organisations? Many industry players feel that decentralised autonomous organisations or DAOs may eventually replace the inherent trust quotient in personal ties or with central authorities through specially-made blockchain smart contracts. DAOs may also automate a model where every stakeholder gets adequate compensation and a long-term project stake. Here are a few key points worth noting in this regard: However, there are a few disadvantages of decentralised autonomous organisations or DAOs. Automated smart contracts may be hard to tweak whenever any problem is found, while hackers may also find some loopholes for the illegal misappropriation of funds against stakeholder interests. Participants may also shell out higher transaction charges for every transaction, while human intervention will also be necessary for the implementation of legal and physical procedures. The legal applicability and status of DAOs is still being understood by global authorities, which mean current risks for all investors.  DAOs are still in their infancy. In the short term, they could have a major effect on overall fundraising for particular projects/objectives. Several services that promote causes will find them effective in the near future, enabling voting by participants alongside. DAOs may also enable newer investment entities while automating the procedure of returning money to all participants. DAOs may eventually help establish decentralised business models for support and investments alike. Participants may get tokens for their support and long-term stake in any venture. It is early days as of yet, although DAOs could well transform into some of the most exciting future trends. FAQs What are the benefits of a DAO? DAOs ensure automated procedural efficiency along with higher transparency and the absence of any central authority. It will enable swifter fundraising while enabling streamlined distribution of incentives/rewards/returns simultaneously. Are DAOs legal? The first U.S. State to legally recognise DAOs was Wyoming in 2021. They were recognised as limited liability companies, giving them a defined corporate structure and legal protection. Some other States are also considering the legalities of DAOs, while they are also attaining legal status in several other countries. What are the risks associated with participating in a DAO? DAOs are still works in progress, with several authorities yet to recognise them legally. This presents risks for participants, including personal liability. Any DAO participant may be liable for any action taken by an organisation, even when it was not personally authorised by him/her. What is the difference between a DAO and a traditional organisation? Any traditional organisation has its own centralised and legal entity. This is absent in a decentralised autonomous organisation (DAO).

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The Power of Data: How Analytics is Revolutionising Debt Collection in BFS

