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of Management, 14. Ali, M.M.M. and Deshmukh, A.A., 2023. A STUDY ON CONSUMER PERCEPTION TOWARDS ADOPTION OF E -VEHICLE IN SANGLI CITY. The Online Journal of Distance Education and e -Learning, 11(2). Khalid, A.M. and Khuman, Y.S.C., 2022. Electric Vehicles as a Means to Sustainable Consumption: Improving Adoption and P...
Applications (pp. 331 -344). Cham: Springer Internatio nal Publishing. Chakraborty, R. and Chakravarty, S., 2023. Factors affecting acceptance of electric two -wheelers in India: a discrete choice survey. Transport policy, 132, pp.27 -41. Vasudevan, V., Agarwala, R. and Dash, S., 2021. Is vehicle ownership in urban ind...
MOTOR INSURANCE 7.1 MOTOR OWN DAMAGE INSURANCE With new liberalization policies encouraging FII (Foreign Institutional Investment), Automobile giants all over the world started establishing their base in the Indian Market with companies like Hyundai, Ford etc. flooding the market with technologically advanced new model...
f or carriage of goods, which are his properties, or carriage of goods, which are necessary for the purpose of his business. ii. Good carrying vehicle (public carriers ): The owner of the transport vehicle who uses the vehicles only for carriage of goods, wh ich are not his properties, or carriage of goods, which are n...
policy which covers Accidental Damage to the vehicle involved in an accident along with or in addition to the third party liability.  Liability only with Fire andor theft only of the vehicle to be insured in addition to third party liability. This decision is taken by the underwriter after considering the various fac...
means Malicious Act Terrorist activity Whilst in transit by railinland water wayRock slide Accidental external means the happening of something unexpected or unforeseen and it excludes loss arising from natural causes within. The word external refers to outwardly visible. It means that what is not internal. Examp...
any right to the order of the court. Transfer of Policy in case of change of Ownership : The policy benefits stand to accrue to the buyer of the vehicle once sale consideration is paid and suitable endorsements made in the certificate of registration provided the transfer of insurance from the original owner to the new...
pay the premium on short period basis. The premium for short period is slightly higher than the regular premium -rating factor. It means policy for short period is more expensive than normal annual policies. Situations under which short period premium is collected i. When the policy is issued for a period less than 12 ...
quantum chosen by the insured as per tariff . Concession for Laid -Up Vehicle: If a vehicle is laid up in garage and is not put to use for a continuous period of more than 2 months, the liability of the insurers under the liability risk section of the policy is suspended for such period and a concess ion is given to th...
caused by nuclear weapons material is not admissible. No claim due to war, warlike operations The premium must be calculated in accordance with the premium computation tables appearing in the tariff separately for different types of vehicles. Rate of premium is different for accidental damages to the insured’s own ve...
the cause of accident, the perils insured, he arrives at the cost of repairs, cos t of replacement of parts and the salvage value. He then discusses and negotiates with the repairer to arrive at a consensus and authorizes the repairers to carry out the repair work relevant to the accident. Under this repair basis, the ...
is to be issued only in FORM 51 in terms of Rule 141 of Central Motor Vehicles Rules 1989.  Nil Depreciation cover - Differe nt Insurers have different Add -On Covers as per material filed by them under File and Use guidelines but with Nil Depreciation Add-On Cover, no depreciation is applicable in case of replacement...
the purpose of dealing third party claims. Deathproperty damage of third party is caused due to the fault of the driver. The vehicle owne r being the master becomes vicariously liable for the fault committed by the servant (driver) under the law of Tort. Similarly employer is liable for the damage caused to employees c...
