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[ad_1] Russia warns of nuclear deployment if Sweden and Finland join NATO [ad_2] Source link

[ad_1] Ambedkar Jayanti Celebrations Live Streaming: Leaders across party lines, including Prime Minister Narendra Modi and Congress leader Rahul Gandhi, today paid tributes to Dr Bhimrao Ambedkar on his 131st birth anniversary. Babsaheb an Indian jurist, politician, philosopher, anthropologist, historian, and economist who was a key architect of the Indian Constitution. Dr Ambedkar acquired legal degrees and doctorates for his studies in law, economics, and political science, earning a reputation as a scholar and pushing for political and social freedom for Dalits. Born on April 14th, 1891, Dr Ambedkar campaigned against the Indian caste system. He converted to Buddhism and is credited with sparking a wave of conversions that saw tens of thousands of people from the lower castes follow his footsteps. [ad_2] Source link

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[ad_1] Benettons, Blackstone offer 23 euros a share in Atlantia bid [ad_2] Source link

[ad_1] Flat 30% tax on any income from transfer of crypto and other virtual digital assets (VDAs), including metaverse tokens and NFTs, has become effective from April 1, 2022. The new tax rule and the proposed 1% TDS on transfer of VDAs from July 1st have taken the shine away from the lucrative crypto markets in India. The effects of these tax announcements could be seen in dropping trade volumes at major crypto exchanges in India.  However, crypto, metaverse and NFTs are expected to drive the world into a new era of technology, also popularly referred to as Web3. In such a case, does it makes sense to invest in metaverse and NFTs now, while knowing any income from them would be taxed at the rate of 30%?  ALSO READ | Can you avoid 30% crypto tax by buying tokens on a foreign exchange? Experts suggest that one should invest in a virtual asset only if they believe it holds value.  “For those who believe that crypto-assets hold value, it makes sense to trade in them notwithstanding the 30% crypto-tax, since they will be liable to pay this tax only if they make a profit from out of their crypto-trades,” Vinod Joseph, Partner at Argus Partners law firm, told FE Online.  However, VDAs are extremely volatile, uncertain and unregulated. Hence, traditional instruments like mutual funds may hold more significance for investors looking at some sort of surity.  ALSO READ | How not to be a crypto fool: 5-point guide L “For most retail investors looking for long term and predictable gains, mutual funds  or index funds still remain the best option. The crypto frenzy brings with it a lot of short term speculators and a flurry of pump-and-dump issues that can hurt retail investors who unreasonably expect an endless upward rally in crypto,” said Utkarsh Sinha, managing director at Bexley advisors. How will 30% tax on VDAs work? The 30% tax applies to income received from the transfer of virtual digital assets or cryptocurrencies. For this tax to apply, the assessee should have made a profit from the  transfer of VDAs.  “A seller would not have to pay this tax if the sale is at a loss, that is, at a price lower than the original purchase price. Since the highest tax rate in India is 30%, this tax is not such a big deal,” said Vinod Joseph.  “The only hitch is that, even if a person’s net income is not taxable at 30%, if the assessee has made a profit through the trade of crypto assets, such profit is taxable. Assessees cannot set off the profit from trading cryto-assets against other income streams. It does not matter if the crypto assets are sold through an overseas exchange. As long as the assessee is an Indian resident , this tax will apply,” he added.  (Cryptos and other virtual digital assets are unregulated assets in India. Investing in them could lead to losses. Please consult a professional financial advisor before making any investment decision in crypto) [ad_2] Source link

