But in a court filing Monday, Jonathan Marks, the deputy elections secretary, acknowledged that a fourth county, Butler, had also refused to count those ballots — and that the county had notified the department three weeks before the lawsuit was filed.
Marks apologized to the court for what he described as an oversight resulting from “a manual process” — a spreadsheet — the department had used to track which counties were counting undated ballots. Butler County was misclassified in the spreadsheet, he said, and from that point forward was left out of the state’s campaign to push counties that hadn’t included them.
The Department of Justice has dropped its investigation into the Pennsylvania Public School Employees’ Retirement System, said Chris Santa Maria, chairman of the $75.9 billion pension fund’s board of trustees, in a statement. PSERS made no further comment on the matter.
The pension fund had been under investigation by the Justice Department since at least May of last year, when subpoenas indicated that the FBI and prosecutors were seeking evidence of kickbacks and bribes at PSERS.
The subpoenas were reportedly looking for information from the pension fund, its executive director, chief financial officer, chief auditing officer and deputy CIO. The court orders reportedly showed that the FBI and prosecutors were probing possible “honest services fraud” and wire fraud.
According to a report released earlier this year following an internal investigation, PSERS investment consultant Aon took responsibility for the accounting error. The report includes a letter from Aon to Grossman that said the firm had become aware of data corruption in some sub-composite market values, cashflows and returns for April 2015.
Aon attributed the data corruption to an error by an analyst in uploading net asset value and cashflow data into the performance system it uses. The company said the data corruption impacted “a few asset class composites” in the public markets.
In the PBRAR, VM-31 3.D.2.e.(iv) requires the actuary to discuss “which risks, if any, are not included in the model” and 3.D.2.e.(v) requires a discussion of “any limitations of the model that could materially impact the NPR [net premium reserve], DR [deterministic reserve] or SR [stochastic reserve].” ASOP No. 56 Section 3.2 states that, when expressing an opinion on or communicating results of the model, the actuary should understand: (a) important aspects of the model being used, including its basic operations, dependencies, and sensitivities; (b) known weaknesses in assumptions used as input and known weaknesses in methods or other known limitations of the model that have material implications; and (c) limitations of data or information, time constraints, or other practical considerations that could materially impact the model’s ability to meet its intended purpose.
Together, both VM-31 and ASOP No. 56 require the actuary (i.e., any actuary working with or responsible for the model and its output) to not only know and understand but communicate these limitations to stakeholders. An example of this may be reinsurance modeling. A common technique in modeling the many treaties of yearly renewable term (YRT) reinsurance of a given cohort of policies is to use a simplification, where YRT premium rates are blended according to a weighted average of net amounts at risk. That is to say, the treaties are not modeled seriatim but as an aggregate or blended treaty applicable to amounts in excess of retention. This approach assumes each third-party reinsurer is as solvent as the next. The actuary must ask, “Is there a risk that is ignored by the model because of the approach to modeling YRT reinsurance?” and “Does this simplification present a limitation that could materially impact the net premium reserve, deterministic reserve or stochastic reserve?”
Understanding limitations of a model requires understanding the end-to-end process that moves from data and assumptions to results and analysis. The extract-transform-load (ETL) process actually fits well with the ASOP No. 56 definition of a model, which is: “A model consists of three components: an information input component, which delivers data and assumptions to the model; a processing component, which transforms input into output; and a results component, which translates the output into useful business information.” Many actuaries work with models on a daily basis, yet it helps to revisit this important definition. Many would not recognize the routine step of accessing the policy level data necessary to create an in-force file as part of the model itself. The actuary should ask, “Are there risks introduced by the frontend or backend processing in the ETL routine?” and “What mitigations has the company established over time to address these risks?”
This is the common response when people learn about the US Navy’s Fat Leonard scandal. The high stakes drama and salacious details do seem made for the silver screen, but what’s more surprising is how many people — among them Hill staff, Pentagon budget experts, and other defense policy participants — are unaware of the crimes that proliferated up and down the ranks of the 7th Fleet less than a decade ago. That military leaders, Congress, and the public seem to have forgotten this affair that took down rising leaders, defrauded the US government, and undermined our national security is at least as troubling as the events themselves.
