Nirph Identification Solutions - a biometric identification technology company

Fingerprint recognition technology enables secure distribution of pensions and benefits on a mobile basis to an underprivileged illiterate population. The Nirph Pensioner management system starts with the collection of pension contributors and ensuring that each person has a unique identity on the National Pension database.

Uniquely identify/verify pension contributors and next of kin using fingerprint identification;
Properly authenticate pension contributors;
Convert the existing fingerprint image databases (if available)
Capture fingerprint from both paper and electronic devices;
Compatible with various electronic fingerprint capture devices
A completely integrated solution (End – to - End)
Solution used by Government pension funds, Pension Fund Administrators (PFAs), Pension Fund Custodians (PFCs) and any other stakeholders.

Social welfare solutions

Social welfare, health and human services agencies across the globe realizes the potential that Identity Management solutions offer for increased program integrity and reduced fraud.

Currently, the use of biometric capabilities is not standard in the process of determining eligibility for and delivery of government benefits and services.

Expected objectives include:

increased program integrity,
reduced fraud and
program costs,
improved public service and access,
And enhanced benefit utilization analysis and targeting of interventions to improve program results.

Key to achieving these outcomes is the ability to validate customer identity at point of enrollment and to verify identity at the point of delivery of public benefits.

Benefits:

Detection of duplicates (Duplicates are eliminated, no more multiple records on the same person)
Elimination of double dipping (Our advanced AFIS solutions eliminates multiple identities)
Easy identification (Nirph solutions accurately identify individuals in less than 1 second)

Various private and government agencies are implementing biometrics to prevent double-dipping and welfare fraud. Each person who attempts to register for the government service provides fingerprints, which are compared to all other previously registered people. If a matching fingerprint is found in the database, it suggests that this is a possible case of double-dipping.

For serious biometric applications, such as detecting welfare fraud, there needs to be a human component added to the automatic biometric matching. For example, all cases where a new applicant is matched to an existing record in the database, which could be fraud or a false match, are referred to a trained Fraud Investigator. The investigator does a side-by-side comparison of the fingerprints, photographs, and demographic information before making any conclusions about possible fraud. The same process is also done in cases where an apparent returning applicant fails to match their existing record in the database, which could be fraud or a false non-match.

Biometrics for Service Use (Payout or other services)

Using biometrics for service is often simpler than enrollment. During service use, a person is making a claim about an existing relationship, and the task is to determine if that claim is authentic. Instead of comparing biometric information to every record in a database (1:N comparisons), service authentication can be done by comparing biometric information with one stored record (1:1 comparison). The biometric information, such as a fingerprint are stored in a centralized database, as well as with the individual, perhaps on a smart card (if applicable) .

This form of authentication is often being used to verify the accuracy of some kind of document or credential. So, for example, biometric passports (or e-passports) can contain stored information about faces or fingerprints, and the authenticity of the claim that this is an individual’s passport can be made by a 1:1 biometric comparison. Since there is only one comparison being made, the accuracy for authentication decisions can be higher than that for service enrollment. (A service might still choose to use 1:N comparisons if they want to perform authentication using the biometric alone, but the size of the N would probably be limited to the list of current customers rather than an entire population.)

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