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Coronavirus Spreadsheet Errors Are Deadly but Worryingly Normal

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Imagine that you’re working in a government subdepartment that tracks coronavirus infections and traces the patients’ contacts. You’ve just discovered that nearly 16,000 positive tests didn’t get into the system for a week. The people with the coronavirus know they have it, but their contacts don’t know. What do you do?

We don’t have to imagine it. In the United Kingdom, 15,841 people with coronavirus infections went unreported to Serco Test and Trace, the company running the U.K. government’s coronavirus tracing program, in the week from Sept. 25 to Oct. 2, with 48,000 of their possible contacts not warned—because of errors in a data import.

Patients were told they had tested positive, but their details weren’t passed to contact tracers until 1 a.m. U.K. time on Oct. 3, and the cases were not added to official totals until Oct. 5. The cause was simple: a mistake between different formats of Excel files. The U.K.’s response to COVID-19 is widely regarded as scattershot and haphazard. So how did they get here?

Excel is a top-of-the-line spreadsheet tool. A spreadsheet is good for quickly modeling a problem—but too often, organizations cut corners and press the cardboard-and-string mock-up into production, instead of building a robust and unique system based on the Excel proof of concept.

Excel is almost universally misused for complex data processing, as in this case—because it’s already present on your work computer and you don’t have to spend months procuring new software. So almost every business has at least one critical process that relies on a years-old spreadsheet set up by past staff members that nobody left at the company understands.

That’s how the U.K. went wrong. An automated process at Public Health England (PHE) transformed the incoming private laboratory test data (which was in text-based CSV files) into Excel-format files, to pass to the Serco Test and Trace teams’ dashboards.

Unfortunately, the process produced XLS files—an outdated Excel format that went extinct in 2003—which had a limit of 65,536 rows, rather than the around 1 million-row limit in the more recent XLSX format. With several lines of data per patient, this meant a sheet could only hold 1,400 cases. Further cases just fell off the end.

Technicians at PHE monitoring the dashboards noticed on Oct. 2 that not all data that had been sent in was making it out the other end. The data was corrected the next day, and PHE announced the issue the day after.

It’s not clear if the software at PHE was an Excel spreadsheet or an in-house program using the XLS format for data interchange—the latter would explain why PHE stated that replacing it might take months—but the XLS format would have been used on the assumption that Excel was universal.

And even then, a system based on Excel-format files would have been an improvement over earlier systems—the system for keeping a count of COVID-19 cases in the U.K. was, as of May, still based on data handwritten on cards.

PHE was initially blamed for the data disaster. But the question to ask when a procedure leads to disaster is: What problem was the procedure supposed to solve in the first place? PHE’s process was broken in multiple ways; why did it exist at all?

The process that went wrong was a workaround for a contract issue: The government’s contract with Deloitte to run the testing explicitly stipulated that the company did not have to report “Pillar 2” (general public testing) positive cases to PHE at all.

Since a test-and-trace system is not possible without this data, PHE set up feeds for the data anyway, as CSV text files directly from the testing labs. The data was then put into this system—the single system that serves as the bridge between testing and tracing, for all of England. PHE had to put in place technological duct tape to make a system of life-or-death importance work at all.

Right now, Public Health England has worked around the present problem: Serco Test and Trace still takes an Excel 2003-formatted XLS spreadsheet as part of the data pipeline—but the process now uses multiple sheets, so the files don’t overflow again.


The U.K. government has used wide-ranging outsourcing to the private sector to build a COVID-19 response system quickly. But outsourcing is fraught with hazards of exactly this kind, where faulty systems are created to get around regulatory problems or cut corners

A shortage of home testing kits led to the government worrying that people would request multiple kits. Identity verification was outsourced to the credit agency TransUnion—which implemented it by running credit checks. People who couldn’t pass TransUnion’s particular credit checks were refused tests, including many who had bank accounts and were on the electoral roll, and so should have been entirely verifiable as being real people. There are 5.8 million U.K. residents who have bad credit histories and so could be refused a test kit, which disproportionately impacts the already poor and disadvantaged—with obvious implications for public health.

