ARTIFICIAL INTELLIGENCE AND BANK-CUSTOMER RELATIONSHIP MANAGEMENT
1. Introduction
With the advent of the fourth wave of digital transformation, the traditional bank is facing new forms of competition from new players such as Neobanks and FinTechs.
This leads the traditional bank to have to rethink the management of its relationship with customers in order to be able to meet new requirements, improve the quality of its services and this by developing in particular the concept of “Augmented Customer Advisor“, concept which will be described below.
2. The relationship Manager
Traditionally in retail banking, the Customer Advisor is the first vis à vis of the customer with his bank.
Indeed, his main missions are to detect the needs of his clients, to advise them in terms of investments and financing, to analyze credit applications and assess the risks, to prospect for new clients and more generally to monitor his portfolio.
So many missions that require several skills on his part:
- In terms of knowledge: having a good knowledge of marketing and communication techniques, having a good general economic and financial culture, understanding the local economic fabric, also knowing the security instructions for assets and people.
- In terms of know-how: anticipating customer needs, detecting financial risks and providing an appropriate response to expectations, conducting and concluding a sales meeting, carrying out a prospecting process.
Added to this is the need to have a sense of initiative, to know how to make decisions, how to adapt, listen, analyze, synthesize and convince.
3. The added-value of the Artificial Intelligence
Evolving towards an “Augmented Customer Advisor” now means providing him with a certain number of tools using artificial intelligence to enable him to optimize the customer relationship and the act of sale, to free himself from basic requests, to automate repetitive tasks without real added value, to provide more relevant answers more quickly and to improve the analysis and monitoring of his business. Artificial intelligence is a technology based on the development of computer programs that engage in tasks requiring complex mental processes and which increase the productivity of the Customer Advisor at several levels such as:
- Reducing the time spent on KYC: this involves reducing the burden associated with time-consuming and low-value tasks by digitizing, for example, the process of entering into a relationship (RPA: Robotic Process Automation)
- Automating responses to simple customer requests through intelligent conversational assistants (ChatBot) that generate a conversation with users, adapt to new trends and increase business efficiency.
- Diagnosis assistance: this involves, for example, automating the credit granting process (Credit Scoring) and calibrating pricing conditions according to the customer’s risk profile (Risk Based Pricing).
- The prioritization of the actions to be carried out thanks to the generation of alerts: this involves, for example, rationalizing the daily activity of the Customer Advisor on the basis of an intelligent To Do List allowing him to prioritize his tasks and manage his interactions with other departments of the bank.
The use of Artificial Intelligence also allows the Customer Advisor to improve his knowledge of the customer thanks to tools such as:
- Predictive analysis which allows more effective targeting of commercial offers, anticipation of foreseeable events having an impact on the financial health of the customer and the proposal of the most appropriate solutions.
- Behavioral analysis which allows tailor-made customer assistance with an anticipation of his reactions, a proposal of personalized services in real time on the basis, for example, of an analysis of the customer’s navigation (frequency of connection, number of pages consulted …).
This is based on statistical learning (Machine Learning) which makes it possible to process and analyze a large flow of data, extract actionable information and identify common questions/answers.
- Semantic analysis which makes it possible, via automatic language processing, to facilitate the understanding and use of customer verbatim statements, to detect the levers and obstacles to customer satisfaction and to process customer reactions.
- The analysis of the tone which makes it possible to understand the feelings and emotions conveyed by the customers. (NLP: Natural Language Processing)These different applications of Artificial Intelligence result in providing the Customer Advisor with an augmented CRM tool with multiple benefits for both him and his client.
The main benefits for the customer being:
- More autonomy: the client is more autonomous and better guided in his contact process with his Customer Advisor (Concept of “Self Care“). He has a better knowledge of his financial situation which improves his decision-making.
- More accessibility: better customer experience with a simple, digital and transparent journey. Optimization of the customer journey thanks to real-time monitoring, real-time access and 24/7 availability.
- More personalization: creation of innovative offers by type of customer thanks to the data collected.
The Customer Advisor also derives several advantages:
- Better productivity: reduction of the contact time lenght with the customer. Quick identification of the documents required for subscription. Secure collection of customer data.
