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Malaysia Bank Adopts Artificial Intelligence Early Warning System to Reduce Risks of Non-Performing Loans (NPLs)

The client is one of the largest international banks, headquartered in Singapore with a prominent presence in the Asian region. As a Financial Institution with significant focus on commercial loans, the challenge of managing credit risk from loans turning delinquent is pervasive and a major concern to the bank. With a clear understanding that high NPL ratios demand greater loan provisions, which reduces capital resources available for lending and dents the bank profitability, the Bank decided to embark in this journey to mitigate the risks of NPLs.

The Bank was using manual excel-based spreadsheets to forecast potential delinquencies based on historical data and repayment behaviors. This manual process was labor intensive, time consuming, lacking futuristic prescriptive analytics modeling and its precision was questionable. Scalability of analysis was a constant challenge with changing economic climate and trends.

Pounded by these challenges, the Bank realized its need for an automated and intelligent solution with the capability to provide early warning for delinquent accounts.

Solution

With a significant double-digit increase in the number of approved loans, the Bank prioritized its focus on effective management of loans recovery and delinquencies. The Bank realized the need for automation coupled with deployment of Artificial Intelligence (AI) instead of the labor intensive manual processes which lent a toil on the credit management teams.

The conventional CRISP-DM (Cross Industry Standard Process for Data Modelling) breaks the process of data mining into six major phases of which the sequence of the phases is not strict and moving back and forth between different phases is always required. This conventional model usually requires disparate tools and trained statisticians to navigate usage of these tools for data mining.

Juris Technologies has taken a distinctive forward-looking approach in bringing Machine Learning to the next level.  Leveraging design thinking and embedment of wizards, the business users are empowered with the power of machine learning and artificial intelligence to apply their own domain knowledge and hypothesis in training the different analytical models.  By empowering business users, organizations reap the benefits of significant improvements with the capabilities of continuous training of analytical models.

The Bank engaged Juris Technologies, an end-to-end broad spectrum customer and credit management solutions provider to automate workflow and processes for loans management. With precise understanding of the Bank’s need, Juris Technologies proposed and delivered the Juris Mindcraft solution, a system powered by Artificial Intelligence capabilities, to predict potential Non-Performing accounts as early as 6 months prior to delinquency.

Juris Technologies utilized the Bank’s readily available data, consolidated various attributes of Term Loan, Trade and Overdraft services of accounts, and applied Artificial Intelligence prescriptive models. These models combined historical accounts behavioral analysis with future predictive analytics and algorithms to identify and segregate accounts potential of deterioration to NPL status. In addition to analytics, the solution also provided the Bank’s users with insights, rationale and rules for the identification of such accounts, enabling strategic and tactical actions to be deployed in managing and reducing NPLs.

Benefits Obtained

Combining the capabilities of the Bank’s proprietary Credit Scoring Model with Juris Technologies’ early warning and account monitoring system, the Bank successfully enhanced its existing credit assessment structures and risk assessment capabilities. Coupled with improved economic climate, the Bank was able to reduce NPLs significantly from a sharp hike to a plateau.

With reduction in NPLs, the Bank enjoyed increased profitability and improved their ability to provide new lending and a healthy working capital.

Industry: Banking

Big Data Analytics Solutions ProviderJuris Technologies is a Malaysia-based, MSC Status company providing innovative business solutions in the financial services and telecommunications industry.

Juris Technologies started business operations in 2003 with a primary focus in building solutions serving the Banking, Financial Services and Insurance (BFSI) and Telecommunications industry. Our solution consists of an integrated framework of scalable components which is used to build enterprise quality solutions.

Our solution framework is used to design and develop solutions for customer relationship management with modules such as Contact Management, Campaign Management, and Sales Force Management. In the areas of Credit Management, we provide solutions for Customer Acquisition, Loans Origination, Credit Scoring, Conveyancing and Litigation, and Collection and Recovery. Today, we are the leading customer and credit management solutions provider in Malaysia, offering a collaboration platform for over 1,000 external parties including legal firms, collection agencies and valuers.

Our key clients are Affin Bank, Agro Bank, Alliance Bank, Bank Kerjasama Rakyat Malaysia (BKRM), Bank Persatuan, Bank Simpanan Nasional, CIMB Bank, CTOS, Hitachi Capital, HSBC, JCL, Maybank Etiqa, OCBC Bank, SME Bank, Standard Chartered Bank and Tenaga Nasional Berhad (TNB) Malaysia.

Our global footprint for the licensing of Juris Application Server spans across 22 countries and  the Juris Application Server framework is used by organizations such as Sony USA and The Software Engineering Institute of Carnegie Mellon.

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