In the realm of globalized financial markets, commercial banks are confronted with an escalating magnitude of credit risk, thereby imposing heightened requisites upon the security of bank assets and financial stability. This study harnesses advanced neural network techniques, notably the Backpropagation (BP) neural network, to pioneer a novel model for preempting credit risk in commercial banks. The discourse initially scrutinizes conventional financial risk preemptive models, such as ARMA, ARCH, and Logistic regression models, critically analyzing their real-world applications. Subsequently, the exposition elaborates on the construction process of the BP neural network model, encompassing network architecture design, activation function selection, parameter initialization, and objective function construction. Through comparative analysis, the superiority of neural network models in preempting credit risk in commercial banks is elucidated. The experimental segment selects specific bank data, validating the model's predictive accuracy and practicality. Research findings evince that this model efficaciously enhances the foresight and precision of credit risk management.

With the rapid growth of technology, especially the widespread application of artificial intelligence (AI) technology, the risk management level of commercial banks is constantly reaching new heights. In the current wave of digitalization, AI has become a key driving force for the strategic transformation of financial institutions, especially the banking industry. For commercial banks, the stability and safety of asset quality are crucial, which directly relates to the long-term stable growth of the bank. Among them, credit risk management is particularly core because it involves the flow of a large amount of funds and the accuracy of credit decisions. Therefore, establishing a scientific and effective credit risk decision-making mechanism is of great strategic significance for commercial banks. In this context, the innovative application of AI technology has brought revolutionary changes to bank credit risk management. Through deep learning and big data analysis, AI can accurately evaluate the credit status of borrowers, timely identify potential risks, and provide banks with more accurate and comprehensive credit decision support. At the same time, AI can also achieve realtime monitoring and early warning, helping banks intervene before risks occur and reduce losses.

Effective control of credit risk is a key link in the steady operation of commercial banks. This paper is mainly based on the customer information dataset of a foreign commercial bank in Kaggle, and we use LightGBM algorithm to build a classifier to classify customers, to help the bank judge the possibility of customer credit default. This paper mainly deals with characteristic engineering, such as missing value processing, coding, imbalanced samples, etc., which greatly improves the machine learning effect. The main innovation of this paper is to construct new feature attributes on the basis of the original dataset so that the accuracy of the classifier reaches 0.734, and the AUC reaches 0.772, which is more than many classifiers based on the same dataset. The model can provide some reference for commercial banks' credit granting, and also provide some feature processing ideas for other similar studies.

Every financial institution is looking to digital transformation to meet rising customer expectations for speed and convenience, lower its operating cost, and fend off competition, including from tech companies moving into financial services. Some are spending over 10% of yearly revenue on technology investments, according to Bloomberg. "This is a huge investment and most financial institutions cannot support this for the long term," says Michael Fei, SME banking CEO at OneConnect Financial Technology, an associate of Ping An Insurance. The covid-19 pandemic has revealed how even financial institutions that considered themselves digitally advanced are, in reality, still wedded to analog processes along the chain of processing. "For many financial institutions, this has been a wake-up call," says Fei. "In the past, many had thought that if they have an online portal and a mobile application then that's enough. But now they've realized it's not. Some banks have online portals and mobile apps where you can apply for loans, but they still need to send items to the customer and carry out on-site inspection before they can process the loans, which hasn't been possible during covid. Banks have had to reshape and redesign the whole process of their lending products."

West Creek 5 (12075), United States of America, Richmond, Virginia Sr. Digital Product Manager – Commercial Bank Capital One is the only founder-led Top 10 bank in the US. We have a mission to Change Banking for Good and we are transforming how people interact with their money. We offer industry-leading credit cards, checking accounts, savings accounts, brokerage accounts, car loans, home loans, and other financial products that are central to the way that more than 65 million people live every day. Our Product Managers play a critical role in achieving our mission. They lead teams of designers, engineers, data scientists and analysts to define product strategy and develop, launch, and enhance products and services that drive our business forward. We are selectively recruiting for a product manager to focus on the reinvention of how commercial clients interact with their bank in digital channels to position Capital One for growth. General Responsibilities:As a product leader you will: Relentlessly push to understand customer needs and ensures customer is considered in prioritization and trade-off discussions Set product vision and lead road mapping, goal setting, story writing, project execution, A/B testing, and product roll-out strategy Identify unmet needs and disruption opportunities and guide interdisciplinary teams to deliver innovative products to market. Test and iterate in small-scale pilots to validate concepts, refine them to achieve product-market fit, and then scale to drive vertical and horizontal economics Define learning agenda and key performance indicators (KPIs) to measure success/failure Regularly and systematically use data to uncover opportunities, track product performance, and drive decision making Leads a team through rigorous process of test and learn with focus on identifying and developing a minimum viable product (MVP) Prioritize, negotiate and remove blockers to orchestrate successful launch or optimization cycle Serve as subject matter expert, contributing practitioner, thought leader, career guide and mentor to teams Establish or participate in Design Thinking, Agile, and LEAN rituals which establish rhythm for the team, promote ongoing communication, and iterative refinement of roadmaps You should have the following: Proven experience in and passion for building and shipping great products Exceptional communication skills Creative problem solver who lives at the intersection of Human, Business and Technology dimensions. Deep fluency and experience in at least two dimensions and understanding of the third. Blend of strategic and tactical thinking, creative and analytic reasoning Strong quantitative background to support data-informed decision making Creative, outside-the-box thinking and problem solving approach Entrepreneurial ability to identify and prioritize opportunities in highly ambiguous contexts Deep planning skills with the ability to organize thematic work areas in deep detail with long term vision and iterative execution Collaborative, team player attitude with the ability to navigate and influence the organization. Proven ability to attract, retain and develop top talent Product Managers Experience shipping multiple products across variety of platforms and channels Engineering, design, MBA and/or start-up founder experience Fluency in human-centered product discovery methods such as design thinking and service design Industry or hobbyist experience with emerging and leading technologies across disciplines (IoT, Machine Learning, Voice interfaces, etc) Track record of defining strategy, creating advocacy/alignment and being accountable for outcomes Basic Qualifications: Bachelor’s Degree or military experience At least 5 years of experience in digital product management Preferred Qualifications: Bachelor’s Degree in Computer Science or Engineering MBA or Master’s degree 5+ years of experience translating business strategy and analysis into consumer facing digital products 5+ years of experience in Agile product management At this time, Capital One will not sponsor a new applicant for employment authorization for this position.

Banks are starting to use artificial intelligence (AI) technology to recruit new workers to ensure fairness and reduce costs. According to KB Kookmin Bank, Monday, the lender will hire 615 new workers in the second half of the year. During the recruiting, the bank said it will use the AI system in its online interview to evaluate applicants more objectively, and the AI analysis data will be used as reference material for the face-to-face interview. It is the first time for a commercial bank to use AI technology in the recruiting process. "KB Kookmin Bank is looking for new talent with innovative ideas," said a KB Kookmin Bank official.

In the blink of an eye, consumers have evolved from being wary of mobile banking to casually quizzing robots in their home about their spending habits. Innovation in banking will continue at its rapid pace in 2018 as more of every bank's budget is earmarked toward technological development, said Mitch Siegel, financial services strategy leader for KPMG. "As we moved through 2017, we saw a marked pivot from investments in compliance infrastructure to investments aimed at growth, scalability, simplicity and future-looking business models," he said. American Banker spoke with several banks, industry analysts and technology companies to learn what technology efforts will take priority in the new year. Here are five areas of focus.