Heliyon 10 (2024) e27252Available online 29 February 20242405-8440/© 2024 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC license( ).Research article A new improved randomized response model with application to compulsory motor insurance Ahmad M. Aboalkhaira,b,**, A.M. Elshehaw...
may also appear, among which is the non-sampling error bias resulting from “response effects ” such as refusing to respond or untruthful reporting. Before the randomized response technique (RRT) was introduced, little progress has been made towards the solutions of these issues. Randomized response (RR) is a method use...
who focused on reducing the variance of the estimate and improving the efficiency of the model, whether by suggesting parameter selection according to specific criteria that ensures minimizing the variance, or through using different estimation methods, or, mostly, via suggesting a design modification to the original m...
by The World Bank shed some light on this issue in developing countries and emphasizes the importance of this type of insurance for road safety, personal responsibility, and safe transport systems in these countries. The report raises an issue of awareness pointing that car owners tend to think of motor insurance as a ...
however, choosing big values for p leads to the loss of the advantages of confidentiality and that the bias rising from incomplete or untruthful answers dominates the mean square error. That is because the efficiency of the randomized response estimate depends on the psychological reaction of the respondents to the par...
by inserting Eq. (9) in Eq. (8). □ To check the validity of Eq. (5), if we replace Q with q1 , we can get the variance of Warner ’s estimate as given by Eq. (2). Theorem 2. An unbiased estimator of V √π∗is }V }π∗}α 1}α12Q2\ n1 (10) Proof of Theorem 2. Taking expectation on both sides of Eq. (10), the result is h...
value of q1 and q2. Fig. 3 (a – d) shows the difference, in terms of efficiency, between Mangat & Singh ’s model and the proposed model at practicable values of q1 and the different values of q2 and q3. Positive values are in favor of the proposed model. From Fig. 3, it may be noted that. 1 For all different values of ...
model was applied through an experimental study in which the population was final year male undergraduate students within a college of business who 1. own or drive a car (which is very common among university male students) and 2. have knowledge of the basics of risk and insurance. The rationale behind this selection w...
for √π∗is (0.018, 0.357). 4.Discussion The suggested RR model provides an efficient alternative to both Warner ’s model and Mangat & Singh ’s model that allows more credibility from a practical perspective. Setting the values for the probabilities q1Cq2Cq3 to 0B4C0B4C0B5, respectively, seem to be a rational choice in t...
the findings of this study are available within the article. The rawBF02595813. L. Barabesi, M. Marcheselli, Bayesian estimation of proportion and sensitivity level in randomized response procedures, Metrika 72 (2010) 75–88, orgs00184-009-0242-7. Z. Hussain, J. Shabbir, M. Riaz, Bayesian estimation using Warner’s rando...
Heliyon 10 (2024) e36501Available online 18 August 20242405-8440/© 2024 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license( ).Research articlePricing weekly motor insurance drivers ’ with behavioral and contextual telematics dataMontserrat Guillena,b,*, Ana M. P˘erez-Ma...
rating factors to external parties. All in all, this has considerably slowed down research on measurable driving behavior and operating circumstances that explain a driver ’s proneness to cause a traffic accident, in spite of a massive amount of information that is known to have been recorded somewhere. Therefore, data...
and economically viable insurance framework for both the service providers and the transient drivers involved.Unlike previous existing contributions we are able to disclose predictors and examine the role of timely data collection. We therefore take full advantage of the fact that telematics data provide a continuous s...
how a multiplicative scheme derived from a Poisson model specification or an additive scheme resulting from a linear probability model specification may alter the existing usage-based insurance pricing in the current marketplace, primarily predicated on distance driven, irrespective of the manner and location of drivin...
scrutinize the impact of both distance driven and the duration of insurance contracts on claim frequency. Surprisingly, they discovered that neither distance nor contract duration exhibited a linear relationship with claim frequency. Adding to this, Guillen et al. incorporated yearly distance travelled as an offset wit...
and trips, leading to the proliferation of big data in the insurance industry. Paefgen et al. noted the complexity and data volume associated with usage-based insurance pricing, emphasizing its challenge in actuarial decision-making. They analyzed real raw location data, considering 15 predictor variables, and compared...
