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Wealth Management

CHECKLISTS FOR CHOOSING A CORRECT TRADING MENTOR

The trading mentor should be proficient in the particular field and have proper cognition about the field. The duty of the mentor is to help the beginners to improve their trading performance. If the mentor has a lack of experience, he or she will not able to help others. The newcomers face different types of problems when they arrive in the field of Forex, so they become disoriented. At this time, a trading coach can help them to deal with the situation. So, this is very important to choose a good one. Let’s know about the checklist for making the selection of a good one.

 

Full-Time Trader

The mentor should be a full-time trader so that he or she can understand the current market position. If the person cannot practice now, he or she will not able to give the proper solutions to the beginners. So, the traders who trade regularly by managing the money can help others. You also find out that he or she has proper experience in your zone. When the person will invest time to learn about the market, he or she will able to gain more knowledge and ability to help others.

 

Be Successful

If the coach is not successful in his or her field, he or she will not able to help others. Successful investors have the power to inspire others. The fresher will also get motivation when he or she sees that the mentor has gained success. So, they try to learn from him or her properly. The person also needs to share his or her wisdom with others. People should bear in mind that 5% to 10% of traders are successful in the Forex field. So, when you make the choice, you have to be careful. You can also see the features of Rakuten. And we believe, if you analyze their premium offer, you will definitely say let’s trade with Rakuten as they provide professional environment to the retail traders.

 

Motivational and inspirational

If the person cannot able to motivate others for working hard, he or she will not become a good mentor. The coach should inspire the beginners so that they can go forward. The newcomers cannot ignore the emotional components so they cannot able to think for the better. In this situation, the coach can help by inspiring the. If the professional able to increase the confidence level of the fresher by motivating them, you should choose him or her. On the other hand, some are not so bothered about the beginners’ performance, so they should not choose them.

 

Should Respect the Fresher’s Trading Style

The investors have their own styles and preferences. People also need to give priority to their own patterns which will help them to trade independently. The person should try to demonstrate their individuality in the Forex market. If the coach tries to change the style of the trader, this will not better for him or her. When the mentor will not show proper respect for your trading style, you will not able to be comfortable with him or her. Here, he or she will always try to change you. So, investors should aware of this fact.

The coach will help the investors to identify the new opportunity and will increase the thirst for gaining knowledge. They will not able to ensure success but they can able to show the right path. Some mentors are not able to provide authentic information. So, this is not an easy task to find a suitable one. An honest coach can support people in a difficult situation. On the other hand, a dishonest mentor can destroy the career of the fresher. So, the investors are required to check the review and they can also take suggestions from the others to select a suitable person. If the coach demands money from you, then you should understand that he or she is not the right choice.

 

Wealth Management

HOW DO YOU ADAPT YOUR INSURANCE PRICING STRATEGY IN THE FACE OF INCREASED PRICE COMPETITION?

By Ketil Kristensen, Senior Advisor, Insurance, SAS

 

Many countries in Europe have in previous years experienced increased price competition for general insurance products. Especially in Southern Europe, the competition has been very fierce, fuelled by online price comparison websites. In Spain, Portugal and Greece, there has been a substantial drop in average premiums for products like motor, home and health insurance. This poses a real threat to the profitability of property and casualty insurers.

While some insurance products are highly specialised and almost impossible to compare, most common products have increasingly become commodities. Consumers can now easily compare them online.

When comparing insurance policy prices and details becomes as effortless as getting quotes for airline tickets or hotel accommodation on price comparison sites, more insurance companies will eventually enter the market. And thus price competition will increase.

 

Preparing for a price war

Once the price war starts, there is no way to avoid it. And insurers need to meet their competitors head-on.

To win a price war, insurers need to be meticulous when they set the premium levels. They might also need to rethink the definition of “profit” when they are making pricing strategies for the future. In a market where premium levels are volatile and the competitive situation may change rapidly, insurers also need the capability to evaluate potential future scenarios in a short period of time.

