Credit Score in India is a three digit number ranging from 300 to 900, which signifies the creditworthiness of an individual based on his credit profile and past repayment track record.

The weights of various criteria that they look at :

1. 35% Payment History
2. 30% Amount Owed
3. 15% Length of History
4. 10% New Credit
5. 10% Types of Credit Used

The most important factor in determining your score, payment history, is simply a record of whether you've paid your bills on time.

A credit score of 900 is either not possible or not very relevant. The number you should really focus on is 800. On the standard 300-850 range used by FICO and Vantage Score, a credit score of 800+ is considered “perfect.” That's because higher scores won't really save you any money.

FICO scores range from a low of 300 to a high of 850 – a perfect credit score which is achieved by only 1% of consumers.

1. Hunter Fraud Score is a rating score launched locally in India by Credit rating agency, Experian, to detect fraud in credit applications to banks and insurance companies and help them lower their losses.
2. Hunter is the commonly-used abbreviation in the credit industry for the National Hunter system. ... Members of National Hunter submit each and every detail given by consumers on credit applications. These details are subsequently checked against all further applications to identify inconsistencies that may indicate fraud.
3. Hunter matches the application data against multiple data sources including your fraud data as well as shared fraud databases, mortality data and dedicated 'watch lists'. It uses customised rules to cross-match data sources to highlight inconsistencies, as well as matching it to known fraud data.
4. There are various criteria based on which information is matched in the loan application from different data sources and inconsistencies after that are identified. The company has some sophisticated analytical solutions which allows it to create an advanced analytical approach, to predict and calculate some authentic score that can help banks lower their losses. A data repository has been created to collect the data of all the past customers in addition to their KYC norms data, on which data mining is performed to filter out the useful minute details and extrapolate the user's data. The solution has some customised rules to analyse different data sources to highlight inconsistencies and discrepancies so that it can match with the known fraud data. The results calculate the level of fraud risk and any application if found suspicious is moved into a special investigation tool to take further action.
5. Under Section 45 of the Insurance Laws (Amendment) Act, if three years duration is crossed for any reason to reject an insurance claim then it cannot be rejected after that period. So, this repository would help them catch criminals before they breach the obstacles to commit fraud. Data from life insurers reveals that there is about 20 per cent rise year by year in fraudulent claims. A nexus has been identified of fraudulent people who get their claims passed through their relatives in the authorities which pass the claims. Depending on the screening, businesses will be able to identify applications that have high probability of potential fraud.