Gao and Wüthrich introduced speed and acceleration heatmaps, categorized using the K-means algorithm to differentiate varying driving styles. Gao et al. further explored telematics covariates extracted from car driving data, affirming their superior predictive power for claim frequencies compared to traditional pricing...
of insureds. This is a common limitation in actuarial research dealing with telematics data, specifically that the accident history does not match with telematics data collection period. Similarly, Moosavi and Ramnath investigated driver ’s styles and also used past-at fault traffic accidents and citations as risk indi...
not change over time, including a constant intercept.Generalized linear models specify a link of the linear predictor, hxkiCzjit), and the output Eyit). A statistical distribution in the exponential family for the response random variable yit is also specified. Parameter estimates of the linear predictor can easily be ...
from driving without speeding events, during weekdays, during the day and in non-urban areas.Several possibilities for static and dynamic scoring are presented in Table 1. Note that even if Table 1 only aims at modelling accident frequency, usage-based insurance schemes can follow directly from frequency models, once a...
1γ⌈⋃Jj1β2jzjit⋃Ll1β3lzlit1⌉Expected accident frequency is approximated (or bounded for pricing purposed) by a static part that depends on a combination of driver characteristics plus a linear combination of log-distance driven and same- and previous- period dynamic factorsM. Guillen et al. Heliyon 10 (2024) e365016...
Article Not peer-reviewed versionA Dual-Phase Framework for EnhancedChurn Prediction in Motor Insuranceusing Cave-Degree and Magnetic ForcePerturbation TechniquesEmmanuel Chai , Kennedy Hadullo , Kevin Tole * , Dorca Nyamusi StephenPosted Date: 24 September 2024doi: 10.20944/preprints202409.1820.v1Keywords: Churn Predi...
customers to confirmtheir intention to renew. However, by predicting which customers are likely to churn, insurancecompanies can focus their efforts on those most at risk, thus improving retention strategies. Churnprediction approaches can be broadly categorized into two strategies: constructive (local) approachesand g...
(SGD), Adam, and learningrate scheduling, which help accelerate convergence and improve performance. Adjustment ofhyperparameters, using methods such as grid search or random search, is crucial to optimize thepredictive accuracy of these models. The choice of algorithm and optimization techniques dependson the characte...
subsets, preventing the algorithm from getting trapped in local optima. To further refinethis process, a Magnetic Force Perturbation Technique (MFPT) is introduced. The Magnetic ForcePerturbation Technique (MFPT) is inspired by the interaction of magnetic fields, where forces eitherattract or repel solutions based on t...
a Magnetic Force Perturbation Technique that simulates magnetic forces to guide theoptimization process, thereby improving convergence and solution quality.The remainder of this paper is organized as follows. Section 2 introduces the formal formulationof the problem, while Section 3 provides a comprehensive overview of...
to address the problem at handthrough a structured framework consisting of two distinct phases: the initialization stage and theoptimization phase. The first phase, known as the initialization stage, focuses on feature selection. Thisstage is crucial to identify the most relevant features of the dataset that will contr...
the relevance of each feature based on itscontribution to reducing impurity at the nodes of the decision trees. Let Cirepresent the cave degreeof feature xi, which is computed by averaging the importance scores Importance (xi,t)across all treesin the Random Forest ensemble:Ci=1ntreesntrees∑t=1Importance (xi,t)The cave ...
(B) Combined DecisionBoundaries with Sigmoid Function and Inflection PointAs depicted in Algorithm 1, the feature selection process in a Random Forest is guided by thecave degree values. By assigning weights to features based on their normalized cave degrees,˜Ci=Ci∑pj=1Cj,where pis the total number of features, the Ran...
the "charges" or qualities of solutions xandyrespectively,and∥y−x∥is the Euclidean distance between the solutions. Solutions xclose to promising regions,which have higher quality (or "charge"), experience an attraction force pulling them towards thoseregions. In contrast, solutions in less favorable regions experience ...
9 of 22Figure 3. ALNS search trajectory within a solution space. This figure represents the search trajectory ofthe ALNS algorithm through the solution space. The blue lines with arrows indicate the path taken bythe algorithm in navigating from one solution to another. The red, blue, and green points correspondto diffe...
the social interaction of a swarm of particles in a search space to find optimalsolutions to complex problems. In PSO, each particle represents a potential solution and movesthrough the search space influenced by its own experience and that of its neighbors. Particles adjusttheir positions based on their own best-known...
