Of the reactive -based rule. AI transforms consumption loans. But to succeed, human capital must be as important as technological advances.
Financial institutions around the world take advantage of AI, marking a transition from traditional systems based on rules to reactive and intelligent solutions. Nowhere has the merger of data and AI has more potential in one of the main banking functions – consumer loans – which promises to make it more intelligent, faster, more efficient and potentially more inclusive.
“Since the launch of our loan solution fueled by AI, SME customers have benefited from a much simpler and faster process for eligible applications,” explains Mikheil Nadareishvili, director of analysis of the Data Analysis of the Georgia Bank (BOG). Other data -based innovations at BOG include recommendations powered by AI and an advanced chatbot fueled by AI. “Automation has stimulated accessibility and eliminated manual obstacles while IA income and Ebitda models have accelerated decision -making.” Nadareishvili reports that, since the launch, 46% of loans have been confirmed by the digital process and that “Time to Yes” has gone from more than 2.5 days to only 11 minutes.
Chatbot evolution
Data is the vital element of chatbots, which counts to learn, understand, respond effectively and improve permanently over time, which makes them more and more precious tools for many financial applications. Bank of America presented Erica, its virtual financial assistant AI, to customers in 2018. The service has undergone significant development since then.
“Erica continues to evolve by guaranteeing that our capacities and investments are scalable and reusable in the various sectors of activity,” explains Hari Gopalkrishnan, the new technology chief and the information manager of the bank. “We continue to work to make Erica more anticipated towards customer needs while allowing our partners to become more productive to sail in complex tasks at the service of our customers.”
Customers have interacted with Erica more than 2.7 billion times since its launch, notes Nikki Katz, digital manager. “This is an example of what this era looks: more personalized, with the customer at the center of everything.”
In Türkiye, Akbank Mobile provides agency conversation services with reasoning from the recovery powered by AI. This form of agent mobile bank exploits the customer imprint to provide a personalized, proactive and beyond the bank, explains Gökhan Gökçay, executive vice-president of Akbank technology.
“Akbank Asistan fueled by AI Analyzes data, products, behaviors and transactional footprint of customers, to generate tailor-made ideas and recommendations,” he said, noting that the virtual assistant increased the product conversion rate to 2% to 18%. Thanks to transparent text or voice interactions, the assistant classifies more than 1,000 intentions and can independently perform more than 200 banking transactions.
“Its design incorporates an advanced NLP [natural language processing] With models of large languages, allowing contextual answers and intelligent research in a few milliseconds, “explains Gökçay.” The unified infrastructure of the assistant supports all [interactive voice response]And feed the self-service capabilities that considerably reduce the volumes of the call center. »»
Akbank Asistan also supports the Bank’s Help Me module, managing 250,000 monthly requests that would otherwise reach call centers, increasing customer efficiency and satisfaction. The dynamic avatars created via Genai reflect customer behavior, deepening their commitment with Akbank Mobile. Avatars are updated monthly on the basis of a client’s financial behavior, offering users a more relatable and emotionally engaging interface.
“This personalized omnichannel experience illustrates how the AI agent transforms relations with customers – from reactive service to the predictive and information -oriented bank,” observes Gökçay.
The essential human element in the adoption of AI
This change to the intelligent and reactive bank does not only improve operational efficiency and decision -making, but the redefinition of customer relations, preparing the way for new AI processing applications in the consumer bank. This does not mean that humans can be replaced. The adoption of AI requires investments in human capital, which means that any technological advance must be linked to the transformation of the workforce.
“The commitment to responsible AI extends beyond our technology,” explains Nimish Panchmatia, data manager and transformation at DBS. “We recognize the potential impact on our workforce and invest in a proactive manner in bulging and reskulling initiatives.” DBS has identified some 13,000 employees who will benefit from its GEN AI programs. To date, more than 10,000 are formed, “demonstrating our dedication to a workforce ready for future which can prosper in this evolving technological landscape”, explains Panchmatia.
At Jordan’s Arab Bank, “we aim to integrate AI assistance on all facets of our operations, decision -making and customer interactions,” explains Eric Modave, Deputy CEO and COO. Becoming an organization in the foreground requires a concentration concentrated in four pivotal areas: staff, systems, data and a governance framework for robust AI, he underlines.
“First, our employees: we must make sure that they have awareness and training to feel comfortable using AI,” explains Modave. “They should clearly understand its advantages, limits, risks and railings. It is also crucial for us to remain informed of the evolution of AI regulations as well as data confidentiality and cloud-use rules, because these can have a significant impact on how we design our AI solutions. “
Technical teams must understand the different technical solutions for the integration of AI into the processes and decision -making of the bank, adds Modave. This includes traditional predictive models, automatic learning, genai for complex tasks, agency AI for processes optimization and conversational AI. It is also important to build technical safety and monitoring of the proactive system to report potential problems before they affect customers or staff.
“Having a coherent data strategy is also essential,” he says. “He must meet our business needs while having a solid control framework. Any data strategy must explicitly address access to data, quality and anonymization, underlines Modave.
Finally, “we must learn to prioritize AI’s ideas to ensure that our investments and our development efforts are really chargeable,” explains Modave. Arab Bank has set up an AI governance committee which examines each new IA idea, assessing the investment effort required in relation to the potential advantages at each stage of the implementation: ideation, prototyping, proof of concept and implementation. Once an AI solution is in production, the staff of the automatic learning operations of the bank and the risk team oversee performance and production to guarantee the delivery of the desired result at the expected cost.
Priority to the transformation of the workforce through reduction and reskulling initiatives, focusing on crucial skills on AI and data analysis, is essential to AI’s success – by informing it that employees include the advantages, limits and risks of technology and that AI is integrated transparently into human expertise and ethical considerations. This being the case, AI has the possibility of amplifying human capacities, leading to more efficient, inclusive and focused consumers.