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Mitigating Business Risk Through Credit Risk Analytics

With growing regulation surrounding credit risk analysis and responsible loans within the B2B and B2C industries, it’s never been more critical that business have the software and expertise in place to effectively manage their decision making. And these days, meeting regulation is no longer enough to safeguard your business’ future – you’ve got to go beyond.

Let’s go back to basics…

We all know that effective credit risk analytics demands the balance of business capital against customer payments against loans. Credit risk itself assesses the potential that any outstanding debt won’t be repaid. Clearly, if this decision is founded upon limited insight, businesses run greater risk of loans not being repaid. It’s important for the ongoing success of any business that offers credit to customers that this risk is mitigated through the introduction of more informed decision making. With clearer insight, business can make better-educated decisions regarding key considerations, such as:

  • Value of loan to offer a prospective customer
  • Customer propensity to repay the loan
  • Interest rate to charge
  • Any suggestion of potentially fraudulent activity?

What with all these ongoing changes in the industry, increasing numbers of banks, financial services, retailers and telecoms providers are looking to overhaul their credit risk analytics. Remember, responsible loans don’t only benefit the recipient but you as a business. After all, if you offer an individual a loan that they can’t afford to repay, you’ll lose out too…

So, what challenges do business face when analysing credit risk?

  1. Disparate data sources making it difficult to generate a Single Customer View (SCV)
  2. Diverse modelling techniques across teams, making it difficult to collate insights for a clearer understanding of individuals, customer types and business service demands
  3. Labour-intensive, inefficient modelling that duplicates effort and makes repeatability a challenge. This also limits transparency and auditability if models are constantly changing
  4. Ineffective credit risk tools. Different businesses have different requirements. If your solution doesn’t exactly meet the demands of the team and the business as a whole, you’re likely to miss out on important insight.

Want to see credit risk analytics in action?

Read our customer case study to discover how their solution is projected to save them £160,000 over three years.

Read the case study

Another Amadeus customer wanted to ensure the ongoing health of their credit risk platform, which was critical to ongoing business productivity. Discover how a support contract with Amadeus has ensured optimal platform performance and expert support on demand.

Read the case study

Speak to the team

Get in touch with our expert team today to understand how to overcome those challenges currently holding back your credit risk analytics and jeopardising business profitability.