Modeling of Motor Insurance Extreme Claims through Appropriate Statistical Distributions

In the area of insurance, probability modeling has a wide variety of applications. In life insurance, the compensation sum is calculated in advance and may often be estimated using actuarial techniques, while in motor insurance, the claim amount is generally not known in advance. In the insurance business, the improvement of actuarial risk control strategies is an essential technique for controlling insurance risk. Although an insurance company’s risk assessment about its solvency is a complex and detailed problem, its solution begins with statistical modeling of individual claims’ amounts. This article emphasizes the possible ways of obtaining a suitable probability distribution model that accurately explains insurance risks and how to use such a model for risk management purposes. For this reason, we have applied modern programming techniques and statistical software implemented the methods provided based on data on premium amounts of third-party motor insurance claims.

The Trouble with Using Risk Assessment Instruments to Quantify the Chance of Future Offending

Risk assessments in carceral settings have proliferated in recent decades and are now prominent in numerous states and regions. A ubiquitous variety is actuarial risk assessment instruments that are used on children and adults to predict their future chance for misconduct (e.g., recidivism) in several vital decision points in carceral processing (e.g., pretrial confinement). These instruments rely on information about past behavior (e.g., criminal history) and an understanding of offending (e.g., antisocial personality) that is thought to be neutral, reliable, and enjoys predictive validity. However, it will be argued that when justice system personnel assess the chance of unwanted behavior in the future, several risk domains are differentially prevalent and more frequently experienced by some groups. Much of this disparity is caused by, or due to, forces external to those being assessed, for instance, inequitable social and economic conditions and inequitable decisions by justice personnel to arrest, charge, or sentence people of color. As such, risk assessment instruments inevitably and disproportionately mark some groups of people as a higher risk to violate rules, conditions, orders, or laws. Consequently, risk assessment instruments systematically disfavor disadvantage, and by inference, favor advantage, leading to the need for a radical shift in the taxonomy of classifying risk for future misconduct.

Application of the Risk Principle in the Supervision and Treatment of Individuals Who Have Sexually Offended: Does “Oversupervision” Matter?

Individuals who sexually offend are commonly misunderstood as being high risk. According to the risk–need–responsivity (RNR) principles, treatment and supervision levels should be determined by actuarial risk for the best outcomes. To date, no studies have examined these principles with individuals on supervision for a sexual offense. This study applies the RNR principles to a sample of 133 men and women serving probated sentences for a sexual offense and mandated to specialized treatment. Results indicate low-risk individuals convicted of a sexual offense were more likely to be compliant with probation and treatment than moderate-risk individuals. An analysis of risk level and supervision overrides ( N = 75) provides support for the prediction that low-risk individuals supervised at high levels may be more likely to have compliance problems. Results suggest similar outcomes when violating the risk principle for individuals who have sexually offended to the findings among general justice-involved people.

Parole Officer Decision-Making Before Parole Revocation: Why Context Is Key When Delivering Correctional Services

Back-end sentencing is the discretionary, administrative process through which individuals on parole are returned to prison for violating the requirements of their supervised release. Parole officers play a crucial role in this process as they are the witnesses to the rule-breaking behaviors of people on parole supervision and ultimately must initiate the back-end sentencing process. This study explores predictors of parole officer decision-making when determining whether to consider a person for revocation or to gear programmatic community-based resources toward them in an attempt to decrease the likelihood of their eventual revocation. Our results indicate that if people released to parole are front-loaded programmatic resources as a part of their release conditions from prison, the odds that parole officers subsequently gear community-based programs toward them decreases by approximately 60%. Other factors such as demographics, actuarial risk levels, and criminal history were not significantly predictive of officer decision-making in this context.

What Works (or Does Not) in Community Risk Management for Persons Convicted of Sexual Offenses? A Contemporary Perspective

Contemporary data from the United States show that rates of sexual offending and reoffending have been in steady decline for decades. Nonetheless, nonprofessionals continue to view sexual violence as a community safety issue fraught with risk and uncertainty. The past 30 years have been witness to considerable research and practice in the assessment, treatment, and risk management of persons who have sexually offended. Gains have also been made in regard to prevention and citizen education. Modern day technologies include actuarial risk assessment instruments, measures of criminogenic need and treatment progress, refinements to treatment processes, and the establishment of evidence-based models. Legislative authorities in the United States and elsewhere have also attempted to affect risk in the community with, perhaps, lesser degrees of success. This article reviews current policies and practices, with a specific focus on what happens when offenders are released to the community (e.g., how public policies intended to track offenders and/or restrict their movements can negatively affect community reintegration). Comprehensive approaches to community sexual offender management are examined in addition to suggestions of unique approaches intended to ensure citizen buy-in and engagement.

