SENTIENT Case Study

Financial Solutions Provider Cuts Losses and Improves Approval Rates

Customer

Financial Solutions Provider

Industry

Banking & Finance

Function

Loan Approval, Credit Risk

Problem

Financial solutions provider seeks to reduce the losses associated with underwriting and loan defaults while improving the approval rate for loans.

Solution

The company managed to develop an ML predictive analytics engine with NLP capabilities to ascertain the risk of approving certain loan applications. This solution was complimented by existing underwriting methods to aid lenders in application processing.

Result

The company reported 33% decline in losses while improving approval ratings by 14% for borrowers; yielding substantial savings overall. The company was also more efficient at ordering risk across all types of borrowers, and provide clear explanations for the reasons for loan approval or denial.

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2263, KAUST Tech Park Headquarters, 

4700 KAUST, Thuwal, Saudi Arabia 22935

Contact

Call : +966 54 312 3734

Email : info@unitx.tech

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ممتاز

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ممتاز

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أدخل معلوماتك للحصول عليها الآن

ممتاز

استلم الورقة البيضاء المجاني حول حلول الذكاء الاصطناعي للتمويل

اتصل بـ info@unitx.tech لمعرفة المزيد

ورقة بيضاء مجانية

أدخل معلوماتك للحصول عليها الآن

ممتاز

استلم الورقة البيضاء المجاني حول حلول الذكاء الاصطناعي للتجزئة

اتصل بـ info@unitx.tech لمعرفة المزيد

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