 

Setting the premiums right

In the fast-paced digital era, customers expect insurance prices to be easily available online. They will make inquiries for insurance covers for their cars or homes on price comparison websites and expect the prices to be available immediately. From an insurer’s point of view, the premium customers will see on their screens when comparing insurance policy prices is the sum of the insurer’s technical premium and the commercial loading.

The technical premium represents the break-even price that the insurance company would charge for the policy if it had no costs and no desire to make a profit. Commercial loading represents the sum of the insurance company’s costs and the profit it expects to make on the policy. Technical pricing is the subject of many actuarial textbooks. But as machine learning algorithms make their way into actuarial departments, we will need to rewrite those books. Modern pricing techniques that include machine learning algorithms are a notable improvement compared to traditional models. If applied properly, ML models will result in more accurate technical pricing given the same data.

But what about commercial loading? How much profit should the insurer aim for?

Every one of us has a different tolerance for how much we would pay for, e.g., a car insurance policy. Some customers don’t consider price to that important. Others will try to search for a better deal elsewhere, regardless of how much time the process would take. Most customers are somewhere in between.

Being able to price the insurance products analytically based on the “willingness to pay” is, for many actuaries, seen as the holy grail of insurance pricing.

 

Personalised premiums

Most insurers already do personal pricing to some extent today. For example, they give different discounts to policyholders with equal risk. However, there is often a great potential to do segmentation and price calculations in a more analytical manner. Ideally, insurers would like to set the premiums as high as possible, but not so high that customers move their policies to another insurer.

On the other side, insurers would like to move customers away from their competitors by offering low premiums – but not too low. The insurer must first determine the price sensitivity of insurance customers and then price each insurance policy so that it maximises the profit for the insurer.

Insurers that can quickly reoptimise changing prices in the online market will also quickly identify customers that are at risk for churn. They can then perform the appropriate actions to prevent this from happening.

 

Rethinking ‘profitability’

When insurers think “profit,” they usually mean the income statement for next year. This is about to change. The concept of Customer Lifetime Value (CLV) is becoming more and more common in the insurance industry. And many insurers are now refining their pricing strategy based on a maximisation of the CLV of all its customers, thus not focusing solely on the profit definition in the income statement. The CLV of an insurance customer is the net present value of this customer for the insurer, where behavioural effects like renewal, cancellation and cross-selling of other insurance products are considered for the entire lifetime of the customer.

To accurately compute CLV for a customer, the insurer will need data that describes the behavioural patterns of the customer. Most insurance companies have quite a lot of such data available – the problem is usually that it is not adequately structured. In practice, to quantitively identify the customer lifetime value, insurers need to integrate both actuarial and customer behaviour models. Once a system for this is in place, insurance companies will have a strong quantitative foundation to compute the customer lifetime value of their policyholders.

 

Competitive insurance pricing

When a customer determines where to buy insurance, the price is the most important factor. Thus, to stay competitive and still run a profitable business, insurers need to set their premium levels just right. The evolution of price comparison websites – which provide real-time quotes on competitor prices and increased access to data that contains information about the customer’s insurance risk – has made the actuary’s job of calculating the premium more complicated.

Over the years, SAS has worked together with insurers to ensure that strong system support is in place to compute premium levels down to an individual policy level. These pricing systems have been put through the test in some of the most competitive insurance markets in Europe. They have turned out to be a valuable strategic tool for insurers to balance the desire for profit against the desire for market share. And maybe most important of all, they have enabled these insurance companies to effectively join the price war, fight it and still make a profit.

 

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Wealth Management

FROM EFFICIENCY TO NEW INVESTMENTS – WHY BLOCKCHAIN IS MORE THAN MEETS THE EYE

Thomas Borrel, chief product officer at Polymath

 

Blockchain has been an extremely hot topic in 2021. With companies and financial institutions internationally having to adapt to an increasingly digital world, the true potential of blockchain is becoming increasingly clear. We have seen hospitals using the technology to track vaccine distributions, major blue-chip companies floating digital assets or ‘stablecoins’, even progress made by central banks in piloting and adopting digital currencies

When it comes to the world of finance, much of the attention has focussed on the booming price of Bitcoin, and there has been much excitement around using cryptocurrencies as an alternative investment. However, the real potential of blockchain technology stretches far into traditional finance and beyond.