Many of those rejected by the credit check were told to visit testing centers at the other end of the country, such as London residents being told to go to Scotland for a test. One London resident was advised by staff at a testing center to say she lived in Aberdeen, Scotland—and this got her a test in London.

The Brookings Institution report Doomed: Challenges and solutions to government IT projects lists factors to consider when outsourcing government information technology. The outsourcing of tracking and tracing is an example where the government has assumed all of the risk, and the contractor assumes all of the profit. PHE did one thing that you should never do: It outsourced a core function. Running a call center or the office canteen? You can outsource it. Tracing a pandemic? You must run it in-house.

If you need outside expertise for a core function, use contractors working within a department. Competing with the private sector on pay can be an issue, but a meaningful project can be a powerful incentive.


This sort of error doesn’t have to happen. There’s a set of basic principles to apply for vital functions when you’re working within an unreliable organization. Site Reliability Engineering principles are lifesavers when you’re short on both human and technical resources.

The first step is fully understanding your task. Document what you need. Document whether you can get it or not. Set explicit priorities, and get signoff. Document when there are requests to drop a priority because of lack of resources.

If the data import from the labs had been checked daily, the problem would have been noticed and solved immediately. Are you cross-checking your numbers? Do you have a list of the numbers that need to be verified—and do you know what “normal” numbers look like? If you can’t get the people you need to do this work, have you documented the refusal?

Consider your software support. In the U.K., the Government Digital Service, part of the Cabinet Office, uses LibreOffice, the current version of the old OpenOffice. LibreOffice is free, though you can buy support easily. The Government Digital Service is on the advisory board of the Document Foundation, the nonprofit behind LibreOffice. The LibreOffice spreadsheet also automatically corrects math bugs in Excel—a function that gives the same wrong answer as Excel will have a corresponding function that gives the correct answer.

Document your duct tape stopgap solutions. Document and request the support that you need to do the job robustly—and document it being refused. If spreadsheets are all you have, send your staff on training courses. Training and caution are much cheaper than a widely publicized disaster. Particularly when lives hang in the balance.

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Loans Bad Credit Online – Loans Bad Credit Online – Reforming India’s deposit insurance scheme | Fintech Zoom | Fintech Zoom

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Loans Bad Credit Online – Loans Bad Credit Online – Reforming India’s deposit insurance scheme | Fintech Zoom

Loans Bad Credit Online – Loans Bad Credit Online – Reforming India’s deposit insurance scheme | Fintech Zoom



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Loans Bad Credit Online – Reforming India’s deposit insurance scheme | Fintech Zoom

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The government’s incentive to step in and bail out depositors when banks fail is clear from past experience.

By Anusha Chari & Amiyatosh Purnanandam

The failure of the Punjab and Maharashtra Co-operative Bank (PMC) in September 2019 shone a light on the limitations of India’s deposit insurance system. With over Rs 11,000 crore in deposits, PMC bank was one of the largest co-op banks. That the Deposit Insurance and Credit Guarantee Corporation (DICGC) insurance covered depositors, provided little solace when the realisation hit that the insurance amounted to a mere Rs 1 lakh per deposit.

The predicament of PMC depositors is, unfortunately, not an anomaly. Several bank failures over the years have severely strained RBI and central government resources. While co-operative banks account for a predominant share of failures, other prime examples include the Global Trust Bank and Yes Bank failures. These failures entail a direct cost to the taxpayer—the DICGC payment or a government bailout. More importantly, bank failures impose long-term indirect costs. They erode depositor confidence and threaten financial stability, presenting an urgent need for deposit insurance reform in the country.

A sound deposit insurance system requires balancing two opposing forces: maintaining depositor confidence while minimising deposit insurance’s direct and indirect costs. At one extreme, the regulator can insure all the deposits, which will undoubtedly strengthen depositor confidence. But such a system would be very expensive.