May 10, 2023

Data, as always, is proving to be the real game-changer for BFS (banking and financial sector) companies. Analytics is driving higher efficiencies and benefits for BFS players, including debt collection. What is the role of analytics in BFSI debt collection? Here’s finding out. With regard to better engagement with consumers for debt collection, BFS players have always depended on conventional models including phone calls and emails/letters. The aim here is application in bulk, which has often led to several experiences that are not as pleasant for both parties (borrowers and lenders). Customers now expect increasing personalisation with diverse requirements and preferences. By tapping machine learning, AI, and predictive analytics, companies are now acting on data-based insights while resolving several problems across sectors, including debt collections. It has led to simpler, faster, and easier systems and procedures for consumers and banks alike, with advanced data science abilities providing teams cutting-edge tools that they require for higher transparency and standardising operational processes.  How is data analytics transforming debt collections for BFS entities? Here are some of the ways in which analytics is gradually revolutionising debt collections for banks and financial service providers. A. Building custom outreach strategies- Debt collection is not only about physically reaching out to borrowers. The blueprint has to be wider today, in sync with fast-changing banking ecosystems. Personalising the outreach to borrowers across types and personas, with stage-based plans across channels (deriving from anticipated consumer responses at each stage) is highly necessary for BFS entities today. Data and analytics is now spurring decision-making throughout the entire value chain of collections, along with saving time, energy, and costs for companies simultaneously.  B. Debt resolution strategies- Analytics has enabled better debt resolution blueprints on the basis of insights. These include the following aspects: Risk Classification of Borrowers- ML-based algorithms can accurately forecast the chances of delinquency of borrowers, deploying innumerable parameters as inputs. Due to resource limitations, calling every defaulter is next to impossible, not to mention the need to engage debtors, to avoid future non-payment risks and delinquencies. Hence, analytics is what enables hyper-personalisation in this case, enabling agents to communicate the right message in specific scenarios to particular groups of customers.  Channel Forecasts- On the basis of insights on earlier communication and behaviour of customers, BFS companies can predict the suitable template, channel, frequency, language, and time to contact borrowers. Several borrowers also prefer digital communication and their preferences may be better identified by algorithms. Optimising Blueprints- Tracking real-time borrower behaviour throughout multiple channels enables the creation of a personalised blueprint and mechanism for debt collection. Predicting Intent-to-Pay– It encompasses forecasting the willingness of borrowers to repay the money, based on outreach measures and historical measures for working out the priorities for the coming day in terms of tele-calling or other outreach initiatives.  Internal transaction information, when fused with other factors and behavioural triggers can predict delinquencies, while enabling BFS companies to accurately build pro-active strategies for customer outreach. For instance, lenders may swiftly gain a perspective of customers’ aggrieved/negative reactions or reducing account balance and their inter-relationships. Better Borrower Understanding- Using analytics for debt collections will enable an examination of transactional, demographic, and behavioural information.  This will help BFS players gain a better understanding of consumers, while identifying specific patterns and getting insights that help them develop strategic blueprints for collections.  Monitoring borrower responses to several types of messages is also helpful in determining ideal frequencies for interaction and suitable timelines. Risk-driven segmentation may also be useful for better targeting. Insight-Driven Debt Collection Decisions- Debt collection decisions can be taken in a better way, driven by analytics-based insights. Segmentation, predictive systems, deep behavioural analysis, and other blueprints are all possible for BFS companies. Insights are helpful for warning banking entities early regarding delinquencies and defaults in the future. It will help banks work out when people are likely to default and come up with custom strategies for mitigating these situations. These insights also help build suitable responses for interactions with borrowers. Issues with continual follow-up communication will be resolved with data-based intelligence. Banking entities will have suitable knowledge for catering to customers with suitable details at the right times.  Building Personalised Relationships- Customer relationships and experiences are crucial aspects for all BFS entities. Data-driven insights and analytics may help greatly in both these departments. Lenders can have language/region-based responses for customers. As can be seen, data analytics can completely transform debt collections for banks and financial services players. Data errors, incorrect entry, issues with detecting frauds have been identified and resolved with smart and new-age AI-based tools. At the same time, debt collection can be enhanced greatly through better insights and real-time visibility into the process. From reaching out to customers at the right time and with personalised offerings, to improving engagement and scaling up predictive/forecasting abilities, it enables BFS players to resolve long-standing problems and convert debt collection into a seamless and standardised process. FAQs 1. What is debt collection in BFS? Debt collection refers to the mechanism for collecting and recovering unpaid/due debt from borrowers.  2. What kind of data is collected and analysed for debt collection? The types of data collected and analysed for debt collection include historical customer data on engagement and interactions, behavioural data, preferences, demographic data, socio-economic and macro-economic data, past financial transaction history of customers, and more.  3. What are the benefits of using data analytics in debt collection? There are several benefits of using data analytics for debt collection, including customising communication and outreach with borrowers, predicting/forecasting future chances of defaults and non-payment, working out better debt collection strategies, and standardising the process.  4. Can data analytics help in predicting future defaulters? Data analytics can be immensely helpful in the prediction of future customer defaults, through generating insights on past purchasing behaviour, financial history, transaction history, and many other parameters. This helps banking and financial services companies forecast the likelihood of defaults and take pro-active steps accordingly.

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Hackathon Diaries #7 - The Third Eye