 

Improving access to investment options

Security tokens created and issued on the blockchain are already being used to improve efficiency in a variety of more traditional asset classes, ranging from real estate to green bonds. The Sustainable Digital Finance Alliance (SDFA) and HSBC Center of Sustainable Finance recently joined forces to highlight how security tokens for green bonds can reduce management costs and increase operational efficiency by up to ten times. And in early 2020, RedSwan CRE Marketplace tokenised $2.2B in commercial real estate, making it one of the biggest tokenisations we’ve seen so far.

Thomas Borrel

However, the potential of tokenisation does not only stand to improve the process of trading traditional assets; blockchain can also open up the pool of investors able to participate. To date, the focus has been on how fractionalisation brings benefits to retail investors by lowering the bar to entry. However, the retail regulations are still very stringent, which is important to protect non-professionals from disproportionate losses.

Tokenisation can be used to enable large institutional investors to buy into smaller projects. Referred to as aggregation, this process can be used to bind assets together so that they meet an institution’s minimum investment threshold. Because of the transparency of blockchain, the investor is still able to inspect each individual offering and ensure each element meets their quality and risk requirements, but by packaging it into one larger token, an institution can diversify with assets that would have otherwise flown under its radar.

 

Optimising efficiency and minimising risk

Risk management and operational efficiency are usually at the core of any financial institution’s wider strategy. However, no matter how much firms optimise their own processes, there are a range of financial instruments that are still very prone to issues in these areas, especially those that are traded ‘over the counter’ (OTC). The best example of this is likely the bonds market – a multi trillion-dollar market, where OTC trades are still common practice.

When an OTC trade is conducted, it is often so over the telephone – one person calling another to make a deal. This introduces significant information risk with securities operations teams reporting error rates as high as 40%. When instructions for the trade are passed on to the custodians, they will spot the discrepancy. They then have to investigate and find out what has gone wrong, often resulting in very long delays to settlement times.

Blockchains go a long way to solving this problem, providing transparent access to trade and clearing information so that operational issues can be caught earlier and help mitigate settlement risk (i.e. settlement failure). For example, on Polymesh settlement instructions must be affirmed prior to settlement, in a case where an OTC trade has been improperly captured by one counterparty, the counterparty which has affirmed the instruction can see that the other counterparty has not affirmed the instruction within a defined period. In this way, the affirming counterparty can reach out proactively prior to the settlement date to rectify the situation and avoid settlement failure.

Trading on blockchain also generates an easily accessible, secure ledger of trading information. When it comes to reporting in traditional asset classes, the process is highly manual and often expensive. But, with a blockchain solution, reporting is built into the ecosystem from the ground up. There are no significant additional costs or resources required to extract this data and share it where necessary, and the number and complexity of the steps required to complete reconciliations between different entities are reduced and simplified.

 

Is tokenisation a ‘cover all’ solution?

Fundamentally, certain traditional asset classes are not right for the blockchain yet. Instruments with well-established frameworks, like publicly traded stocks, already have very well-formed, rigorous rails in place, and so transferring to a blockchain could cause disruption and incur unnecessary costs.

It is very common to hear blockchain advocates claiming that blockchain technology should be introduced into every corner of the finance space, which is misguided. Blockchain should be introduced where it brings value to investors or institutions. It should be about augmenting and supplementing the marketplace – not overhauling it, or at least not until the incumbent systems no longer keep up with demand.

The costs and infrastructure associated with capital markets have made some assets – like green bonds or real estate – too expensive to bring to market and service, or too difficult to invest in. These use-cases are examples of where tokenisation can really shine.

Blockchain is an extremely powerful tool, with a range of exciting applications and potential benefits for businesses and financial institutions, ranging from risk management and efficiency through to enabling new investments. However, as with any product, it isn’t the answer to all problems, and must be treated as a powerful enabler – not as an agitator.

 

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