Lending Enterprises- like any other business organization- are driven by the objective to boost their revenues. Regulators play an important role in balancing this objective by ensuring that the customer interest is not sidelined. Lending organizations must have a customer-centric approach towards acquiring and retaining customers if they wish to have an edge over competitors. To do that, lenders need to adopt Artificial Intelligence (AI) and digital technology to significantly enhance operational transparency for customers and proactively understand their needs to provide hyper-personalized solutions.
FinXEdge Lend uses AI to enhance customer experiences, predict and prevent customer churn and better channel management. Here are a few ways how:
Predictability in Loan Closure Timeline
In last two decades, we have witnessed numerous claims of shortening loan funding cycle time from days to hours to minutes. In practice, a large portion of such loan applications are funneled through exception and do not meet the claimed SLAs. A significantly more pragmatic approach for customer-centric lenders would be to use Machine Learning (ML) to predict the closing cycle time and let the customer know upfront if they can be fast-tracked or not. In addition, complete transparency can be ensured by progressively predicting the remaining time to closure.
Incentivizing Quality Over Quantity
According to the U.S Department of Labor, the cost of hiring is approximately 30% more than the employee’s annual earnings. Assuming the annual compensation for a Loan Officer(LO) is $90000, the cost of hiring one will be about $30000. This loss is significantly higher when a star performer resigns. There is a need to create an objective way of measuring the LO’s performance based on the quality of loans (risk to default) that they can convert.
Creating a framework that links the performance of the channel to the forward-looking quality of the loans can help lenders in:
- Enabling lenders to create value-based pricing for the channels
- Enabling regional managers to align sales investments based on the channel performance prediction in their region
Valuing the High-Value Customers
LOs traditionally focus on converting as many leads as possible. There is no way to differentiate leads based on either the risk of rejection or the risk of customer fall out. This might result in a high rate of rejection or worse, higher downstream risk of default. With FinXEdge Lend, there is a defined framework that helps LOs to prioritize valuable customers who have a high risk of fall out.
Hyper-Personalization of Solutions
FinXEdge Lend helps in personalization to the customers, so that they are not just offered an off-the-shelf loan, but a well-thought-through, customized solution.
- Lead Assignment – ML and text analytics are used to match the borrower profile with the skills of the LO to improve chances of conversion and enhance overall customer experience
- Product Recommendation – ML algorithms ensure that the recommended product has the highest match with the specific needs of customers. This reduces the risk of fall out at a later stage.
Adopting Effective Marketing Strategies
FinXEdge insights combine the historical trends of the performance of the region, channel and product along with the projections for the next quarter. This helps sales teams to realign their marketing investment on strategic products and channels.
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