Hackathon Diaries #7 – The Third Eye

May 5, 2023

Greetings, fellow coders and tech enthusiasts. It’s the 7th and final edition of the INT. Hackathon Diaries V1.0. But don’t shed a tear just yet, we will be back soon with the next edition as our in-house masterminds are up and running with new and innovative ideas all the time. We’ve saved one of the bests for last, and it’s a project sure to keep you wide awake: The Third Eye – Driver’s Drowsiness and Mobile Distraction Detection Solution. The Third Eye We all know how dangerous driving is when we’re tired or distracted. It’s like playing Russian roulette with our lives, and those of everyone else on the road. But fear not, as The Third Eye team has come up with a solution that’s so clever, it’ll make you wonder why nobody thought of it before. Using the latest computer vision and machine learning technology, The Third Eye system monitors drivers in real time, watching for telltale signs of drowsiness or distraction. It’s like having a personal wake-up call or a stern aunt, reminding you to keep your eyes on the road and your hands on the wheel. It is to create the leeway to a sustainable and protected world while driving. The Team Arijit Datta Arnab Kanti Ghosh Pabitra Bhunia Nitesh Kumar Singh Rahul Lohar Suva Samanta Explosive Growth in the Market  Per recent reports, the global market for drowsiness monitoring systems was valued at a staggering $2.2 billion in 2019 and is projected to grow to $3.3 billion by 2027 with a CAGR of 5.2% during the forecast period.  But that’s not all, folks. The global market for distracted driving prevention technology is expected to explode from $1.27 billion in 2019 to a whopping $2.9 billion by 2025, with a CAGR of 12.7% during the forecast period.  These numbers speak volumes about the urgent need for cutting-edge solutions that keep drivers alert and focused behind the wheel. So get ready to join the race to the top as we explore the latest developments in driver safety technology that are taking the market by storm. Resolution Realms Scope 1 – Drowsiness Detection Prepare the dataset: Collect and prepare data for drowsiness detection. Augment the data: Improve the model’s performance by data augmentation techniques. Split the dataset: Divide the prepared dataset into training and testing sets. Configure the model: Customise the YOLOv5 model for drowsiness detection by modifying configuration files to specify hyperparameters, input image size, and a number of classes. Train the model: Train the YOLOv5 model using the prepared training set and the configured model. Evaluation: Measure the model’s performance on the testing set using evaluation metrics such as precision, recall, and F1 score. Fine-tune: Adjust the hyperparameters and retrain the model on the entire dataset or a subset of it to fine-tune the model. Deployment: Integrate the trained model into a mobile or web application for real-world drowsiness detection. Scope 2 – Mobile Phone Distraction Data collection: Gather a dataset of images depicting instances of mobile phone distraction. Data Preparation: Transform the annotations into a format that is compatible with YOLOv5, such as COCO or YOLO. Model configuration: Set up the YOLOv5 model to recognize mobile phone distractions. Model training: Employ a deep learning framework like TensorFlow or PyTorch to train the YOLOv5 model on the training set. Evaluation: Test the trained model on the test set to determine its accuracy and performance. Deployment: Deploy the trained model onto our device. Alert mode: Once our device detects a driver using a mobile phone while driving, it will emit a continuous alert message until the driver puts down the phone. Tech Stack AI/ML Azure Map Service Smart Band Edge Computing  IoT Wow Factors Scene 1: Driver wearing sunglasses Infrared (IR) cameras detect the heat signatures of objects, including human eyes, even when they are partially obstructed by sunglasses. Scene 2: Driving at night Night Vision Camera tracks the driver’s face and eye movements. Scene 3: Presence of multiple faces before the camera Detection of only the front face. Conclusion Stay tuned and keep your eyes peeled for the next edition, where we’ll bring you more cutting-edge solutions and innovations that are driving the industry forward. See you there.

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The benefits of adopting telematics in auto insurance