Citation: Pouﬁnas, Thomas, PeriklisGogas, Theophilos Papadimitriou,and Emmanouil Zaganidis. 2023.Machine Learning in ForecastingMotor Insurance Claims. Risks 11:164. risks11090164Academic Editor: Shengkun XieReceived: 11 August 2023Revised: 11 September 2023Accepted: 13 September 2023Published: 18 September 2023Copyrig...
activity by which an individual or enterprise exchanges an uncertain(ﬁnancial) loss with a certain (ﬁnancial) loss. The former is the outcome of an event forwhich the insured individual or enterprise has received coverage via an insurance policy;the latter is the premium that the insured has to pay to receive this cove...
requires(one of) the biggest portions of capital (allocations). Indeed, insurers assume the risksthat individuals and enterprises want to transfer, hedge, or mitigate. A claim is ﬁledwhen a covered event (the assumed risk) has occurred. A higher risk appetite indicatesthe assumption of higher risk and thus higher claim...
identify similar applications of ML as they pave the futureof insurance. Risks 2023 ,11, 164 3 of 19In this paper, we employ a series of Machine Learning algorithms (Support VectorMachines–SVM, Decision Trees, Random Forests, and Boosting) to forecast the average(mean) insurance claims amount per insured car per quarte...
a wide range of topics relevant to theinsurance activity, there is ample room for further research. The main literature strands fo-cus on claims, reserving, pricing, capital requirements–solvency, coverage ratio, acquisition,and retention. We group them into two main categories; actuarial and risk management thatincorp...
claims (over the portfolioof Porto Seguro, a large Brazilian motor insurer). Selvakumar et al. (2021) concentrated onthe prediction of the third-party liability (motor insurance) claim amount for different typesof vehicles with ML models (on a dataset derived from Indian public insurance companies).Some recent articles...
implemented ML approaches in health management/insurance.Bauder et al. (2016) introduced ML approaches to tackle a different topic of insuranceclaims, thereby allowing them to spot the physicians that post a potentially anomalousbehavior (pointing out misuse, fraud, or ignorance of the billing procedures) in health Ris...
at the same time, increased the issueof interpretability. Henckaerts et al. (2021) capitalized on ML methods to price non-lifeinsurance products based on the frequency and severity of claims; their results are superiorto the ones produced by the traditionally employed generalized linear models (GLMs).Kuo and Lupton (20...
the variables in our dataset is constrainedby the availability of the data from the insurance company. Thus, we used a sample withquarterly frequency.Besides the claims data, our dataset consists of the number of new car sales, importedused car sales in the greater region of Athens, the weather conditions as described ...
station of ElefsataHNMS (2022)Max Temp Tatoit1Max Temp Tatoit2Max Temp Tatoit3Max Temp Tatoit4The maximum temperature recorded atthe weather station of TatoiHNMS (2022)Min Temp Tatoit1Min Temp Tatoit2Min Temp Tatoit3Min Temp Tatoit4The matimum temperature recorded atthe weather station of TatoiHNMS (2022)Mean Temp Tato...
some seasonality onpeaks and troughs, especially after 2012), which is most likely attributed to a signiﬁcantreduction in car activity during this period. This was the result of the Greek sovereign debtcrisis that started in 2010 and resulted in strict austerity measures that greatly negativelyimpacted household income...
a bit earlier, towards the end of the 3rd quarter, which is a small deviation from the seasonality observed. 4. Methodology Machine Learning was established in the 1950s to deliver the “Learning” component on the Artificial Intelligence (AI) systems. The basic concept of Machine Learning is the automated analytical mod...