Law-abiding versus criminal identity and self-efficacy: A quantitative approach to unravel psychological factors supporting desistance from crime

Previous studies suggest that the process of desistance from crime is accompanied by a shift from criminal to law-abiding identity and self-efficacy. Against this background and to explain variance in recidivism, we developed direct and indirect measures of law-abiding and criminal identity as well as a direct measure of self-efficacy for law-abiding and criminal behavior. We predicted that 1) a stronger law-abiding identity relative to criminal identity as well as 2) a stronger self-efficacy for law-abiding and a weaker self-efficacy for criminal behavior will correlate with a lower risk to reoffend and will prospectively explain variance in recidivism. We applied the developed measures in a sample of 325 offenders on probation and tested cross-sectional associations with actuarial risk factors at T1. Two to three years later, we tested whether identity and self-efficacy measured at T1 explained variance in recidivism at T2, controlling for actuarial risk factors. Results showed that a stronger law-abiding identity relative to criminal identity as well as a stronger self-efficacy for law-abiding and a weaker self-efficacy for criminal behavior correlated with a lower risk to reoffend (T1). In addition, law-abiding relative to criminal identity prospectively explained variance in recidivism over and beyond actuarial risk factors (T2). The results indicate that the strength of law-abiding identity relative to criminal identity plays a role in persisting in or desisting from criminal behavior. Yet, further research is necessary to identify the causal psychological mechanisms of identity change in the process towards desistance from crime.

Estimating the probability of sexual recidivism among men charged or convicted of sexual offences: Evidence-based guidance for applied evaluators

Risk assessment is routinely applied in forensic decision-making. Although relative risk information from risk scales is robust across diverse samples and settings, estimates of the absolute probability of sexual recidivism are not. Nonetheless, absolute recidivism estimates are still necessary in some evaluations. This paper summarizes research and offers guidance on evidence-based practices for assessing the probability of recidivism, organized largely around questions commonly asked in court. Overall, estimating the probability of sexual recidivism is difficult and should be undertaken with humility and circumspection. That being said, research favours empirical-actuarial risk tools for this task, more structured scales, and the use of multiple scales. Professional overrides of risk scale results should not be used under any circumstances. Paradoxically, however, professional judgement is still required in some circumstances. Risk scales do not consider all relevant risk factors, but the added value of external risk factors reaches a point of diminishing returns and may or may not be incremental (or worse, can degrade accuracy). There are reasons actuarial risk scales may both underestimate recidivism (e.g., undetected offending, short follow-ups) and overestimate recidivism (e.g., inclusion of sex offences not of interest in some referral questions, data on declining crime and recidivism rates, newer studies demonstrating overestimation of recidivism). Given all these considerations and the need for humility, in the absence of exceptional circumstances, I would not deviate too far from empirical estimates.

Evidence-Based Sentencing

The evidence-based practice (EBP) movement can be traced to a 1992 article in the Journal of the American Medical Association, although decision-making with empirical evidence (rather than tradition, anecdote, or intuition) is obviously much older. Neverthless, for the last twenty-five years, EBP has played a pivotal role in criminal justice, particularly within community corrections. While the prediction of recidivism in parole or probation decisions has attracted relatively little attention, the use of risk measures by sentencing judges is controversial. This might be because sentencing typically involves both backward-looking decisions, related to the blameworthiness of the crime, as well as forward-looking decisions, about the offender’s prospective risk of recidivism. Evidence-based sentencing quantifies the predictive aspects of decision-making by incorporating an assessment of risk factors (which increase recidivism risk), protective factors (which reduce recidivism risk), criminogenic needs (impairments that, if addressed, will reduce recidivism risk), the measurement of recidivism risk, and the identification of optimal recidivism-reducing sentencing interventions. Proponents for evidence-based sentencing claim that it can allow judges to “sentence smarter” by using data to distinguish high-risk offenders (who might be imprisoned to mitigate their recidivism risk) from low-risk offenders (who might be released into the community with relatively little danger). This, proponents suggest, can reduce unnecessary incarceration, decrease costs, and enhance community safety. Critics, however, note that risk assessment typically looks beyond criminal conduct, incorporating demographic and socioeconomic variables. Even if a risk factor is facially neutral (e.g., criminal history), it might operate as a proxy for a constitutionally protected category (e.g., race). The same objectionable variables are used widely in presentence reports, but their incorporation into an actuarial risk score has greater potential to obfuscate facts and reify underlying disparities. The evidence-based sentencing literature is dynamic and rapidly evolving, but this bibliography identifies sources that might prove useful. It first outlines the theoretical foundations of traditional (non-evidence-based) sentencing, identifying resources and overviews. It then identifies sources related to decision-making and prediction, risk assessment logic, criminogenic needs, and responsivity. The bibliography then describes and defends evidence-based sentencing, and identifies works on sentencing variables and risk assessment instruments. It then relates evidence-based sentencing to big data and identifies data issues. Several works on constitutional problems are listed, the proxies problem is described, and sources on philosophical issues are described. The bibliography concludes with a description of validation research, the politics of evidence-based sentencing, and the identification of several current initiatives.