The Benefits Of Adopting Telematics In Auto Insurance

April 25, 2023

Telematics systems have become mainstream throughout the automotive industry. Many experts feel they have the potential to completely revolutionise and transform the sector. Based on reports by Bloomberg NEF, close to 1.2 billion cars were plying in the year 2022, while this could reach a staggering 1.5 billion vehicles by the year 2039 as per estimates. This naturally calls for a revamped auto insurance mechanism, which takes things like driver behavior into account. This has been an offshoot of the usage-based insurance model in the automotive insurance space. Due to the continual increase in car volumes, the global auto sector is poised to touch a staggering USD$1.4 trillion in revenues by the year 2040. This will be backed by stringent regulations worldwide which make insurance coverage compulsory, along with systems for tracking and penalties, in order to scale up auto insurance penetration throughout owners. In a more traditional context, insurance companies usually emphasised upon things like the vehicle age, location, and motor vehicle reports for working out the premiums and risks.  However, telematics systems are now enabling the evaluation of driving habits with a view towards more effective estimates of risks and pricing. These programs are increasingly driven by technologies like IoT (Internet of Things) and data analytics, thereby becoming disruptors for the segment in recent years. If you look at it objectively, North America is already the biggest market for telematics-driven insurance, with close to a whopping 22 million policies active from top companies. The global market for telematics systems in insurance should touch USD$6.2 billion in 2025, indicating 22.7% in CAGR (compounded annual growth rate) as per Grand View Research reports. What does this tell us? Telematics is here to stay.  What is telematics and how is it relevant in insurance? UBI (usage-based interface) or telematics fuses informatics and telecommunications, which is the foundation for data processing, with an aim towards retrieval and storage.  Insurers put tracking devices into vehicles which receive, store, and send telemetry information/data on the onboard diagnostics of the vehicle, enabling wireless communication. Vehicle-based data is collected, including the location, speed, harsh braking, idle time, and fuel consumption. This is given on a real-time basis to car owners and insurance companies via tracking devices or smartphone apps. What are the biggest advantages of telematics? Some of the top advantages of telematics systems in vehicles include the following:  Insured policyholders can lower their premium costs through the adoption of safe driving practices/habits.  Insurance companies can better analyse risks of possible accidents and predict the possibilities of claims in the future.  Insurance companies can provide rewards and value-added incentives for scaling up customer retention, loyalty, and satisfaction.  Insurance companies have a much fairer and more effective method of risk and premium estimation with telematics.  Telematics offers valid and accurate data regarding the vehicle functions and driver behavior, which ensure actionable insights for processing claims. It also contributes towards reducing any fraudulent claims or losses.  Insurance companies are seeing the evolution of models like distance-based/pay how you drive/pay as you drive/control your drive insurance options.  Dashboard cameras in tandem with telematics can help insurers gain better insights on the reasons behind accidents and get more knowledge of the same.  Telematics in insurance removes several hurdles throughout the supply chain, right from underwriting and claims management to serving customers.  These devices also lead to higher awareness and alertness amongst drivers who wish to improve their driving behavior, patterns, and scores. Hence, it may contribute towards lower accidents on the road.  These technologies may contribute greatly towards lowering crime rates globally.  Telematics can thus be a major boon in the auto insurance space, with huge potential not just for personal vehicle insurance, but also for fleets and logistics players. It offers more transparency in premium and risk evaluation, while lowering the chances of accidents and other mishaps. It will keep evolving gradually throughout the world, until it becomes an accepted form of auto insurance. At the moment, it is steadily being recognised and implemented by insurance companies and should have its boom moment in the near future. FAQs How can telematics be used in auto insurance? Auto insurance companies can use telematics to determine the driving behavior and vehicle operations of policyholders, using actionable data for evaluating risks and premiums. Telematics can also offer higher insights on mishaps and accidents, thereby helping with claims management.  What are the benefits of using telematics in auto insurance? Telematics helps in accurately estimating risks of policyholders and their premiums. Good drivers get incentivised with lower premiums and rewards. At the same time, fraudulent claims and losses are minimised with this system.  What are the challenges of implementing telematics in auto insurance? Some of the challenges include data privacy and other regulations, since location-based information is received, stored, and shared. Other challenges include technological integration and awareness-building.  Are there any examples of successful implementation of telematics in auto insurance? Some examples of telematics-based auto insurance models include control your drive, pay as you drive, pay how you drive, and distance-based insurance.

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The emergence of decentralised finance (DeFi) and the potential impact on traditional banking and financial services

The Emergence Of Decentralised Finance (DeFi) And The Potential Impact On Traditional Banking And Financial Services