Here’s the short version of events:
The US Navy contracted with Glenn Marine Group (GMG), a ship husbanding company that assisted the Navy with port security, repairs, fueling, restocking and other dockside needs. The president of GMG, Francis Leonard (aka Fat Leonard), overbilled the Navy for things like fresh water and redirected carrier movements to ports where he could charge the most. He bribed officers with $18,000 meals and extravagant hotel stays, prostitutes, parties, cash, and luxury goods. He gained access to sensitive information and paid off people in roles who could help avoid investigations into his activities. Only after the US Department of Justice stepped in — to investigate a suspected mole within the Naval Criminal Investigative Service (NCIS) who was tipping off Leonard — did the enterprise start to unravel.
In 2013, federal agents arrested Leonard in San Diego and charged another 33 people with various crimes, though Leonard’s activities cast a much wider net. In 2018, the Washington Post reported that: “According to the Navy, an additional 550 active-duty and retired military personnel — including about 60 admirals — have come under scrutiny for possible violations of military law or ethics rules.”
The SEC’s complaint, filed in the federal district court in Manhattan, alleges that Structured Alpha’s Lead Portfolio Manager, Gregoire P. Tournant, orchestrated the multi-year scheme to mislead investors who invested approximately $11 billion in Structured Alpha, and paid the defendants over $550 million in fees. It further alleges that, with assistance from Co-Lead Portfolio Manager, Trevor L. Taylor, and Portfolio Manager, Stephen G. Bond-Nelson, Tournant manipulated numerous financial reports and other information provided to investors to conceal the magnitude of Structured Alpha’s true risk and the funds’ actual performance.
Defendants reduced losses under a market crash scenario in one risk report sent to investors from negative 42.1505489755747% to negative 4.1505489755747% — by simply dropping the single digit 2. In another example, defendants “smoothed” performance data sent to investors by reducing losses on one day from negative 18.2607085709004% to negative 9.2607085709004% — this time by cutting the number 18 in half.
The star portfolio manager at the centre of a fraud at the U.S. funds unit of Allianz SE (ALVG.DE) relied on the German insurer’s good name to lure investors and thrived from a lack of oversight as he pocketed $60 million in pay, U.S. authorities said.
Gregoire “Greg” Tournant, a citizen of France and the United States, was indicted on Tuesday for securities fraud, investment adviser fraud, wire fraud and obstruction of justice in a scheme that ran from 2014 to 2020. read more
It was a major development in a two-year saga that has haunted and embarrassed Allianz, one of the globe’s biggest financial firms, and began after the $11 billion in funds managed by Tournant collapsed as markets roiled with the outbreak of the coronavirus in early 2020.
U.S. prosecutors on Tuesday said Tournant faked documents, fabricated risk reports, altered spreadsheets, and lied about the investment strategy.
Author(s): Tom Sims, Alexander Hübner and John O’Donnell
This year we had record participation with over 250 insurance professionals taking part. This is the fifth iteration of this poll and 2022 shows some consistency along with some very new risks. Inflation, Employee retention and Ability to hire new employees are three new risks to the top of this poll, but they should not be surprises.
2. INFLATION Up very sharply – Previously #52 Prices are rising faster than they have since the 1980s in most of the developed world. Insurers will be hit with a double whammy as the real value of invested assets decays and the cost of doing business and claims costs increases at the same time.
EMPLOYEE RETENTION Not on the list previously The Great Resignation makes the headlines. COVID seems to have accelerated the timeline for the inevitable wave of Boomer retirements. Also concerning are the numbers leaving due to health care burnout and caregiver responsibilities. The problem for insurers is figuring out how to respond to the massive loss of experience.
In its 2021 EMEA-wide Life Financial Modelling Survey, WTW reveals that many life insurers are under significant pressure from regulators and management to improve their financial reporting, exacerbated by key barriers to adopting cloud technologies capable of transforming their modelling capabilities.
