CRx provides its clients a suite of key features listed
below
Financial Analytics
CRx provides features that
allow strengthened fundamental analysis, thereby facilitating
high-impact decision making and guidance on market trends.
Flexibility to create
and edit multiple financial templates, catering to different
business lines with Excel like features for entering
formulas
Ability to upload/ enter
data in MS Excel® like format (e.g.+12,785-342)
and view detailed Cash Flow and Ratio Analysis
User can enter detailed comments as
well as help text for each line item.
User can set and monitor financial covenants
Ability to generate default projections
based on trend analysis of previous period
Ability to project impact
on businesses in response to any sharp change in global
variables such as cost of input (steel prices, oil prices),
demand for output, etc.
Capability to perform peer group analysis
owing to centralized database
Flexibility in generating
detailed, summary, comparison or other customized reports
with graphical representations of trends
Secure and detailed
data archive of customer’s financial data, useful
for reports, comparisons and analysis
Internal Risk Rating
A key development in risk
management among financial institutions has been the development
of internal risk models. A track record of consistent internal
assessment of credit risk is an important part of the regulatory
framework from the point of view of implementation of Basel
II requirements on capital adequacy. CRx has the following
features that take care of these prerequisites.
Ease in defining multiple
risk models for rating obligor and facility in line
with the credit policy of the organization
Ability to capture collateral and guarantor
details for a facility
Ability to define inflators/deflators
for score/rating based on scenarios
Ability to analyze financial
(actual and projected) information and non financial
information to rate industries, countries and individual
businesses of all sizes based on model definition
Facility of Back-Testing
for analyzing and testing alternative models using historical
data over large sets of clients for determining the
validity of the credit risk measurement of the model