April 24, 2023

Decentralised finance (DeFi) has made a huge splash worldwide, with its potential for traditional banking disruption. It is a rapidly growing financial technology that uses secured and distributed ledgers, based on blockchain and smart contracts, just like cryptocurrencies. But how is it contributing towards disruption or financial services innovation? In the U.S., for instance, the SEC (Securities and Exchange Commission) and Federal Reserve have clearly outlined the regulations for centralised financial entities such as brokerages and banks that customers depend on accessing financial services and capital directly. DeFi poses a challenge to this centralised financial setup through empowering people with peer-to-peer digital transfers/exchanges. It also contributes towards the elimination of fees charged by financial institutions and banks for the usage of specific services. Those holding their money in secure digital wallets can instantly transfer funds, while anyone with internet can make use of DeFi. What is centralised finance? For understanding decentralised finance, one should first have an idea of what centralised finance is all about. Here are some core points worth noting in this regard:  Centralised finance has the money held by the banks and third parties. They are the ones who enable money transfers across multiple parties, each of them charging fees for the usage of services.  Networks clear charges and request payments from banks. Every chain entity gets payments for services provided.  All transactions are supervised in this system, right from local banking services to applying for loans. How does decentralised finance (DeFi) work? Decentralised finance (DeFi) has huge potential for traditional banking disruption. Here are some points worth noting:  This system does away with intermediaries by enabling merchants, individuals, and businesses to take care of financial transactions with new and emerging technologies.  DeFi makes use of security protocols, software, connectivity, and hardware advancements via peer-to-peer financial networks.  Individuals can easily trade, lend, or borrow funds whenever they get an internet connection, using software for verifying and recording financial transactions throughout financial databases that are distributed.  Distributed databases are those which are readily accessible throughout multiple locations, gathering and aggregating data across users and leveraging a consensus-based mechanism for verification.  Decentralised finance (DeFi) does away with the need for any centralised financing model, through enabling any individual to make use of financial services almost anywhere, irrespective of their identity or location. DeFi applications enable higher control over funds for users via personal wallets and trading solutions catering to individuals.  Decentralised finance does not ensure complete anonymity. Transactions, while not having individual names, can be traced throughout all entities with access, including the law and Governments.  DeFi makes use of blockchain technology as used by cryptocurrencies. The blockchain is the secured and distributed ledger/database. Transactions get recorded through blocks and verified by users. Once verifiers agree to transactions, the blocks are closed and then encrypted. Another block is made with data on the earlier block within the same. The blocks are conjoined through data in every proceeding block, which gives it the blockchain moniker. Information in earlier blocks cannot be modified without any effect on the following ones. Hence, there is no way to change a blockchain.  How DeFi is being used in the financial sector Decentralised finance (DeFi) is being used widely in the financial sector, with the following being the major take-aways:   P2P (peer-to-peer) financial transactions, right from payments through applications and issuing loans.  DeFi is enabling direct interest rate negotiation between two parties and lending through its networks, equating to lower fees.  Anyone with internet can access DeFi platforms and there are no locational limitations on transactions.  Smart contracts on blockchain and records of competed transactions can be easily reviewed and are immutable.  Income-generation and capital transfer abilities for investors with high security. Here’s how it is disrupting traditional protocols: DeFi is enabling lending/borrowing at scale between unknown parties and minus intermediaries with automatic setting of interest rates, based on demand and supply. Loans are secured through over-collateralisation, with loan access anywhere and anytime.  DeFi is also enabling the de-centralised trading and development of derivatives for various assets like commodities, stocks, and even currencies. Decentralised asset management for cryptocurrency is another growing trend.  Decentralised exchange concepts have come up, with cryptocurrency holders no longer needing to leave the arena for token swapping. DEX has several smart contracts with reserves of liquidity, operating as per pre-defined mechanisms of pricing.  Decentralised insurance is also available, covering bugs for smart contracts in this entirely new space. This is a major risk area for DeFi users, and is covered by these plans.  As can be seen, crypto-based decentralised finance has already reached an advanced stage in terms of its evolution. It is steadily taking care of all the necessary functions of a financial system as a result. DeFi could well be the next big thing in global finance, provided it can navigate security threats successfully.  FAQs What is decentralised finance (DeFi) and how does it differ from traditional finance? Decentralised finance is where distributed and secured ledgers are used with blockchain technology like cryptocurrencies. It means peer-to-peer transfers without higher fees for transactions as charged by all the entities in a traditional transaction chain. It can enable anytime and anywhere transactions between unknown parties, with automatic conditions and smart contracts, eliminating intermediaries.  How does DeFi work and what are the key components of DeFi platforms?  The main components include specific hardware, software, stablecoins, and so on. The infrastructure is continually evolving, and the system works through an independent yet secured and highly traceable network on the blockchain. Transactions are recorded, stored, and are verifiable easily. At the same time, there are no intermediaries and resultant charges. Parties can directly engage in transactions with automatic setting of interest rates or other crucial parameters.  What are the potential advantages of DeFi over traditional finance?  DeFi is a transparent and open system as compared to the closed and centralised system followed by traditional financial institutions. Transactions are public and may be viewed by any individual. They are readily traceable as well. At

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The future of EHRs and their impacts in patient care