- Better customer knowledge: analysis of customer banking behavior. Heritage vision and understanding of needs. Increased accuracy of default risk prediction
- Better knowledge of products and markets: Analysis of offers in a more relevant way and proposal of the best possible solutions.
4. Exemple for illustration
By way of illustration, augmented advice at Société Générale (SocGen) takes the form of three aspects:
- Day-to-day banking with the aim of providing quality service and an online experience close to that offered by neo-banks,
- Asset allocation
- Investment advice with an innovative “My Heritage”* solution based on a 360° vision of the client which purpose is to:
- Aggregate the client’s financial and non-financial assets as well as its liabilities (loans) held within SocGen as well as within other banks to build an exhaustive view of its assets.
- Give the customers secure access from their internet space or on their smartphone, via the SocGen Application
- Generate a report allowing the client to understand the behavior of his portfolio in the short and medium term and to estimate the potential gains or losses according to the different investment scenarios.
The results can be shared by the client, on his initiative, with his Relationship Manager if he wishes to discuss the asset allocation strategy.The bank is also experimenting with various tools such as:
- Speech-to-Text to assist the Advisor in formalizing his customer meeting reports.
- The Robotic Process Automation (RPA) tool to automate KYC analysis based on internal IS data. This is to reduce processing times and operational risks.
- The Optical Character Recognition (OCR) and Natural Language Processing (NPL) tools that will identify weak signals in order to prevent the leakage of outstandings before it occurs.
This has resulted in a positive impact on customer satisfaction thanks to increasingly precise profiling based on better use of customer data, finer segmentation, increasingly differentiated offers according to customer profiles. Added to this are new modes of communication (videoconferencing, instant messaging, online appointment booking, etc.) and Machine Learning algorithms will make it possible to better anticipate customer attrition and their needs by taking into account their behaviours
5. The challenges of the use of Artificiel Intelligence
In conclusion, technology is certainly an essential tool for the Customer Advisor which allows a global vision of the customer, improves the commercial and marketing performance of the bank.By dematerializing end-to-end customer processes, banks allow customers to handle less paper and carry out as many transactions as possible themselves.The integration of connected mobile devices into daily life has reduced the distance between individuals and created a virtual world where it is possible to communicate and constantly learn.Social platforms are increasingly present in the professional and personal lives of customers. Social networks are an essential part of the advisor’s toolbox today.Robots will be more and more efficient to hold a quality discussion in front of a client. The question therefore arises of the threat to jobs in the banking sector, knowing nevertheless that the advent of artificial intelligence also generates the appearance of new professions oriented towards data management in the era of Big Data.The use of solutions using Artificial Intelligence nevertheless represents many challenges for financial institutions at several levels:
- Organizational challenge: the client must be accompanied and well informed, hence the necessary balance between the physical presence of the Advisor and the digital means used. One of the organizational challenges is to define the aspects of the job that really require having a “flesh and blood” Advisor. The physical Advisor remains fundamental thanks to his contribution of confidence and expertise. Financial institutions must therefore work on defining a model combining physical and digital relationships.
- Human Resources Challenge: have an advisor who has the necessary technical knowledge (financial and digital) as well as a certain number of soft skills (knowing how to explain, listen and manage stress). The training of Customer Advisors in the handling of new tools is essential, in order to develop an acculturation to new technologies and remove any obstacles resulting from changes in their profession within the framework of a “Phygital” model.
- Technological Challenge: ensure the quality and availability of customer data. Open banking promotes the consolidation of customer knowledge, particularly on means of payment. The detailed knowledge of the customer favors the personalized and adapted offer. The transformation of the distribution model of banking products/services towards omni-channel must clearly identify and understand what customers expect from their Advisor.
- Regulatory Challenge: some regulatory constraints prevent banks from taking advantage of customer data. In Europe, PSD2 Open Banking is opening up new perspectives through the possibility of exploiting bank account data.
In Tunisia, the expected lifting of certain administrative constraints (legalization of signature, certification of copies, etc.) should, with the implementation of the electronic signature, boost banks’ efforts in terms of end-to-end digitization of operations with the clientele.