Artificial Intelligence for banking

The names are the chatbot that is already implemented in banking. It is a Chatbot technology can act "as if it's"as human beings in dealing with clients. Technologies that can simulate this man known as AI and ML.

Artificial Intelligence (which is popularly called by AI) and Machine Learning (ML) is a technology that was lodged with the banking are in the digital age.

AI technology and ML is a technology before it began to be known by the banking is already widely used by companies based financial technology (fintech). Banking should be recognized a little late to respond to this technology.

Fintech already uses the technology of AI/ML to perform complex decision in banking need to involve human factors, such as credit risk, give unsecured loans to customers, as well as automatic chatbot. The Bank began adapting the AI chatbot, chatbot on the automated customer service where human beings will be served by the AI to solve problems they experienced when interacting with the bank.

What is Artificial Intelligence and Machine Learning?

Artificial Intelligence (or commonly also called AI) or artificial intelligence is human intelligence that is implemented into technology/machines. A machine is said to have an AI if it can show its intelligence mimicking human cognitive functions without human intervention.

Machine learning (ML) is a terminology that cannot be released from the AI because AI application form ML where machine learning data using statistical methods then do a job without first programmed in the past.

AI/ML in principle does not replace human workers. AI/ML is used to complete the pekerjaan2 easy and repetitive while humans can focus more to handle issues that are more complex.

On the job customer service like the example above, the AI chatbot in humans can help to explain an easy procedure such as a block card, check balances, view the status of the customer's applications and so on. While our customer service can focus on more complex work such as corporate loan and decide to analyze the customer's risk profile.

Application of AI/ML in banking

Some use case that can take advantage of technology AI/ML are as follows:

1. Chatbot and Virtual Assistant

The Bank used the chatbot (a kind of service text) and the voice bots (with sound) to resolve the problem.

Typically the technology involved here is Natural Language Processing

2. Customer Profiling

The Bank can do communicate and take decisions based on detailed profiles of every customer. The decision was taken without human intervention.

AI uses data that is structured as well as unstructured to view customer profile.

With this technology, the Bank is able to gauge the risk of the customer and this will bring up a lot of products that can be offered as loans and credit cards

3. Simplify the process

The process that nature's "low value " repetitive and can be submitted to on AI because AI is equipped with the knowledge related to the regulation and the regulation of the legislation in force.

Further AI/ML can be used to predict the possibility of a failure of a system, it opens the possibility for no need for preventive maintenance

4. Detect patterns

AI can detect patterns and anomalies related transactions they fraud or money laundering (money laundering). Face and Voice recognition can be used to detect the perpetrator of the fraud. The data can also be used to find a use case business insight and bar are related to risk and investment opportunities.

The technology used is Machine learning which can be unstructured data from cleans up noise that occurs in the data. Complex image recognition can be used to identify people and goods.

AI/ML is the answer to the business processes in banking that relies on the business rule in the different process.

Implementation of AI/ML in banking

To be able to apply AI/ML in banking the bank needs to pay attention to the following points:

1. 1.Build the digital backbone for safe and fast

AI requires a large amount of data and the quality is good to be able to function properly, perform analysis and make the right decision. This data should be able to move safely and quickly from one point of collection to the point analysis and vice versa.

These large amounts of data can take advantage of Enterprise Data Warehouse (EDW) or big data is already owned by the bank.

2. Transform human resources

AI/ML is used to do work that is repetitive and "low value " relating to regulation and the rule of law.

But AI/ML does not replace the role of human beings. AI/ML is the complement of men. Humans enabled for jobs that require more complex analysis capabilities that cannot be handled by the AI/ML. However banking needs to improve its resources, employees need to be given proper training related to the utilization of AI in their daily work.

3. Comply with privacy and security legislation

Related to data, respecting customer privacy but maintaining high-security standards is very important. AI uses a large amount of customer data to "learn" (or learn) and do its job. However, this data utilization needs to follow regulations that have been set nationally by the Bank or the Financial Services Authority.

The utilization of this data should be accompanied by the protection of customer data to minimize the security risks that might be posed by the AI data utilization.

4. Keep in touch directly with the customer

AI helped the banking customer service to interact with the customer for such needs estimate things that will happen in the future or give personal recommendations to customers. AI was utilized to resolve issues quickly and efficiently.

However, AI has no ability and emotional empathy, which is a very important part of our Customer Service. So the banking needs to balance the AI with a human so that businesses can stay in touch with clients in the context of human relationships.