The Future Of Electronic Health Records (EHRs) And Their Impact On Patient Care

April 18, 2023

Electronic health records (EHRs) have stolen a march over not just conventional paper-based records, but also electronic medical records or EMRs in several ways. The EMR vs. EHR debate can be put to rest with reports by Grand View Research that indicate how the global EHR market has achieved a valuation of $28.1 billion in 2022, with expectations of it touching $38.5 billion by 2030, growing by 4% (CAGR-compounded annual growth rate). EHR implementation has become a foundational activity for healthcare players, functioning as digital or electronic patient records, including all vital data from notes and prescribed medicines to the history of symptoms and vital signs, radiology reports, lab information, and a lot more. The entire clinical history of a patient is comprehensively held in EHRs while they also enable better optimisation and automation of workflows for healthcare providers, thereby contributing towards improved patient care at multiple levels. They also enable easier access to evidence-based tools for providers to come up with specific recommendations for patient care, which is another plus point to be noted in this context. Deloitte reports state that factors like the interoperability of data, data-sharing, and growing consumerism will fuel a transformation of the healthcare sector by 2030, with electronic health records (EHRs) becoming key catalysts of this change. Key Aspects Related To EHRs In The Healthcare Industry The industry is now transitioning towards a more value-based model of patient care, with specific requirements for suitable EHRs from this perspective. Here are some additional points that you should also keep in mind:  Future EHR Trends Here are a few future trends related to electronic health records (EHRs) that should be noted:  It is pertinent to note that EHRs will play a vital role in lowering the time for documenting and maintaining patient records. They will also enable quicker and easier access to entire medical records and the history of patients while enabling quicker decision-making and personalised recommendations for improved patient care. They will also help boost relationships between patients and providers due to this personalised approach and easier access to entire interoperable data records and histories. Participatory healthcare is the new buzzword today, where patients collaborate with their providers on their treatment journeys and decision-making. EHRs represent a pivotal step in enabling better outcomes for patients while offering clear benefits for the entire healthcare system at large. FAQs What are electronic health records (EHRs), and how do they differ from traditional paper-based records? Electronic health records are digital forms of patient records and data. They are different from paper-based records which have limitations in terms of space and legibility. EHRs enable electronic data recording and full understanding while being encrypted for higher security, unlike paper records which are vulnerable to damages, theft, exposure, transcription, copying, faxing, and scanning. How have EHRs evolved over time, and what are some of the latest trends in EHR technology? EHRs have greatly evolved over time to include more efficient capturing of data while automating several data-gathering procedures alongside. Automation has also enabled easier searching mechanisms alongside. EHRs are witnessing several trends including better result management, voice assistance, cloud platforms, better interoperability across systems, patient support and resource mechanisms, and reporting functions. What are some of the challenges associated with implementing EHR systems in healthcare organisations? Some of the challenges include the implementation costs and resistance by healthcare personnel, along with the lack of proper digital training and knowledge. Training takes a lot of time, while data privacy and migration remain concerns as well. How do EHRs enable collaboration between healthcare providers and improve care coordination? EHRs enable better coordination and collaboration across healthcare providers for patient care and other purposes. It enhances patient care quality through interoperability and easy access to data across departments and healthcare providers. EHRs enable seamless access to patient records, enabling personalised recommendations and faster treatment decisions.

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Addressing drug shortages with advanced analytics

