Business / Data Analyst for Credit Risk Data Remediation
Manila (One Ayala Tower 2), Philippines
Background on what ING is about (Generic ING background):
ING Hubs Philippines (ING Hubs PH) is an international part of the ING organization delivering services to many Business Units across the world for both Wholesale Banking and Retail Banking activities. Working for ING Hubs PH means working with the most diverse workforce and where no challenge is the same.
At ING our purpose is to empower people to stay a step ahead in life and business. We believe that sustainable progress is driven by people with the imagination and determination to make a better future for themselves and those around them.
ING is changing what banking is. For you, that means plenty of opportunities for personal growth in a continuously evolving environment. If this is the environment you thrive in, then apply and join us in changing the future of banking!
Job Overview
COO Risk sits right at the heart of the Bank’s complexity. We translate our rather complex banking business exposures into impact on risk weighted assets and provisions in line with the constantly changing business desires and the latest regulatory requirements. We are an integral part of the Credit Risk Modelling organization where we manage our processes from credit risk modeling approach definition all the way up to postproduction monitoring. We hereby offer a unique opportunity to enter one of Europe’s most appealing Banks at a key position that enables you to contribute, collaborate and grow!
In a nutshell, it is all about collaboration and understanding the end to end complexity of the Bank in particular it’s products and related credit risk exposures [including corresponding processing activities and the way these are underpinned with state of the art technology solutions]. If you have a natural drive to collaborate and a sense of urgency to conclude and deliver we would be very keen to get in touch!
Key Responsibilities
We are looking for a Business / Data analyst within the Default remediation and Loss Given Default (LGD) data team. The team focuses on ensuring complete and correct default and LGD related data for modelling purposes starting from data capturing to data delivery.
The role is twofold as it is focused on performing historical default data analysis, data collection, and data enhancement for the wholesale banking portfolios, in line with latest internal and external regulation related to ING Definition of Default policy and LGD model estimation. You will further help management to develop and implement processes and working instructions, hold responsibility for KPI tracking and dashboarding as well as support the teams in managing ad-hoc requests and help coordinating onsite inspections by the regulator
• You perform historical data remediation for default cases within the Wholesale Banking portfolio (including Large Corporates, Commercial Property Finance, Project Finance, Lease, Trade Commodity Finance, Object Finance).
• You work in a team of experts which are all involved in ensuring complete and correct C&R data for current default cases in the WB portfolio in LGD lab (via standalone C&R tool).
• You work on process improvements and help management to coordinate the ongoing remediation projects.
• You support in managing the planning backlog of the remediation teams
• You closely interact with your colleagues within the COOR and WB area, who are using your remediated default data, in order to build the WB credit risk models (for RWA, ECAP and IFRS9).
• You have regular interaction with the credit risk officers and front office involved for the respective (problem) loans.
Key Capabilities/Experience
We are looking for professionals to perform historical default data analysis, data collection, and data enhancement for the wholesale banking portfolios as mentioned above, in line with latest internal and external regulation related to ING Definition of Default policy and LGD model estimation. Knowledge in both front office banking
processes as well as the restructuring and refinancing processes is preferred. Experience in analyzing cashflows and transactions of separate loans/facilities is a plus.
Candidates:
• should have basic understanding of Wholesale Banking regular lending products;
• should have experience in credit risk, data management, data quality, or a related field within financial services;
• should be able to read and understand loan documentation and identify terms and conditions in line with the default events of each NPL;
• should have an affinity for technology and the ability to analyze and work with data using Excel, VBA, Access, Python, SQL, SAS, or other tools;
• should have strong analytical mindset, attention to detail, and ability to work independently and collaboratively;
• should have excellent communication and stakeholder management skills to work across risk, data, and technology teams;
• Working knowledge on credit risk concepts and components including PD, LGD, and EAD is ideal;
• Relevant working experience on new definition of default policies and related (forbearance) default indicators and triggers is a plus
Minimum Qualifications
We are looking for pro-active candidates with background in wholesale banking lending, credit risk, credit restructuring and refinancing processes. Good writing and oral communication skills are a must (primarily English). The candidate has a critical and analytical mind and willing to get the job done.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Banking Credit risk Data analysis Data management Data quality Excel Finance Python R SAS SQL
Perks/benefits: Career development Team events
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