[ad_1] Despite advances in technology, the mortgage industry still lacks efficiency Mortgage executives are aware of a problem: despite billions of dollars in technology investments, the mortgage industry still largely looks like it did two decades ago. After all, it still takes 43 days, on average, to close a loan.  “Realistically, it’s still basically the same industry,” Brian Woodring, chief information officer at Rocket Mortgage, said on Tuesday during the Mortgage Bankers Association’s Technology Solutions Conference & Expo in Las Vegas.  He added: “We have a tremendous amount of proprietary technology being built. We have organizations [working] to create some standardization. But it’s a challenge. This is an industry where most significant lenders are still building a decent amount of their technology footprint.”  Rocket, the top lender in the country with $351 billion originated in 2021, according to Inside Mortgage Finance, has perhaps invested more than any other lender in America on mortgage tech over the last decade. It has a dedicated team of thousands of workers focused on algorithms, analytics, automation and technology, and likely has more data on consumers than any competitor. In the mortgage market of 2022, using technology to create operational efficiencies will be key, executives said at the conference in Vegas. Lender profitability is shrinking amid rising interest rates, lower refinance originations, and higher expenses. According to a recent MBA report, per-loan production expenses reached $8,664 in 2021, compared to $ 7,578 in 2020, the highest level since the inception of their report in 2008. It is fair to say that the recent refi boom, from 2020 and 2021, brought a higher level of automation than in prior cycles, mortgage executives said in Vegas.  “We had a much higher level of automation with things like appraisals, title decisions, streamline income verifications that weren’t quite there yet. We’ve made a lot of progress,” said Thomas Wind, executive vice president of consumer lending at the U.S. Bank Home Mortgage.  U.S. Bank Home Mortgage is the 10th-largest lender in the U.S. Last year, it originated $102 billion, up 14.7% year-over-year, according to data from Inside Mortgage Finance.   According to Wind, despite recent developments in mortgage technology, there is still quite a bit of work to be done. “Hopefully, in a few years, we can get more and more automation through a refi cycle,” he said. “So, then, we can focus on the purchase, which has always been a core part of our journey.” The next frontier is data processing and automation, the executives in Vegas said. “I think what you’re going to start to see is a future-looking mortgage lender in the residential space to be a data processing company, not really a financial services company. I like to think of it as ultimately the investor is the finance company,” Woodring said.  A data processing company would, ideally, have borrowers’ information as quickly as possible, without asking many questions upfront, and take automated decisions, according to the executive.    Regarding technology development, big lenders are adopting different approaches.  The Minnesota-based U.S. Bank Home Mortgage has a roadmap with a vision of where the bank wants to be over the next few years, the customer experience it wants to provide, and the deficiencies it wants to avoid. Based on that, the company is trying to figure out the little things it can do each year to achieve its goals. “That helps us control the risks in the process as well,” Wind said. “We’ll try as always to make incremental improvements.” The executive said he wants his team to do pilots as soon as possible, testing new technologies in a controlled way. U.S. Bank Home Mortgage has a model focused on partnering with vendors to develop technologies. “We really try to focus on being very well integrated, also thinking of the right partner for us,” Wind said. At Rocket Mortgage, executives are trying to understand what technologies will change the world in five years, rather than being attached to the return on investment (ROI) in the short term.  “The return on investment is great as a way of looking at going after one, two, three years, maybe even four,” Woodring said. “But when you go beyond, you really have to focus on what’s really going to change the customer experience, not necessarily what saves you a little bit of money, which is important, top and bottom line are always going to be critical.” The executive said Rocket develops in-house the technology that will “move the needle” for the company but, increasingly, is partnering with vendors that can bring more efficiency to the business. “Historically, at Rocket, we have tried to build everything. We want to control the things where we can get strategic differentiation.” The post Data automation is the next frontier of mortgage tech? appeared first on HousingWire. [ad_2] Source link

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[ad_1] Judge finds Tesla liable to Black former worker who alleged bias, but slashes payout [ad_2] Source link

[ad_1] IN 2021, protections built into Windows, Azure, Microsoft 365, and Microsoft Defender for Office 365 blocked more than 9.6 bn malware threats and more than 35.7 bn phishing and other malicious emails. According to Microsoft’s 2022 Work Trend Index Report, cybersecurity issues and risks top the list of concerns for decision-makers in the year ahead. Here’s a look at six new features Windows 11 is introducing to help customers combat the security challenges of distributed work scenarios: Microsoft Pluton: Microsoft Pluton Security Processor is an innovative solution for securing a critical layer of computing. It has several key capabilities that stem from its direct integration into the CPU and the OS. It is said to be the only security processor which is regularly kept up to date with key security upgrades. Personal Data Encryption: The new Personal Data Encryption will be used to protect user files and data when the user is not signed in to the device. To access the data, the user must first authenticate with Windows Hello for Business. This means that if a device is lost or stolen, data is more resistant to attack and sensitive data has another layer of protection built in. Smart App Control: It prevents users from running malicious applications on Windows devices. Using code signing along with AI, the new Smart App Control allows only those processes to run that are deemed safe. Microsoft Defender SmartScreen: The enhanced phishing detection and protection built into Windows with Microsoft Defender SmartScreen will help check phishing attacks by alerting users when they are entering their Microsoft credentials into a malicious application or hacked website. Credential Guard by default: Windows 11 makes use of hardware-backed, virtualisation-based security capabilities to help protect systems from credential theft attack techniques. It also helps prevent malware from accessing system secrets even if the process is running with admin privileges. Hypervisor-Protected Code Integrity (HVCI) default enhancements: In the next Windows 11 release, HVCI will be enabled by default on a broader set of devices. This would prevent attackers from injecting their own malicious code and ensure that all drivers loaded onto the OS are signed and trustworthy. [ad_2] Source link