A bank with full deposit insurance has minimal incentive to be prudent while making loans. Taxpayers bear the losses in the eventuality that risky loans go bad. Depositors also have little incentive to be careful. They can simply make deposits in the banks offering high interest rates regardless of the risks these banks take on the lending side.

Boosting depositor confidence and reducing direct and indirect costs require careful structuring of both the quantity and pricing of deposit insurance. Some relatively quick and straightforward fixes could help alleviate the public’s mistrust while improving the deposit insurance framework’s efficiency.

India has made some progress on this front over the last couple of years. First, the insurance limit increased to `5 lakh in 2020. Second, the 2021 Union Budget amended the DICGC Act of 1961, allowing the immediate withdrawal of insured deposits without waiting for complete resolution. These are very welcome moves. Several additional steps could bring India’s deposit insurance system in line with best practices around the world. Even with the increased coverage limit, India remains an outlier, as the accompanying graphic shows.

The government’s incentive to step in and bail out depositors when banks fail is clear from past experience. However, these ex-post bailouts are costly. The bailout process also tends to be long, complicated, and uncertain, further eroding depositor confidence in the banking system. A better alternative would be to increase the deposit insurance limit substantially and, at the same time, charge the insured banks a risk-based premium for this insurance. Under the current flat-fee based system, the SBI pays144 the same premium to the DICGC—12 paise per 100 rupees of insured deposits—as does any other bank!

A risk-based approach will achieve two objectives. First, it will ensure that the deposit insurance fund of the DICGC has sufficient funds to make quick and timely repayments to depositors. Second, the risk-based premia will curb excessive risk-taking by banks, given that they will be required to pay a higher cost for taking on risk.

India is not alone in trying to address the issue of improving the efficiency of deposit insurance. The Federal Deposit Insurance Corporation (FDIC) recognizes that the regulatory framework governing deposit insurance is far from perfect and the United States is moving towards risk-based premia. The concept is similar to pricing car insurance premia according to the risk profile of the driver. The FDIC computes deposit insurance premia based on factors such as the bank’s capital position, asset quality, earnings, liquidity positions, and the types of deposits.

In India, too, banks can be placed into buckets or tiers along these different dimensions. The deposit premium can depend on these factors. It is easy to see that a bank with a worsening capital position and a high NPA ratio should pay a higher deposit insurance premium than a well-capitalized bank with a healthy lending portfolio. The idea is not dissimilar to a risky driver paying more for car insurance than a safe driver.

Risk-sensitive pricing can go hand-in-hand with the increase in the insured deposit coverage limits bringing India in line with its emerging market peers. In a credit-hungry country like India, these moves would build depositor confidence, possibly increasing the volume of deposits and achieving the happy result of the banking system channeling more savings to productive use.

Chari is professor of economics and finance, and director of the Modern Indian Studies Initiative, University of North Carolina at Chapel Hill and Purnanandam is the Michael Stark Professor of Finance at the Ross School of Business, University of Michigan

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5 Signs You’re Not Ready to Own a Home, According to a CFP

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The housing market has boomed over the last year, despite a global pandemic and millions of Americans struggling to make ends meet. 

Many people are spending less on entertainment, clothing, travel, and other discretionary purchases during COVID. Federal student loan borrowers have seen temporary relief from their loan payments. These expenses will most likely rise again after the pandemic, and many people who committed to a new home with a large mortgage will struggle to keep up. 

I often speak with clients and prospective clients who want to buy a home before they have a strong financial foundation. Buying a home is not only one of the largest purchases you’ll make in your lifetime, but it’s also a huge commitment that’s extremely hard to undo if you have buyer’s remorse

It’s important to make a thoughtful, informed decision when it comes to a home purchase. Before you take the plunge into homeownership, check for these signs that you’re not quite ready to buy. 

1. You have credit card debt

Credit card debt can be a drain on your monthly budget, and when combined with student loans and a car loan, it can lead to high levels of stress. 

