WHAT WE DO / SOLUTIONS BY FUNCTION
Risk Management
The phenomenal growth in Consumer lending witnessed in the past 50 years would not have been possible without a parallel development of analytics-driven risk management methodologies. Analytics is the set of decision models and technologies that help lenders decide who will get the credit, how much credit will they get, and what operational strategies will enhance the profitability of the accounts to the lenders. Eventually, the application of analytics has extened to other industries where there are risks related to the consumer (for instance, fraud detection, collections, in insurance, health-care payers, hospitals, telecommunications and utilities), or businesses (for instance, credit rating of businesses).
Depending on the industry, there are several factors determine the risks related to an entity or a portfolio. Analytic Risk management models can help you identify these factors by combining characteristics across several dimensions, including customer demographics, past relationship history, past behavior, events and environmental factors.
LatentView can help you adopt an analytics-driven risk management approach across the account lifecycle from originations and acquisition to managing collections and write-offs. We build and maintain analytic models and reports that can be used to effectively spread your risks, manage by the odds and eliminate the need for judgmental assessment.
Originations. Origination models predict the probability of default or lapsation (in Insurance) at acquisition. Origination models help you decide who to accept or decline, the terms and conditions of offer.
Read more on originations.
Account Management. Behavioral scoring models help predict account behavior over the course of the account lifecycle, and help managers exert control over account usage. For instance, in a consumer lending scenario, these models help determine whether to extend the credit line, authorize a payment, grant a credit limit increase or control the balance in your portfolio.
Read more on account management.
Collections & Recovery. Collections models predict account payment behavior. These models can identify high, medium and low risk accounts, and allow improved collector targeting at a lower cost.
Read more on collections.
Risk Management
The phenomenal growth in Consumer lending witnessed in the past 50 years would not have been possible without a parallel development of analytics-driven risk management methodologies. Analytics is the set of decision models and technologies that help lenders decide who will get the credit, how much credit will they get, and what operational strategies will enhance the profitability of the accounts to the lenders. Eventually, the application of analytics has extened to other industries where there are risks related to the consumer (for instance, fraud detection, collections, in insurance, health-care payers, hospitals, telecommunications and utilities), or businesses (for instance, credit rating of businesses).
Depending on the industry, there are several factors determine the risks related to an entity or a portfolio. Analytic Risk management models can help you identify these factors by combining characteristics across several dimensions, including customer demographics, past relationship history, past behavior, events and environmental factors.
LatentView can help you adopt an analytics-driven risk management approach across the account lifecycle from originations and acquisition to managing collections and write-offs. We build and maintain analytic models and reports that can be used to effectively spread your risks, manage by the odds and eliminate the need for judgmental assessment.
Originations. Origination models predict the probability of default or lapsation (in Insurance) at acquisition. Origination models help you decide who to accept or decline, the terms and conditions of offer.
Read more on originations.
Account Management. Behavioral scoring models help predict account behavior over the course of the account lifecycle, and help managers exert control over account usage. For instance, in a consumer lending scenario, these models help determine whether to extend the credit line, authorize a payment, grant a credit limit increase or control the balance in your portfolio.
Read more on account management.
Collections & Recovery. Collections models predict account payment behavior. These models can identify high, medium and low risk accounts, and allow improved collector targeting at a lower cost.
Read more on collections.
