With artificial intelligence (AI) powering the financial industry, more opportunities are being created for financial institutions to serve their customers better, grow their market share, personalise product offerings, and achieve higher revenue rates at lower costs. Financial institutions that transition to adopt new digital channels can access larger and richer data sets to fuel advanced analytics and machine learning decision engines. With the help of using these decision-making capabilities powered by AI, financial institutions stand to hold a stronger competitive edge giving more incremental value to their customers, especially in the momentous growth of competing in global and regional markets.
Artificial intelligence can be a significant resource to financial institutions, especially in lending where they can expedite the process of hundreds of thousands of customer applications coming in. However, traditional financial institutions today still face challenges to cater to these applications due to prevalent manual functions that are both time-consuming and can opt to error lead decisions from human biases. An AI platform like Juris Mindcraft serves as a one-stop solution for all financial institutions’ problems, that uses data mining and machine learning capabilities to speed up the entire loan origination process. This includes functionalities from reducing loan approval times and quickly reviewing customer credit history to predicting customer behaviours in the likelihood of potential defaulters.
Let’s dive a little deeper into some of the use cases of Juris Mindcraft and how it can efficiently improve your lending process.
Identifying credit default risk when scoring customers
The COVID-19 crisis has triggered implications for managing and mitigating credit risk. The risk of loss arising from a borrower’s inability to pay its loan obligations in full or on time on any material credit obligation may impact all credit-sensitive transactions, including loans, securities, and derivatives. Hence, the ability to accurately identify credit risk during the scoring and loan approval stage is a huge challenge.
Juris Mindcraft uses Machine Learning modelling as a basis to better predict the potential risk and likelihood of a current loan defaulting. Its AI-based algorithm helps crunch huge quantities of customer data in a few seconds to verify the customer’s creditworthiness and determine whether to grant a customer a loan. Juris Mindcraft enriches the credit risk management process by reducing time-to-market and ensuring accurate credit scores.
Utilising alternative credit scoring for the credit-invisible customers
In traditional financial services, only those who are in the credit system will be given access to loans. However, people outside the credit system such as the unbanked, unserved, or underserved market would not qualify to access such services. This is because financial institutions have no way of assessing their customers’ creditworthiness due to the lack of credit data/history.
Juris Mindcraft’s machine learning model takes into account non-traditional data sources such as financial transactions, web traffic, mobile devices, and public records that can be used to assess the creditworthiness of an individual or a business without a credit history. Financial institutions can leverage alternative data to expand their services to credit-invisible customers to increase market reach. This more granular and individualised approach also allows banks and financial institutions the ability to more accurately assess each borrower and allows them to provide credit to people who would have been denied under the traditional scorecard system.
Predicting the next best action
Industries have come to realise that every customer journey is unique. The challenge for origination officers is to find the right set of actions for an individual that will move them to the next step in guaranteeing a loan.
Juris Mindcraft recommends the next best actions to origination officers enabling them to make faster, more accurate, and automated decisions backed by data insights. Ultimately, Juris Mindcraft helps officers to build more meaningful interactions, take corrective actions, and make offers that actually meet customers’ needs.
Juris Mindcraft analyses the creditworthiness of customers. For credit-worthy customers, Juris Mindcraft will suggest officers to approve applications while for customers who are not credit-worthy, Juris Mindcraft will suggest officers to ask them for a bank guarantee, for example.
The rapid improvement of AI-powered technologies can be a tremendous resource to financial institutions. AI’s automation capabilities to strengthen the lending process give room for loan origination officers to focus more on complex issues that offer strategic value to internal and external stakeholders. Artificial intelligence is no longer just an option to consider in the lending industry, but the only truth that lies to be seen for financial institutions that are determined to remain competitive and relevant in the industry.
With a growing demand for financial products, it is imperative for financial institutions to be able to constantly cater to customers’ needs, offering personalised experiences while automating the user journey to maximise the lifetime value of every relationship while reinforcing market leadership.
Interested to learn more about Juris Mindcraft and how you can automate your lending processes, connect with our team today at email@example.com
JurisTech (Juris Technologies) is a leading Malaysian-based fintech company, specialising in enterprise-class software solutions for banks, financial institutions, and telecommunications companies in Malaysia, Southeast Asia, and beyond.
Juris Mindcraft is an artificial intelligence (AI) platform that uses advanced machine learning (ML) techniques to build powerful AI models.