Generally, more debt means higher fixed expenses and little opportunity to save for long-term financial goals. Your financial situation will only get worse with the addition of a mortgage. I always recommend that clients be free of credit card or other high-interest debt before they consider buying a home. 

To rid yourself of credit card debt, take some time to get a good handle on your cash flow. Take an inventory of your spending over the last six to 12 months and see where you can cut back. From there, develop a realistic budget that includes aggressive payments to your credit cards. 

There are several strategies to help you knock out credit card debt fast. Regardless of the method you choose, stick with the plan and track your progress along the way. Once you pay off your credit cards, you can allocate your debt payments to savings, which can help you avoid this situation in the future.  

2. You have bad credit

Bad credit is not only a sign that you may not be ready to take on a mortgage, it can also signal a high risk to

mortgage lenders
. A high-risk status results in higher interest rates and more strict requirements to qualify for a loan. A mortgage is one of the largest loans you’ll take out in your lifetime, and if you get behind on payments, you could lose your home. 

Just as with credit card debt, bad credit could be a result of past financial mistakes. Dedicating the time to repair bad credit and improve your credit score will help you beyond purchasing your dream home. 

Start by pulling a recent credit report from each of the three credit bureaus so you can review it for errors. Dispute any errors, address past-due accounts, and bring your overall debt balances down. It’s helpful to learn what has a negative effect on your credit score so you can avoid these mistakes in the future. 

3. You don’t have an emergency fund (or an inadequate one)

If you’re unable to save for a rainy day, you probably don’t have enough money to buy a house. Owning a home is a big responsibility, and unexpected expenses pop up all the time. In addition, you could lose your job, have a medical emergency, or another unexpected expense unrelated to the home. Maintaining an emergency fund is a good sign that you have discipline and are prepared for the responsibility of homeownership.

Many financial experts recommend saving at least six months of living expenses in an emergency fund. If you have variable income, own a business, or own a house, you should save more. To build an emergency fund, set money aside from each paycheck and automate transfers to make the process easier. Give your emergency fund a boost when you receive lump sums such as bonuses or tax refunds. Start by saving one month of living expenses and build from there. 

4. You don’t have separate savings for your home

I always advise clients to set aside savings for a home in addition to an emergency fund. It’s a bad idea to start homeownership with no savings. Whether you have unexpected expenses related or unrelated to the home, having no emergency fund after a home purchase will lead to unnecessary stress — and possibly more debt. 

When purchasing a home, you’re responsible for a down payment and closing costs. While a 20% down payment is ideal to avoid private mortgage insurance, a down payment of at least 3.5% is typically required. Closing costs can range from 2 to 5% of the home’s value. 

Also, you will have moving costs, costs to spruce up your new place (like new furniture or light cosmetic updates), and any initial maintenance and repairs. Be sure to budget for these items to know how much to save on top of your emergency fund. It doesn’t hurt to boost your emergency fund, too, in preparation for homeownership. 

5. You have a low savings rate

It’s much easier to develop good savings habits before you have a lot of responsibilities. To get on track for financial independence, several studies show that you should save at least 15% of your income. The longer you wait, the more you’ll need to save. 

If your savings rate is low before you purchase a home, it will most likely worsen after becoming a homeowner. Even if your mortgage is similar to your rent, ongoing maintenance and repairs, higher utilities, and homeowners association fees can wreak havoc on your budget. 

Take a look at your current savings rate and see if you’re on track for financial independence. If you’re saving less than 15 to 20% of your income, work to improve your savings rate before you consider buying a home. A strong savings habit can help you build your home savings fund faster and ensure that a home purchase doesn’t impede your long-term financial goals. Finally, understand how much house you can afford so you can avoid being house poor. 

Buying a home can be rewarding, and when done the right way, it’s a way to build wealth. Before you decide to buy a home, it’s important to understand your numbers and ensure that you’re ready for the commitment. Without preparation, your dream home could be detrimental to your long-term financial goals.

Chloe A. Moore, CFP, is the founder of Financial Staples, a virtual, fee-only financial planning firm based in Atlanta, Georgia and serving clients nationwide.

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