Debt Collection with Predictive Analysis
Debt Collection Use Case
Debt collections is one of the most complex portfolios in the BPO industry. It needs multiple KPI iterations to recover lost revenue and each iteration impacts recovery margin. Intellicus debt collection analytics solution is enabling BPOs to optimize debt collection processes strategically. With business intelligence and analytics, BPOs are implementing data driven strategies to curb debts and enhance overall portfolio performance.
The use case is for debt collections for an Outbound BPO.
Business Challenge: This ﬁnancial institution was looking for ways to optimize their debt collections operations. They lacked visibility into their data and were constantly failing to gauge the real impact of a derailed debt collection process.
Intellicus provided them with a single source of truth with a 360-degree assessment of their business. Intellicus helped them build dashboards to perform portfolio and risk assessments to assess risk vs opportunities. With machine learning based analytics, Intellicus helped them derive predictions on probable outcomes. Intellicus also provided them deeper insights into their agents’ performance with the ability to analyse, listen and rate even a single call right from Intellicus dashboards.
Portfolio Insights Dashboard
This dashboard gives an overview of how the portfolio looks today. Its key components include:
Contact View – It provides insights into reachable and non-reachable contacts.
Age Bucket – Age bucket provides customer age in 3 buckets i.e. 21-30, 31-40 and 41-50 (in years). The signiﬁcance of this view is to strategize the account level approach and customer reach based on the count of each bucket.
EMI Category – EMI Category reflects the customer segmentation basis the principal outstanding of
- Low Balance – Deﬁnes customer with the lowest principal outstanding.
- Medium Balance – Deﬁnes customer with medium-range principal outstanding
- High Balance – Deﬁnes customer with highest range principal outstanding
The EMI Category helps target the right high paying customer based on factors like how frequently the customer paid the debt etc.
Employment Split – Segregation of customer segment basis the employment status. Salaried customers are prone to pay sooner as they have a recurring income and the best time to connect with them is probably around salary credit days.
You can ﬁlter the portfolio data as per the required KPIs. Here we have used KPI ﬁlters like:
- Duration of Credit – This is a critical KPI to measure the customer tenure with the product for debt collection portfolio. The KPI helps to prioritize the accounts basis loan tenure and reduce non performing asset (NPA) impact.
- Risk Score View – This KPI helps segregate the customer into risk categories. Risk score is KPI to strategize the approach for each customer. Below are the deﬁnitions for the risk score:
- Low Risk – Highest propensity to pay
- Medium Risk – Medium propensity to pay
- High Risk – Lowest propensity to pay
Risk scorecard enables the strategy for customer approach and bifurcates the approach basis 3 broad categories that is:
a. Location – Identify in which region or city do you have the maximum outstanding and which areas have the probability of fastest recovery.
b. EMI Balance Bucket – Categorization of the collectable amount in pending EMI range of Low (200 K – 350 K), Medium (350K-450K), High (550 K and above). This will give you insights on how many accounts do we have with a pending balance of 200 K or others.
c. Delinquency Bucket – Filter accounts and people based on their payment pattern that is 3 signiﬁes the debts weren’t cleared for more than 4 months
Risk Analysis Dashboard
Gives an overview of what is the risk in the portfolio for debt collection, it provides predicted outcomes based on various factors.
The dashboard helps draw conclusion on the portfolio performance based on the predictions of what is the expected recovery from the portfolio in terms of Principal Outstanding Sum (POS) resolution, Expected Collectible EMI, Expected EMI Loss, and Expected POS loss.
Risk vs. Actual Dashboard
This dashboard gives a comparison of the predicted collections versus the actual amount collected. The comparison is given for all the KPIs covered in this solution. It gives an indication of how effective the recovery strategy was and the overall performance of the portfolio on actuals as compared to the predicted values.
Call Details Analysis
In-depth analysis of all the calling activities on different KPIs in the portfolio. From number of calls made to their duration, disposition and quality, everything can be ascertained from this report. Get complete flow of actions on a given account number in a single click. How many attempts were made, what was the disposition, what was the customer response etc. can all be viewed here. It also gives immediate access to call recordings of each case, that can be leveraged by the QA and training teams for agent evaluation and feedback.
Employee Performance Report
Heat map analysis of employee performance on the portfolio. Cumulative Gross Performance Analysis (CGAP) method-based ratings created for employees based on KRAs like Call Count, Promise to Pay (PTP) Resolved, PTP Amount etc. From manager level, you can drill down team and then to agent level and see how calls and escalations.
Intellicus debt collections use case automates all processes associated in collections life cycle, from data management to last level customer interactions. It enables an aggressive, proactive approach of debt collection while ensuring optimum operational efﬁciency.