Post-loan: The era of AI robots

Transformation Overview

At present, consumer finance companies use measures such as collections scoring models, intelligent outbound calling, and robot-assisted collections in post-loan collection processes, gradually shifting from past passive responses to proactive service.

◎ Intelligent collections account for 80% and even more than 90%

Statistical results show that more than half of institutions indicate that intelligent collections have already taken a dominant position throughout the entire collections cycle. In particular, AI intelligent robots can independently handle tens of thousands of collections calls.

◎ Intelligent collections methods are becoming more diversified

For specific intelligent collection approaches, collections scoring models, intelligent outbound calling, and robot-assisted collections are the three most widely adopted “go-to tools” among institutions.

◎ Clear advantages in intelligent post-loan management

Intelligent AI robots can be configured with different personas and voice tones. Based on users’ different communication needs and scenarios, they can intelligently invoke different types of robots to respond quickly to requests.

◎ Three directions for future deployment

With help from technology, deeper alignment and integration are promoted among scenario development, customer service, and business process execution.

Transformation Challenges

As the use of personal information becomes further regulated, the ability to repair and reprice information for overdue customers is narrowing, and the rate of customers going missing is rising; the market has also spawned cases involving alleged “agent rights protection.”

◎ Know and uphold the compliance boundaries for post-loan collections

The issue of violent collections has grown increasingly severe in the past few years and has become a key area for regulators to crack down on. Multiple compliance requirements have already been issued.

◎ Balancing collections cost and efficiency

Because the amount borrowed per single loan in consumer finance is small, although intelligent robot collections can to a large extent resolve the above problems, the standardization level of intelligent robots is high, and the upfront R&D cost for robots is also high.

◎ Still weak areas in human-machine interaction

Robot-based intelligent collections are already more widely adopted, but weak spots still exist in areas such as human-machine interaction—for example, the strategy configuration of intelligent collections robots still falls short compared with human collections.

◎ How to effectively transfer non-performing assets

In addition to collections and write-offs, another issue consumer finance companies must address is how to effectively transfer the non-performing assets already formed, because non-performing assets in consumer finance operations have a low average single-asset amount and are unsecured.

Breaking Through the Transformation

Internet of Things, cloud computing, big data, artificial intelligence, and blockchain frontier technologies are key elements for financial digital transformation, helping better leverage the role of expert teams in human collections.

◎ Put end-to-end credit electronic data on-chain

Some institutions are already trying to apply new technologies such as blockchain and cloud computing. In the context of overdue loan litigation, companies use blockchain evidence storage technology to put end-to-end credit electronic data on-chain, so that electronic data becomes electronic evidence. This establishes a risk prevention and dispute resolution mechanism that integrates information preservation, evidence fixation, and evidence review and determination.

◎ Continue to increase investment in technological resources

With the broad adoption of digital financial products and service models, multiple consumer finance companies say they will increase investment in technological resources. Externally, they will provide high-quality financial services with intelligent capabilities; internally, they will be driven by technologies such as big data, artificial intelligence, and cloud computing.

◎ Still cannot eliminate traditional post-loan management

In addition to methods such as robot-assisted collections, consumer finance companies will also adopt independent human collections, SMS and letter notifications, and outsourced collections. In addition, they will promote collections through court litigation and online arbitration. There are also channels such as notarization with compulsory enforcement and diversified dispute resolution (such as pre-litigation mediation by courts, arbitration mediation, and people’s mediation).

(Editor: Ma Lu YIN HF120)

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