While participating firms said they were satisfied with their current financial modelling, the demand for ever increasing and faster reporting is causing concern for many insurers, with this pressure being most evident for multinationals. Firms taking part in the survey highlighted three barriers in particular that they will first need to overcome in order to meet this demand for improved speed and efficiency: • Managing costs – Companies are under constant pressure to improve operational efficiency and meet the demand for real time services, but at ever decreasing costs. • Shortage of skilled resources – Having the right skill set and software is essential said survey respondents, particularly compared to the situation for companies still using old, obscure, or bespoke toolsets. • Improve governance and auditability – The challenge of updating financial modelling practices that not only deliver faster but are also capable of delivering a greater level of control and auditability. More than 90% of survey respondents recognised that the application of automation technology – including business process automation, elastic cloud computing and Software as a Service (SaaS) – is a key priority to address these challenges. At the same time, a number of participating firms were cautious of the changes needed to implement new technology, naming transition cost, data and IT policies, and technical challenges as the main barriers to adoption.
The hack into the client database of the private Vastamo psychotherapy center was first exposed on October 21, 2020, when the patient data of tens of thousands of people was stolen and used to blackmail both l company and patients.
Investigators asked each victim to file a criminal complaint, and as of February 2021, more than 25,000 such reports had been submitted. The majority of complaints were lodged at the Pasila police station in Helsinki, but others were lodged elsewhere in the country.
Instead of a database, criminal reports were saved via Microsoft Excel files. Some of the files turned out to be unreadable when the police attempted to transfer them into the official system. The cause of the problem is unknown.
Detective Inspector Jari Illukka from the Helsinki Police Department told Svenska Yle that a dozen crime reports had disappeared from Excel, but the exact number is not known.
Police estimate that the records of more than 30,000 people were stolen during the Vastaamo data breach, and more than 22,000 of those victims have since reported the crime.
However, a little more than three thousand declaration forms had been given to the police at the end of January, that is to say one victim in ten.
At least 20 older climate models disagreed with the new one at NCAR, an open-source model called the Community Earth System Model 2, or CESM2, funded mainly by the U.S. National Science Foundation and arguably the world’s most influential. Then, one by one, a dozen climate-modeling groups around the world produced similar forecasts.
The scientists soon concluded their new calculations had been thrown off kilter by the physics of clouds in a warming world, which may amplify or damp climate change. “The old way is just wrong, we know that,” said Andrew Gettelman, a physicist at NCAR who specializes in clouds and helped develop the CESM2 model. “I think our higher sensitivity is wrong too. It’s probably a consequence of other things we did by making clouds better and more realistic. You solve one problem and create another.”
Since then the CESM2 scientists have been reworking their algorithms using a deluge of new information about the effects of rising temperatures to better understand the physics at work. They have abandoned their most extreme calculations of climate sensitivity, but their more recent projections of future global warming are still dire — and still in flux.
Skeptics have scoffed at climate models for decades, saying they overstate hazards. But a growing body of research shows many climate models have been uncannily accurate. For one recent study, scientists at NASA, the Breakthrough Institute in Berkeley, Calif., and the Massachusetts Institute of Technology evaluated 17 models used between 1970 and 2007 and found most predicted climate shifts were “indistinguishable from what actually occurred.”
Still, models remain prone to technical glitches and are hampered by an incomplete understanding of the variables that control how our planet responds to heat-trapping gases.
The percentage of U.S. insurers that reported outsourcing investment management to an unaffiliated firm has remained relatively unchanged at year-end 2020, compared to the last several years; it was about half of all U.S. insurers, dating back to at least 2016. Consistent with prior years, small insurers, or those with less than $250 million in assets under management (AUM), accounted for the largest percentage, or 63% of the total number of U.S. insurers, that outsourced investment management. Property/casualty (P/C) companies continue to account for almost 60% of the total number of U.S. insurers that outsource to unaffiliated investment managers. For U.S. insurers that named the unaffiliated investment management firms that they utilize, BlackRock, Conning, and New England Asset Management Inc. (NEAM) have been the top three most-named investment managers over the last few years.
Author(s): Jennifer Johnson and Jean-Baptiste Carelus
Publication Date: 18 Jan 2022
Publication Site: NAIC Capital Markets Special Bureau
Texas, Indiana, Washington State and the District of Columbia sued Alphabet Inc.’s Google on Monday over what they called deceptive location-tracking practices that invade users’ privacy.
“Google falsely led consumers to believe that changing their account and device settings would allow customers to protect their privacy and control what personal data the company could access,” Washington, D.C., Attorney General Karl Racine’s office said in a statement.
Yet Google “continues to systematically surveil customers and profit from customer data,” the statement said, calling the practice “a clear violation of consumers’ privacy.”