Artificial Intelligence invests the banking sector

Today, artificial intelligence makes it possible to process an application form in 5 seconds, rather than 58 minutes. Applied to a rapidly changing banking sector, this technology has much to contribute to one of the oldest professions in the world, which urgently needs to modernise in order to better meet and retain the expectations of its customers, but also to remain competitive in the face of the growing number of fintechs. The transformation is underway.

Aoday, for the bank as for many other sectors, exploiting information has become essential: it is an invaluable resource for a financial organization. Artificial intelligence comes into play at this stage: part of the processes of semantic understanding and analysis of textual content can - and must - be handled by technologies such as AI and machine learning.

Natural language search transforms the customer experience via chatbots and intelligent question and answer forums on websites. The more accurately questions in natural language - as opposed to keyword research - are addressed, the more easily and quickly the customer is satisfied, with a humane, yet stress-free and conflict-free 24/7 service.

Because some customer categories will never switch to 100% digital, it is also possible to reduce the duration of after-sales calls by providing intelligent assistance to agents. The consequences are immediate: on the one hand, costs melt away and call center performance is optimized, and on the other hand, customer satisfaction grows strongly.

 

Multi-channel analysis of the customer's voice can be used to identify areas of customer interest or potential customer attrition. It also enables effective corrective action to be taken when problems are detected and to pick up weak signals that can feed into the Group's marketing strategy during the redesign phase of its product and service offerings.

This recognition by AI enables a real revolution in the user experience as it exists today. This dynamic is leading us towards a new type of 'client-bank' proximity relationship where the permanent link is no longer reserved for online banks alone, but democratized to all banking institutions. Or how to compete with these fintechs while modernizing its image?

Deployed in the service of economic and marketing intelligence, AI can be a real asset for banks, in particular by enabling them to build a 360° vision of their customers. To do this, artificial intelligence can monitor the web and social networks in order to assess the e-reputation of an institution or analyze the verbatim and emails reported by agencies in order to qualify the customer relationship and measure the associated satisfaction rate. It can also be a tool of choice to achieve a more competitive reaction time in the processing of customer returns. This monitoring must also be part of benchmarks: it is nowadays a key tool to study products and services, the type of communication or even the customer relationship mode adopted by challenger establishments, and to adapt its strategy accordingly.

 

Moreover, the assistance of artificial intelligence can be a concrete asset in reducing operational and contractual risks, particularly in the context of the fight against money laundering. Indeed, by analysing, according to defined rules, signed contracts in order to deduce an associated risk rate in the context of an investment or a loan for example, AI can compress the investigation time required by reducing it from several weeks to a few minutes! Semantic Artificial Intelligence can thus provide an almost instantaneous response thanks to the analysis of data from various private and public sources. Exposure to risk can thus be reduced.

At present, the bank could benefit from reducing the time it takes to process applications. Indeed, reports such as theft/loss of bank cards or claims must now become automated processes to improve productivity and optimize costs. IA assistance can also simplify internal processes such as recruitment: by automatically analysing and cross-referencing published job offers and received applications, it is now possible to speed up the detection of relevant applications and thus accelerate recruitment.

Among all these processes, the interest of artificial intelligence is the drastic reduction in the processing of files, which can approach 50%. Indeed, the documentation received by banking institutions, especially those with insurance offers, requires time-consuming and costly analysis that can be detrimental to customer satisfaction. Today, AI makes it possible to extract the important information contained in a claims file, to analyse the type of damage in question, and to understand whether or not it is covered by the insurance policy. The relevant data can then be imported into a claims database, thus helping agents to trigger the appropriate compensation process. However, the AI is not intended to deal with these sensitive files: it must assist the decision-making process by diagnosing the percentage of risk that can then lead to a human decision.

 

By investing in the banking sector, Artificial Intelligence allows the tedious work of understanding context to be shifted to technology so that the agent can concentrate solely on value-added tasks. Reducing human errors, speeding up response time and customer satisfaction: AI is there to assist the agent in his decision making by identifying possible inaccuracies, the risks of fraud, and by optimising the ratio between profit, profitability and customer satisfaction.

 

Alain BiancardiVice President Sales, Expert System France