Analysis of the three major pain points in the collection industry and the four major advantages of ArcelorMittal Intelligent Collection

There is a saying in the financial industry that "one-third of the loan is divided into seven parts for management." In the process of "management," collection is an indispensable part. Some people say that collection is the "scavenger" of the financial market. ArcelorMittal assists collection agencies in legal compliance and intelligent collection.

Traditional collection methods are mostly labor-intensive, with large personnel turnover, high recruitment pressure, and rising labor costs. The supervision on debt collection has become increasingly strict, and industry self-discipline has also made debt collection more standardized. This has reduced the sense of identity of debt collection practitioners who have "first seen the light" and further increased the staff turnover rate. Some practitioners in the industry said that they "go home during the New Year. When relatives asked me what I did for a living, I was too embarrassed to say it was debt collection, so I could only tell him euphemistically that I was in finance."

The lack of recognition among practitioners and the sharp drop in collection rates have forced collection practitioners to leave one after another and look for a brighter path. In this current industry situation of lost people and low recovery rates, the intervention of artificial intelligence has subverted the traditional collection methods and helped improve the efficiency of collections.

Many years ago, when people in the online lending industry talked about artificial intelligence collection, many people (especially collection companies) felt that it was unrealistic and that its practical application was very far away. In the past two years, the development of artificial intelligence technology and the needs of financial market users have simultaneously promoted the development of intelligent collection robots. When various types of intelligent collection robots have sprung up on the market, many people have panicked and machines have replaced manual labor. The time may have come.

Collection was originally a little-known industry. Traditional collection companies generally focus on banking and credit card business. With the rise of Internet finance, especially the large number of overdue cash loans, the market has become more and more concerned about collection. The demand has increased several times. The lowering of the threshold and the substantial increase in demand have led to the rapid development of the collection industry. Since the traditional collection industry is a labor-intensive industry and is limited by time, location, weather and other factors, companies in order to control costs , most of them rely on telephone collection. Telephone collection is currently one of the most effective methods in China.

Three major pain points in the collection industry

1. Low efficiency and a lot of labor being wasted.

There are statistics in the online lending industry. Assuming that the effective working time in a day is 7.5 hours, and a collector makes a phone call in the traditional way, the real effective time is only 2 hours, and a lot of time is wasted in invalid dialing. People in the online lending industry said: Due to the particularity of inclusive finance, traditional collection methods have gradually been unable to meet market demand, and the industry urgently needs to explore new collection methods to meet urgent needs. In the era of Internet consumer finance, user reminders need to be more timely, and overdue phone collection calls also need to be more efficient.

2. The demand for post-loan business is huge and it is difficult to fully cover it.

Due to the sinking of Internet consumer credit service users and the expansion of the coverage of the population, the number of users has increased exponentially compared with traditional finance, and there are higher requirements for telephone collection efficiency. Faced with a steady stream of overdue persons, improving collection efficiency is key.

3. On the premise of compliance, using the traditional model to collect collection costs will increase.

Due to the rapid expansion of consumer finance and other businesses, there has been a huge shortage of personnel in the collection market, and personnel costs have doubled. Recruitment has become the primary issue for many companies; the core goal of artificial intelligence is to reduce costs and save manpower, which is in line with the current situation. Trend; Financial industry insiders pointed out that from the test results, the collection rate of consumer loans and credit loans using artificial intelligence combined with intelligent collection can reach 50-60, which is 13 percentage points higher than the purely manual collection method.

Four major advantages of artificial intelligence collection:

1) Strategy, model, and case division. Build a model through data, design a collection strategy through the model, and set case division rules through the strategy. Each module is interconnected;

2) Outbound call system. Including automatic outbound calls and manual outbound calls. The automatic outbound calls and automatic docking system import data to make regular outbound calls and text messages, and at the same time, manual outbound calls are made.

Manual outbound calls need to carry out customer portraits and remind collectors of relevant speaking skills, etc.;

3) The reporting system can realize real-time business monitoring and early warning according to authority and needs, and realize manpower deployment decisions;

4) Auxiliary systems to realize intelligent, batch-oriented and compliant services such as SMS and quality inspection.

Anmi Intelligent Collection System (www.anmiai.com) processes the basic information of each collection case and uses algorithms, big data and other technical means to complete interpersonal network analysis through the knowledge graph. Find the relevant person through public information and obtain the priority contact number. Then, based on different overdue account ages and different user portraits, AI will automatically analyze the best words and communication strategies in history. Finally, the machine will automatically simulate the completion of voice or text message collection and generate a disposal Report, proceed to the next step of processing according to the recall situation, case closure, manual intervention, etc.

With the empowerment of artificial intelligence, collection methods will transform from labor-intensive to technology-intensive. Driven by big data and artificial intelligence, they will become increasingly transparent and standardized. With the expansion of the financial market, instrumental, systematic, and batch collection methods may become the industry trend in the future.