[ad_1] With interest rates on the rise, refis trending downwards and a significant decrease in purchase volume brought on by low inventory, mortgage lenders are looking for smart solutions to combat margin compressions in 2022 and beyond. HousingWire recently spoke with Maylin Casanueva, President of Teraverde, about the importance of data-driven decision making and the power insightful data can have on the overall health of a lender’s business. HousingWire: What are some key challenges lenders will face this year when it comes to profitability and productivity? Maylin Casanueva: Rising interest rates have already resulted in large decreases in volume this year. Refinances fall as rates rise. Purchase volume is also affected by low inventory, increasing property values, and when coupled with rising rates can significantly reduce a borrowers’ ability to purchase a home. Making the process increasingly more difficult. This quick reduction in volume has caused margin compression to become a major pain point. The competition for new hires to manage the refinance boom over the last 18 months has increased compensation costs as well. The result is a lot of painful decisions facing mortgage lenders. How does a lender manage declining volume, shrinking margins and potentially excess staff? Said another way, in late 2021 the key question for lenders was how to get all the loans in their pipeline to close. Now, the key question is how to cope with a much smaller pipeline, compressing margins and high compensation costs? HW: How can lenders leverage data-driven insights to overcome these challenges? MC: Data-driven decision making is and will continue to be a critical component needed to make important real time decisions moving forward. There is an enormous amount of data in the lending process, and lenders are still struggling to try to make sense of it all. Some lenders have made big investments in business intelligence tools and business analysts to provide reports, KPIs and dashboards. And many executives may say, “So what?”  Many executives have privately shared their frustration that KPIs, dashboards and reports show the summary of what we already know:  Volume is down, margins are down and compensation costs are too high given current volumes and margins. These executives also confide that they are not receiving valuable, interesting and actionable insights from the investment in tools and staff. According to one bristling executive, “I do not need coders and analysts suggesting how I run my business”. These roles have not been successful in providing the information and critical insights that lead to action.   Why have so few lenders been successful in getting their data to answer critical questions that tell the full story? KPIs are alerts that provide a snapshot at a point in time. Pull through percentage is a good example. The pull through KPI does not provide enough information to see the full picture of the final status of a loan application, and what action is necessary to reduce fallout right now. If a lender views fallout as a cost of doing business, they are missing the opportunity for increased funding from the pipeline. For instance, a lender was surprised when we analyzed fallout by category. The lender discovered certain producers had service level problems that contributed to heightened fallout. The lender discovered a way to recover loans that had a certain type of fallout. The adoption of a Point-of-Sale system by producers had a significant impact on certain types of fallout. Also, denials from certain underwriters were too low in some cases and too high in others when looking at the credit metrics of approvals and declinations. What is the nature of fallout? Which employees are causing it? Are processes or origination methods causing it? If you know the questions to ask, one can navigate to success. In short, every issue in mortgage lending has a story, and an executive needs to see the story to generate the insights (or “aha!” moments that improve productivity, efficiency and profitability). The executive needs to explore their data with the executive’s domain knowledge to discover the answers that complete the story. The combination of executive domain knowledge being applied to the data at hand in a creative way is one element of the effective implementation of data-driven decision making. Another element is to have direct access to the single source of truth. That is, accurate data from the original entry into the lender’s system of record.  If you want to get to the core issues, it is imperative to know the true factual data versus manipulated or transformed data. An example: A lender noted that their dashboards had variations that did not seem to make sense. Closer examination found the dashboards were being served erroneous data. Some of the errors were bad data entry at the inception of the loan. Bad data, coupled with the inability to detect and correct these data entry errors results in rework, potentially incorrect decisions and unsalable loans. A second set of errors can arise from incorrect coding of data source and/or transformation of data from the original system of record to a lender’s data warehouse. One CFO was shocked that the reports derived from the lender’s data warehouse contained data that differed from their original books of entry. Three issues were revealed:  mapping issues, data transformation issues and lack of error trapping. The solution is to shorten the path from the original books of entry to the use of that data, as well as error detection/correction and proof of data provenance. Lenders working with the real time data extracted from the original system of record significantly reduced data issues. In short, the health of the data being used in decision making translated directly into the health of the lender. It is like unhealthy food making the human body ill. Bad data, when ingested, can make the lender ill. HW: Where are areas that most lenders could improve their lending efficiency? MC: Primarily, executives need to ask simple questions about every report, KPI, dashboard and BI tool they use. That