financialtreat – will explain about AI In Banking Is Indispensable For Digital Activities In The Banking Sector which you will get in the following article. let’s look at this article carefully!
The total population of Indonesia is currently 270.2 million people with a population of 197.71 million internet users. With the current Covid-19 pandemic situation, these developments will continue to increase. Many companies that use to run their business processes conventionally turne to digital by creating new applications to help businesses during the pandemic. For this reason, ai in banking is neede to support business quickly.
In addition, with the emergence of these applications, companies are starting to think about increasing their efficiency, especially in terms of data storage. Seeing this, the majority of application makers are starting to go cloud-base. The current use of the cloud in the corporate environment is becoming deeper and digital transformation is accelerating with big data analysis.
AI in banking is indispensable for digital activities in the banking sector
Thus, the banking sector as one of the national strategic sectors needs to increase its services by providing an increasingly efficient network infrastructure to meet the needs of its customers in order to maintain the stability of Indonesia’s financial platform.
The new challenge for banks is the need to increase network capacity, reliability and security in line with the development of digital transactions. Therefore, AI in banking is neede to launch a business that is turning to digital. This is due to increase the needs of its customers.
Along with the increase in digital activity in the banking sector, cyber crime and digital fraud are also increasing. Banks are require to be able to increase digital security through the application of the latest technology. One of the new technologies widely applie by banks is artificial intelligence (AI) technology.
Seeing its very broad scope, the definition of AI still cannot be establishe. Monet et al. conclude that researchers still do not agree on a general definition of AI. Base on Mckinsey’s working paper, the application of AI in the banking sector can add 4 (four) positive benefits for the bank itself, namely increasing profits, large-scale personalization, working on the omnichannel market (online shopping), and increasing discovery in companies.
From Mckinsey’s research, it was also found that nearly 60 percent of large banks have use AI in their business systems. Most of them use AI for virtual assistants (CS robots), as a fraud detection tool, and realtime risk monitoring.
Seeing the many benefits of implementing AI in the banking sector, OJK as the regulator needs to hold a webinar regarding the potential for AI implementation in the banking sector in order to provide broad understanding and insight for banking stakeholders.
BCA has Vira, BNI has Cinta and Lena, at BRI there is Sabrina, HSBC has Amy, OCBC has Emma. These names are chatbots that have been implemente in banking in Indonesia. This chatbot is a technology that can act “as if” like humans in dealing with customers.
Technologies that can simulate humans are known as AI and Ml. Artificial Intelligence (popularly known as Ai) and Machine Learning (ML) are currently technologies that are being explore by banking in the digital era.
AI and ML technology is a technology that before being recognize by banks has been widely use by financial technology-base companies (Fintech). It must be considere that banks are a bit late in responding to this technology.
Fintech has use AI/ML technology to carry out complex regulations that in banking need to involve human factors, such as credit risk, providing additional unsecure loans to customers, and also automatic chatbots. Banks are starting to adapt AI to chatbots, chatbots are automate customer service facilities where humans will be serve by AI to solve cases they experience when interacting with banks.
What is Artificial Intelligence and Machine Learning?
Artificial Intelligence (Or commonly referre to as AI) or prosthetic intelligence is human intelligence that is implemente into technology / machines. A machine is said to have AI if it can show its intelligence to imitate human cognitive benefits without the hegemony of humans.
Machine learning (ML) is a terminology that cannot be separate from AI because ML is a form of AI application where machines learn data using statistical methods and then run a job without being programme first.
Ai/Ml in principle does not replace human work. AI/Ml is use to complete simple and repetitive tasks when humans can focus more on tackling more complex problems.
In customer service work like the example above, AI in chatbots can help humans to explain easy mechanisms such as block cards, check balances, view customer application status and so on. Pas customer service can focus on more complex work such as deciding on loan companies and analyzing customer risk profiles.
Application of AI / ML in banking
Some use cases that can take advantage of Ai/Ml technology are as follows:
1. Chatbot and Virtual Assistant
The bank uses chatbots (a kind of text service) and voice bots (with melodies) to solve cases. Usually the technology involve here is Natural Language Processing
2.Customer Profile
Banks can conduct and carry out communications and take regulations base on the detaile profile of each customer. Regulations are taken without human intervention. AI uses structure and unstructure data to view customer profiles. With this technology, banks can measure their risk to customers and this will bring up many products that can be offere such as loans and credit cards
3. Simplify the process
Processes that are “Low value” and repetitive can be left to AI because AI is equippe with knowledge regarding regulations and applicable legal decisions. Furthermore, Ai/Ml can be use to predict the possible failure of a system, this allows for the possibility of unnecessary preventive maintenance.
4. Detect pattern
AI can detect patterns and anomalies regarding transactions that are indicate as fraud or money laundering. Face and Voice recognition can be use to detect fraud perpetrators. The data can also be use to find use cases and new business insights relate to risks and investment opportunities.
The technology use is machine learning which can clean unstructure data from noise that occurs in the data. Complex image recognition can be use to identify people and things. AI/ML is the answer to business processes in banking that rely on business rules in various processes.
AI/ML Implementation in Banking
To be able to apply Ai/Ml in banking, banks need to pay attention to the following:
1. Build a conducive and fast digital backbone
AI requires large amounts of data and good quality to function properly, perform analysis and make the right decisions. This data must be able to move conducively and quickly from one point of collection to the point of analysis and vice versa.
This large amount of data can take advantage of the Enterprise Data Warehouse (Edwh) or big data that is already owne by the bank.
2. Transforming human energy sources
Ai/Ml is functione to carry out repetitive and “Low value” work relate to regulations and statutory provisions. But Ai/Ml does not replace the human role. Ai/Ml is human complement.
Humans are functione for jobs that require more complex analytical skills that cannot be handle by Ai/Ml. However, banks need to increase their resource capacity, employees need to be given proper training on the use of AI in their daily work.
3. Comply with the provisions of privacy and security laws
Regarding data, respecting customer privacy while maintaining high security standards is very important. AI uses large amounts of customer data to “Learn” (or learn) and carry out its tasks.
However, the use of this data needs to follow the provisions. That have been determine nationally by Bank Indonesia. Or the Financial Services Authority. The use of this data must be accompanie by assistance on the security of customer data to minimize. The risks that may arise from the use of data by Ai.
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4. Keep in direct contact with customers
AI helps banking customer service to interact with customers. For purposes such as predicting things that will happen in the future or adding personal recommendations to customers. AI is also use to solve problems quickly and efficiently.
But AI lacks the emotional capacity and empathy. Which is a very important part of Customer Service. So that banks need to balance AI with humans. So that businesses can stay in touch with customers in the context of human interaction.
Well, those are some interesting reviews about using AI in banking. Hopefully the explanation above can be use as a reference, thank you.
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