Citation: Wilson, Alinta Ann, AntonioNehme, Alisha Dhyani, and KhaledMahbub. 2024. A Comparison ofGeneralised Linear Modelling withMachine Learning Approaches forPredicting Loss Cost in MotorInsurance. Risks 12: 62. https:doi.orgrisks12040062Academic Editor: Angelos DassiosReceived: 17 February 2024Revised: 27 March 20...
severity modelling; loss cost model1. IntroductionThe financial services industry, especially its most prominent and visiblemember—Insurance—is undergoing a rapid and disruptive change fueled by advancedtechnologies and changing consumer needs. The insurance sector is on the brink of adigital revolution, transforming t...
create large, similar, and different groupswithin and between classes Smith et al. (2000).Actuarial science is a discipline that analyses data, assesses risks, and calculates proba-ble loss costs for insurance policies using a range of mathematical models and methodsDhaene et al. (2002). Actuaries consider information ...
inefficiency for updating the GLM models in light of new data, as commonpractices followed by actuaries require manual steps in the fine-tuning of the weightsof each factor.• The dependence of GLM on assumptions on the distribution of the data, which arenot always valid for datasets representing an unusual market, for ...
and the location of residency.Garrido et al. (2016) used generalised linear models to calculate the premium bymultiplying the mean severity, mean frequency, and a correction term intended to inducedependency between these components on a Canadian automobile insurance dataset. Thismethod assumes a linear relationship be...
than that obtained from the GLMmodel. Poufinas et al. (2023) also suggested that tree-based models performed better thanalternative learning techniques; their dataset, however, was limited to 48 instances andtheir results were not compared to GLM Poufinas et al. (2023).Also, in the existing literature, multiple papers ...
there are multiple works in the literature that support the Gradient Boost Machines(GBM) model since it ensures model interpretability through its feature selection capabilities.The literature review also highlights the importance of the neural network approach, as itshows better and more reliable results than traditio...
CASdatasets were found for claim frequencymodelling and claim severity modelling Dutang and Charpentier (2020). These datasetscontain the risk characteristics gathered over one year for 677,991 motor vehicle third-partyliability insurance policies. While freMTPL2freq comprises the risk characteristics and theclaim numb...
merging the datasets are changed to zero, where the leftjoin of the frequency and severity datasets resulted in records with 0 claims having noequivalent severity records (leading to NA values).• Duplicate rows (exact duplicates) have been removed, as those were deemed to bedata entry errors.• The dataset was filtered ...
weremade within one accounting year; hence, these exposures above 1 may have been the resultof a data error and were corrected to 1.The distribution of the feature variable ‘Exposure’ before and after the cap is depictedin Figures 1 and 2.Figure 1. Histogram showing the distribution of feature ‘Exposure’ before capping...
We cappedBonusMalus at 150 covering 99.96% of the data, thus ensuring that both the Bonus (valuesless than 100) and Malus (values over 100) are captured when building the models. Figure 10shows the distribution of the BonusMalus values with respect to the frequency and numberof claims after capping.Figure 9. Barplot sh...
due to factors such as driver adjusting to the vehicle and itsnovelty.Figure 14. Relationship between vehicle age and the number of claims.Figure 15 depicts the relationship between vehicle power and the number of claims,and it can be inferred that vehicles with powers 5, 6, and 7 have a greater number of claims.Figure...
IOP Conference Series: MaterialsScience and Engineering PAPER • OPEN ACCESSModel estimation of claim risk and premium formotor vehicle insurance by using BayesianmethodTo cite this article: Sukono et al 2018 IOP Conf. Ser.: Mater. Sci. Eng. 300 012027 View the article online for updates and enhancements. You may also l...
values p is 7.922 and  is 1.414. Therefore, the obtained values of the mean and variance of the aggregate claims respectively are IDR 32,667,489.88 and IDR 38,453,900,000,000.00. In this paper the prediction of the pure premium eligible charged to the insured is obtained, which amounting to IDR 2,722,290.82. The predi...
approach. Meanwhile, Eliasson applied the Bayesian method for the estimation of the credibility parameters for non-life insurance pricing on historical data of individual claims. In the analysis of non-life insurance, the risk distribution model of loss is an important concern for insurance companies. The risk distribu...
done by using Bayesian method. According to Boldstad and Gill , the Bayesian method is one of the parameter estimation methods that uses preliminary information on parameters , or so-called as the prior distribution, and information from the observed data that has been obtained. After the sample information is taken, ...