Addressing drug shortages with advanced analytics

April 3, 2023

Drug shortages have become a part and parcel of modern healthcare systems due to several reasons. While there is a sizeable economic impact of drug shortages for manufacturers and pharmacies alike, there are widespread community and social disadvantages as well. Pharmacies or clinics running out of medicine stocks are representatives of a scenario that is often witnessed worldwide and with frightening consequences.  For example, Europe is already seeing shortages of commonly-used medicines. A survey by the Pharmaceutical Group of the European Union (EU) had 100% of 29 member nations reporting shortages of medicines amongst community pharmacists. 76% also stated how shortages had worsened than the earlier year (the survey was implemented between 14th November and 31st December 2022). The UK is also witnessing HRT shortages according to reports, while hospitals in the U.S. are also reporting issues with procurement for liquid ibuprofen, while ADHD diagnoses have gone up in the U.S. as well, leading to shortages of vital drugs for the same. Mexico is witnessing chronic shortages and unfulfilled prescriptions and supply fluctuations and disruptions have been seen widely throughout Asia too.  What are the reasons for medicine shortages?  Wondering about the reason for drug shortages? There are quite a few that can be noted in this context:  Higher seasonal illness outbreaks in the aftermath of COVID-19, leading to skyrocketing average annual demand for medicines that is higher than normal in several categories.  The inability of pharmaceutical companies to meet such unprecedented demand, with excess capacity restricted for cost control.  Global supply chain impact along with higher energy costs and inflation have impacted global drug manufacturers who have to contend with pricing measures.  Stockpiling by customers due to sudden drug shortages.  Over-prescribing by the system.  Reports estimate that the National Health Service in the UK loses a whopping 300 million pounds annually owing to partially-used or unused medication which cannot be reused or recycled.  Lack of systems for forecasting and identifying supply shortages, while ensuring proper inventory management.  Drug Shortage Solutions That May Work  There are a few drug shortage solutions that may be effective for combating and reducing shortages.  Data and analytics are enabling better access towards medicines worldwide while enabling superior supply and demand management for individual patients and pharmacies alike.  Real-time pharmacy, hospital, and clinical data will enable a proper understanding of the demand for specific drugs/medical products.  Leveraging electronic and public health records for enabling healthcare stakeholders to report demand figures for drugs, without revealing confidential patient data.  Opportunities for better inventory and supply chain management with AI (artificial intelligence) and machine learning (ML).  Generic entities may leverage smarter technologies for lowering manufacturing costs by up to 20% while enhancing production. Smarter and connected factories with proper insights and data analysis can enable higher savings and reliable deliveries.  Companies may look at higher procurement of local active ingredients while depending on go-to nations for the same. Boosting supply and production levels, along with harnessing real-time data analytics will enable tackling this scenario.  Supervised machine learning and analytics models can help in forecasting/predicting shortages for most drugs used throughout various categories, price points, and age groups.  Modelling can enable healthcare stakeholders to understand more about the issues behind drug shortages while analytics can also help predict demand for specific drugs based on historical data and current trends.  Pharmacies and other players may not have access to data on the supply side, although they have demand-side information. They will be able to gain more visibility into the supply chains of manufacturers with an integrated information-sharing system.  Data analytics-driven insights for optimizing orders and eventually lowering the effect of drug shortages on pharmaceutical and healthcare operations.  Systems for tracking and reporting drug shortages, including aspects like the frequency, drugs involved, period, causes, duration, managing strategies, impacts, and future shortages too.  Real-time identification and tracking of patients receiving shorter supplies of drugs by hospitals, clinics, and pharmacies. Immediate patient identification regulations for capturing present drug utilization across multiple categories.  Real-time identification and addressing situations along with finding out drugs in shorter supply. Predictive abilities enable higher time for researching material for alternative agents or making suitable arrangements for drug acquisition from other sites or facilities.  Once supply levels normalize for a drug, pharmacists and healthcare stakeholders may discontinue their surveillance regulations without waiting for technical assistance. Real-time data-filtering and reporting abilities are leveraged for viewing drug usage trends and prescription patterns throughout healthcare systems. These insights may enable higher standardization of drug management across institutions, while also facilitating better training of clinicians for lowering care variations.  Advanced data analytics will help address drug shortages and enable better inventory management simultaneously. However, suitable implementation, technological integration, and awareness are necessary for the same.  FAQs How can advanced analytics be used to address drug shortages? Advanced analytics can be deployed for tackling drug shortages through real-time tracking and surveillance of prescription trends and drug demand, forecasting shortages, and enabling better drug supply management.  What are the benefits of using advanced analytics to address drug shortages? Advanced analytics goes a long way towards helping tackle drug shortages, enabling forecasting future demand and shortages, identifying patterns for better management, and also enabling better global medicine access.  What are the challenges of using advanced analytics to address drug shortages? Challenges include technological integration, legacy systems integration, awareness regarding best practices, quality data generation, and more.  What are the best practices for implementing advanced analytics for drug shortage management? Best practices include unified and integrated public databases, suitable data modelling systems, suitable protocols for data security and privacy, and swift reporting mechanisms for demand and shortages.

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