Credit score speeds up the PROCESS Significantly t
organisations where decisions are driven by data and actions are optimised for the greatest return using predictive analytics.
Our subject matter expertise spans Strategy, Pricing, Credit Risk Management, Marketing and Sales Analytics. By harnessing the power of proprietary credit bureau data, Qarar has built a tangible advantage and offers a suite of industry leading technical solutions that can unlock the true value and power of information. can make rapid and reliable decisions. Credit scores can also help consumers to understand where they stand financially in several ways.
As times change, newer methods of credit scoring have emerged, for example social media scoring. These alternative methods offer particular benefits to consumers including under-banked, thinnerfile individuals, or those living in countries with limited credit bureau data. As credit scoring evolves, loans are becoming easier for consumers across the world to access, as while also posing less of a risk for banks and lending institutions.
A: Social media profiling is paving the way for alternative credit scoring data, and can be applied to customers of all types, including both older and younger clients. Today, loan applications and credit card enquiries essentially hinge on one thing: a credit score. Traditionally, institutions have asserted that an individual’s financial history, which primarily includes their payment history, current debt profile, and length of credit history, informs future behaviour and therefore should dictate the decision over whether to offer credit to potential borrowers and at what rate. This framework makes sense when the necessary information is available, but what about when it is not? In cases where a payment history is lacking banks do not have enough information on which to base credit scores. As a result, taking out a loan is virtually impossible for consumers, which puts them at a severe disadvantage.
Lenders need a way to verify creditworthy individuals when they do not have access to localised credit histories. This is particularly true in GCC countries like the UAE and Saudi Arabia, where vast portions of the population are highly transient or expats, and would otherwise never have access to financial services due to limited credit bureau data. In this situation, big data credit scoring like social media profiling can assess borrower risk and default probability.
Alternative approaches to traditional credit scoring can also be used to assess thinner-file borrowers such as students, foreign nationals, and populations of under-banked individuals. This big data scoring includes data from social media, bank transaction data, cellphone data, mobile data, bank and lender data if available, as well as third party data hubs of personalised, internationally standardised and verifiable data that can be easily packaged for lenders. The analysis of this data helps lenders to increase approval and conversion rates, and offers borrowers better access to financing. It also allows lenders to perform user-permissioned checks on borrowers based on social media and online footprints, IP verification, and browsing history analysis.
Customer data has always been a central decision-making factor for financial institutions, because bankers make lending decisions based on credit scores while insurers might look at driving records or require health checks before issuing policies. But as people and their devices become more interconnected, new streams of granular, real-time data are emerging, and with them innovators who use that data to support financial decision-making. Your social media profile speaks volumes about your lifestyle and creditworthiness. Friendlyscore, for example, conducts in-depth analyses of peoples’ social networking patterns to provide an additional layer of data for lenders trying to analyse the credit-worthiness of a borrower.
A: Risk management in banking has been transformed over the past decade, largely in response to regulations that have emerged following the global financial crisis and the fines levied in its wake. Important trends are afoot that suggest risk management will experience even more sweeping change over the next decade. The change expected in the risk function’s operating model illustrates the magnitude of what lies ahead. Today, about 50 percent of the function’s staff is dedicated to riskrelated operational processes such as credit administration, while 15 percent work in analytics. Mckinsey research suggests that by 2025, these numbers will be closer to 25 and 40 percent, respectively.
The fundamental trends do permit a broad sketch of what will be required of the risk function of the future. The trends furthermore suggest that banks can take some initiatives now to deliver short-term results while preparing for the coming changes. By acting now, banks will help risk functions avoid being overwhelmed by the new demands.