data of claim amount which follows Gamma distribution is expressed by: ni ixnipinpni e xpp x l111) () , \| (  . According to Ntzoufras , amount of claims which is Gamma distributed has a prior conjugate that Gamma distributed with a hyperparameter  and. The probability density function is expresse...
of claims data is presented in Table 1. Tabel 1. Data of claim amount and frequency of claim No Interval Frequency 1 1,978,435 - 3,121,754 6 2 3,121,755 - 4,265,074 13 3 4,265,075 - 5,408,393 20 4 5,408,395 - 6,551,712 12 5 6,551,713 - 7,695,031 8 6 7,695,031 - 8,838,351 4 7 8,838,352 - 9,981,670 7 Total 392,307,367 70...
Variance Standard Deviation  70.001 12.001 5.832931 0.486037 0.697163 The OpenBUGS program is used to obtain a statistical summary of parameters , by simulating the sample data from the posterior distribution in several iterations. In this study, the three chains are used to simulate the posterior distribution of sam...
parameter  which is obtained manually Parameter Posterior  Posterior  Mean Variance Amount of Claim  554.513 392,307,367.001 1.41 10-6 3.6010-15 5,604,380.85 The posterior distribution explains the confidence level of the parameters contained in the sample data. Statistical summary of posterior parameter  show...
000 , 452 , 320 ) ( t p .  By using equation (8), the obtained calculation of standard deviation premium principles is: 783 . 301 , 901 , 2 ) ( t p . 4. Conclusions In this paper, we discussed the estimation of claims risk model and motor vehicle insurance premiums by using Bayesian methods approach. Based on the da...
Working Paper Postal address: Mathematical Statistics Stockholm University, SE-106 91, Sweden. E-mail: daniel@danieleliasson.com. Gamerman, et al. 2006 Markov Chain Monte Carlo: Stochastic Simulation for Bayesian Inference (2nd ed) London : Chapman & HallCRC) Inanoglu H and Jacobs H 2009 Models for Risk Aggregation and...
An examination of the relationship between vehicle insurance purchase and thefrequency of accidentsYung-Ching Hsua, Pai-Lung Choub, Yung-Ming Shiuc,*aInvestigation Section, Civil Service Ethics Of ﬁce, Kaohsiung City Government, 2, Sihwei 3rd Road, Lingya District, Kaohsiung, Taiwan, ROCbDepartment of Risk Management a...
total number of RTA fatal-ities across the world currently stands at 1.24 million per year(WHO, 2014 ). As a result, governments across the world have beenplacing considerable effort into enhancing road safety by imposingrelevant laws and investing in highway capital ( Nguyen-Hoang &Yeung, 2014 ), whilst vehicle manufa...
will tend to have a higher prob-ability of experiencing a loss. Riskier drivers will therefore tend tobuy higher coverage and will also tend to submit more claims. Thisinference gives rise to a positive correlation between the amount ofinsurance coverage and the ex post occurrence of the insured risk.Such a positive re...
and claims can therefore be observed. Conversely, thelatter argues that risk-averse drivers tend to purchase more insur-ance. Because these drivers are less likely to be involved in RTAs, anegative relation is thus observed.Like adverse selection theory, moral hazard theory also predictsa positive relation between cove...
pur-chase behavior may in ﬂuence the probability of RTAs from theperspective of traf ﬁc safety; the present study therefore aims to ﬁllthis gap in the literature. The prior insurance literature also sug-gests that there are other factors, such as risk aversion, that maywell offset the positive correlation between cover...
the relation between in-surance purchase and incidences of traf ﬁc accidents. It is thereforeobvious that data on compulsory insurance cannot be used toexamine this relation. Since all drivers in Taiwan need to purchasecompulsory vehicle liability insurance, using voluntary vehicle li-ability is also inappropriate and ...
