How we calculate our ratings
How Fairer Finance calculate our ratings based on customer happiness, customer trust, complaints and transparency.
Most of Fairer Finance’s ratings are compiled by looking at four key elements:
- How happy are a company’s customers?
- How much do customers trust the company?
- How good is the company at handling complaints?
- How transparent is the company?
These four criteria are used to create our ratings for bank accounts, savings accounts, mortgages, credit cards, personal loans, car insurance, home insurance and travel insurance.
For our life insurance ratings, we don't look at customer happiness and trust. Instead, we look at:
- What percentage of claims does the insurer pay out?
Happiness & trust
Fairer Finance uses independent polling company, Opinium, to survey thousands of UK banking and insurance customers in February and August each year. We combine the results of these surveys every six months, downweighting the significance of the older data. Currently, our happiness and trust ratings are compiled using over 23,000 responses from our surveys. Opinium uses a nationally representative panel, and we believe our customer polling data is some of the most accurate in the UK.
We must receive more than 40 customer responses for a company before they will appear in tables. It is our intention to continue increasing these thresholds, to increase the statistical robustness of our results.
To calculate our customer happiness ratings, we ask customers how satisfied they are overall with their provider, offering them five possible answers: extremely satisfied, fairly satisfied, neither/nor, fairly dissatisfied, extremely dissatisfied. To calculate the percentage score, we multiply the number of extremely satisfied responses by 2, and fairly satisfied responses by 1. We then multiply the number of extremely dissatisfied customers by -2 and the number of fairly dissatisfied customer by -1. We add these numbers together and divide them by the number of respondents. We then turn this score into a percentage of the maximum score of 2.
To calculate our trust scores, we ask customers to agree or disagree with the statement "I trust this brand", offering them five possible answers: strongly agree, agree, neither/nor, disagree, strongly disagree. We use the same technique as we do with our customer happiness score (explained in the paragraph above), to calculate the percentage for our trust score.
The Financial Ombudsman Service (FOS) publishes complaints data on financial services companies every six months.
Complaints are only referred to the FOS once they have been rejected initially by the company, and the customer decides to appeal.
In its six-monthly data release, the FOS publishes details of the percentage of complaints that are upheld in the customer’s favour, for every company that has more than 30 FOS complaints during the period.
Broadly speaking, companies with low uphold rates are doing a good job – as the Ombudsman is backing their decision to reject the complaint in the first place. Companies with high uphold rates are doing less well – rejecting complaints that should have been upheld.
To create our complaints score, we analyse the Ombudsman data over the past four years, weighting the data so that more recent data is given more prominence. As some brands report their data to the Ombudsman by group, and not by brand, we sometimes have to use the same score for multiple brands. For example, Bank of Scotland’s data includes Halifax customers, so they both get the same score in our bank account tables. When it comes to insurance, we try to make sure we're looking at data relating to the company who will deal with the complaints for that brand. For example, Prudential's car insurance is administered by UK Insurance, which is owned by
If a company does not feature in the Ombudsman tables, because they have fewer than 30 complaints, we ask them to provide their own complaints data, and get this verified by the Ombudsman. There are a very small number of companies who have not provided us with their data. For those, we use a sector average.
Once we have generated a weighted uphold score for each company, we subtract this from 100 to create a score which reflects the percentage of complaints that were not upheld in the customer's favour. This means that a higher score shows a better performance by the company.
Our Transparency scores are compiled by Fairer Finance’s research team, and the method used to do so is twofold:
Firstly, for each company we go through the online buying process and check whether or not all the relevant information is provided to customers as they proceed towards purchase.
We expect all relevant information to be available on the main page before the completion of the purchasing process, with any additional information (such as policy documents) to be clearly linked, and the navigation required to get to this information to be obvious and logical. Therefore, we not only analyse the amount of information available before purchase, but also the design and layout of a company's website, judging it on how effectively it makes this information available to the customer.
In general insurance, we also look at whether cancellation terms and any fees or charges are clearly explained in the purchase process, and look at whether consumers are automatically opted into add-ons or data protection consent. In life insurance, we look at whether exclusions are clearly laid out, and whether decreasing term and waiver of premium are clearly explained, if they are offered.
For credit cards, we look at whether the summary box is accessible, and whether the terms of any offer are made clear to customers before they start their application. In both loans and credit cards, we look to see whether lenders make it clear that the advertised rates may not be the rate you are offered.
For savings accounts, particular emphasis is put on what happens to accounts after maturity, and whether what companies do with their customers' money at this time is transparent and fair.
Secondly, in all sectors we score companies on the readability and accessibility of their policy documents, or terms and conditions. Specifically, we ask:
- Are the documents written in plain English? This means analysing documents for legal and financial jargon, sentence length, and grammar, as well as averaging results from seven different readability tests, such as The Flesch Reading Ease formula.
- Are the documents clearly designed and laid out? This means looking at, amongst other things, the size of the typeface and the amount of white space, as well as the use of colour, images and infographics.
- Are the terms and conditions or policy document easy to find before completion of purchase?
We can provide companies with a free full breakdown of their transparency analysis on request. Please email us at firstname.lastname@example.org.
Claims score and total score for life insurance
In our life insurance ratings, we use statistics published by insurers, revealing what percentage of claims they have paid out every year. The main reason life insurance claims are turned down is that a customer hasn't given correct information when they made their application. Very few claims are rejected - and all life insurance companies pay between 84% and 100% of claims.
We take insurers' claims scores over the past three years, and weight them so that more prominence is given to scores from the most recent years. We then print this weighted score in our tables.
When calculating the total score for each insurer, we don't simply use the raw claims score. Instead, we subtract 90 from each score, and divide the result by 10. We then turn this result into a percentage, which is averaged with the complaints and transparency score to create the total score. As an example, if a company has a % of claims paid of 98.42%, we subtract 90 from this, divide by 10 and create a percentage score of 84.2%.
We believe that the responsibility lies with the insurer to ensure that life insurance applications are valid - and all life insurers should be aiming to be in a position where they pay 100% of claims.
We don't believe any insurers in our table should be avoided because of their record on claims - but our ratings reward companies who have close to a 100% percent record on claims.
Our overall score
To calculate our final Fairer Finance score, we take an average of a company's scores across each area of our analysis. Each part of the analysis is given equal weighting.
To decide who is awarded a gold, silver or bronze ribbon, we use Excel's NORM.DIST function. This calculates how far away each company is from the average score, in terms of standard deviations. To qualify for a gold ribbon, a company's NORM.DIST score must be above 0.8. Scores between 0.7 and 0.8 qualify for a silver Fairer Finance ribbon. Scores between 0.6 and 0.7 qualify for a bronze Fairer Finance ribbon.
If this seems overcomplicated, we use this technique to remove the ability for our research team to have any discretion over which providers qualify for gold, silver and bronze ribbons. It may be commercially advantageous for us if one company is awarded a ribbon, because we may know that they are keen to buy our endorsement. So we have removed our ability to have any control over who qualifies for our ribbons, to ensure our ratings can be considered truly independent and robust.
The only way to be awarded a gold, silver or bronze ribbon is to be significantly better than other companies in the sector.
Questions about our ratings?
We're committed to being as open and transparent about our ratings as possible - so if you're a company and have any further questions, please do get in touch, and we'd be happy to explain them in more detail. You can email us at email@example.com.