equal to 1 if policyholderisubmits one or more claims; otherwise 0; and Coverage irefers tothe coverage choice of policyholder i; this variable is a dichotomousvariable which is equal to 1 for high coverage and 0 for lowcoverage; CViis a set of control variables (to be de ﬁned below); eiisa classic error term. We assum...
are presented in Table 2 . It is worth-while to note that these variables are observable to the insurer andused in pricing insurance policies.As stated above, a positive relation between coverage and claimscould indicate the existence of adverse selection or moral hazard.One approach for effectively distinguishing betw...
negative. Wealso anticipate that the positive relationship posited by adverseselection theory will again be weakened, or indeed, become anegative relationship, for older insured drivers and female drivers.We further predict that the age of the insured vehicle may wellprove to moderate the relationship between vehicle d...
on the use of theHeckman two-step estimation approach can be found in Johnstonand DiNardo (1997) .Empirical resultsUnivariate analysisThe summary statistics of all of the variables used in the presentstudy are reported in Table 3 . As the table shows, of our total sampleof insured drivers, approximately 28 per cent wer...
2010 ).In order to examine the moderating effects of the Insured_Age,Gender and Vehicle_Age variables on the relationship betweenCoverage and Claim , interaction terms are subsequently added intoour regressions. The adverse effects potentially arising from theproblem of multi-collinearity are alleviated by mean centeri...
India to overtake Japan as Asia's 2nd largest economy by 2030: IHS India is likely to overtake Japan as Asia's second-largest economy by 2030 when its is also projected to surpass that of Germany and the UK to rank as world's No.3, IHS Markit said in a report on Friday. Currently, India is the sixth-largest economy in ...
said, is being boosted by large inflows of investments from global technology MNCs such as Google and Facebook that are attracted to India's large domestic consumer market. Being one of the world's fastest-growing economies will make India one of the most important long-term growth markets for multinationals in a wide ...
Union Budget 2022 highlights: Boost for various sectors, but middle class taxpayers left in lurch again Finance minister presented the , the fourth budget of Modi 2.0, today. There were a host of measures for a number of sectors, aimed at boosting growth amid high & rising inflation and continuing Covid uncertainties. ...
Merdeka Battery soars 20% on debut as Indonesia's EV push draws investors Indonesian nickel company Materials surged as much as 20% in its trading debut on Tuesday after raising 8.75 trillion rupiah (USD 591.82 million) in the country's third largest initial public offering this year. The strong debut, coming less than...
Eikon data showed, from USD 202 million in the year-earlier period. Other upcoming IPOs in Indonesia this year include Pertamina Hulu Energi, the upstream arm of Pertamina, that could raise up to USD 2 billion, and state-owned fertiliser company Pupuk Kalimantan Timur that could raise USD 500 million.
FPIs sold $14 bln equities in Q1 2022, DIIs bought matching amount: Report New Delhi: (FPIs) have sold around $14 billion worth of equities in the secondary market in the quarter that ended in March 2022, said Kotak Securities in a report. FPIs offloaded stocks in banks, diversified financials and IT services. On the f...
Indian fintech firms will handle $1 trillion in assets by 2030: report Funding in Indian touched $7.8 billion in 2021 and the industry is expected to handle $1 trillion worth assets by 2030, according to a new report by venture capital firm and . Indian fintech firms are expected to clock $200 billion in revenue by 203...
White-collar job openings stay above pre-Covid levels in April The market in India is on a sustained recovery path, as a pickup in business activity and rising attrition levels are prompting companies to ramp up hiring, leading to the number of white-collar job positions in April exceeding the average pre-pandemic mont...
Ford extends production at TN plant till July-end Auto major Ford has extended its production schedule till July-end against the earlier June-end as the company is continuing discussions with the employees who are protesting against the severance package offered to them, the company said on Friday. The factory located ...
Over 2,250 startups added in 2021, raised USD 24.1 bn in 2021: Report NEW DELHI: More than 2,250 were added in the year 2021, over 600 more than what was added in the previous year, a report by Nasscom and Zinnov said on Friday. The study titled 'Indian Tech Start-up Ecosystem: Year of The Titans' said with rising inve...

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