Fresh Jobs at Kuda Bank

Kuda Technologies Limited, or Kuda, is a microfinance bank and fintech in Nigeria and the UK. Aiming to be the preferred banking option for Africans and the diaspora, Kuda leverages technology to provide accessible financial solutions.

It offers various banking services, including free money transfers, investment opportunities, and money management features, all accessible through a mobile app. Kuda is licensed by the Central Bank of Nigeria.

Applications are invited from interested and qualified candidates to apply for Jobs at Kuda Bank

Loan Monitoring & Early Warning Lead

Job Specifications:

• Full Time
• Required Qualifications: BA/BSC/HND – MBA/MSC/MA
• Location: Lagos| Nigeria. See other Jobs in Lagos
• Category: Accounting| Tech Jobs
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Job Description:

• To drive the Bank’s Early Warning, Loan Monitoring and Collateral Management strategies, implement portfolio monitoring policies and procedures, ensure effective credit controls, and promptly identify and escalate warning signals in credits to secure long-term asset quality.

Responsibilities

• Support the Head, ERM by ensuring that early warning indicators are effective, and loans are repaid or recovered promptly in line with contractual terms and established guidelines.
• Implement the Early Warning, Loan Monitoring and Resolution Department’s standardized processes and automation of critical processes and reports.
• Review and enforce Service Level Agreements (SLAs) with Business units and other Risk Management functions for all Early Warning, Loan Monitoring and Collateral Management processes.
• Review and approve the teams Operational Risk tool kits (RCSA) and ensure quality assurance of reports submitted by risk champions.
• Coordinate and act as the Secretariat for the Bank-wide Criticized Assets Committee meetings.
• Engage the Business units and other key stakeholders to track and ensure all action items during the CAC meeting are duly implemented as directed by the committee.
• Supervise and ensure the Preparation a daily exception report on all facilities booked and monitor regularization.
• Coordinate and conduct customer visits to provide leadership and guidance on sensitive remedial actions and deliver commitment from the Bank on resolution.
• Engage the Strategic Business Units to agree and drive Recovery, Collection & Remedial strategies.
• Supervise and ensure prompt confirmation of all submitted invoices by the customers before loans are booked on the Nerve core banking application
• Collaborate in the execution of collection strategies to maximize collections on defaulted accounts, including early problem recognition, management and restructuring.
• Supervise and ensure prompt call-over of activities of the disbursement officers to track compliance with terms and conditions of facilities.
• Prepare a dashboard to notify the Head, ERM of the Bank’s portfolio performance metrics, reflecting re-default ratio and other performance indices.
• Review the Bank’s monthly Criticized Assets Report and ensure the portfolio performance ratios along the relationship managers and the sectors are well captured.
• Ensure the preparation and review of reports as required by internal and external stakeholders
• Review the Loan Loss journal and ensure monthly provisioning is charged to the P and L
• Conduct a high-level review of selected products, highlighting the performance status and useful recommendation to improving the portfolio health.
• Develop a report on Loan loss accounts that will effectively impact the Bank’s bottom line and work with the business team to ensure resolution.
• Ensure the Overdraft efficiencies are effectively monitored in compliance with the agreed turnover covenant.
• Supervise and monitors the appointment of the Bank’s Estate valuers and Collateral managers.
• Review the activities of the Bank’s appointed Estate valuers and Collateral managers.
• Ensure the Bank’s contingent exposures are promptly reviewed and duly updated on core banking application to reflect the Bank’s current liability.

Qualifications and Requirements:

• B.Sc in Economics or related field, MBA (Executive) is an added advantage
• Minimum of 5 years of Credit Monitoring, credit administration, Credit Risk Analysis, Collateral Management and Remedial Management experience with added experience in distressed or workout loans
• Excellent Credit Risk Management and Credit Administration
• Proficient knowledge of loan structuring/restructuring
• Perfect understanding of CBN guidelines
• Proficient knowledge of banking operations and product
• Good knowledge of other extant regulations & provision.

Benefits
At Kuda, our people are the heart of our business, so we prioritize your welfare. We offer a wide range of competitive benefits in areas including but not limited to:

• A great and upbeat work environment populated by a multinational team
• Pension
• Career development & growth
• Competitive annual leave plus bank holidays
• Competitive paid time off (Parental, Moving day, Birthday, Study leave etc)
• Group life insurance
• Medical insurance
• Well-fare package (Wedding, Compassionate and etc)
• Perkbox
• Goalr – employee wellness app
• Award winning L&D training
• We are advocates of work-life balance, working in a hybrid in office schedule.

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Data Scientist – Financial Fraud Detection

Job Specifications:

• Full Time
• Required Qualifications: BA/BSC/HND – MBA/MSC/MA – PhD/Fellowship
• Location: Lagos| Nigeria. See other Jobs in Lagos
• Category: Accounting| Tech Jobs
• Job Alerts: To receive Job Alerts on WhatsApp, Click HERE

Click HERE to Post A Job

Job Description:

We are seeking a highly skilled and experienced Data Scientist to join our Decision Science team, specializing in the development and deployment of advanced fraud detection models. In this critical role, you will play a key part in safeguarding our customers and the bank from financial losses by identifying and mitigating fraudulent activities across various channels. You will work with vast, complex transactional datasets, collaborate closely with Fraud Operation and Credit Risk and Compliance teams, and contribute to the continuous evolution of our fraud prevention strategies in a highly regulated environment.

Roles and responsbilites:

• Design, develop, and implement machine learning models tailored for banking fraud detection, including  anomaly detection, transaction fraud, account takeover, application fraud, and money laundering detection.
• Deploy and monitor real-time fraud detection systems, ensuring high performance and minimal latency.
• Continuously evaluate and refine models to improve accuracy and efficiency.
• Develop models that adhere to regulatory requirements and compliance standards (e.g., AML, KYC).
• Adapt models to the ever-changing tactics of financial criminals.
• Analyze large volumes of transactional data, customer behavior data, and external data sources to identify fraud patterns and anomalies.
• Conduct in-depth analysis of financial transactions to detect suspicious activities and potential fraud risks.
• Develop and maintain data pipelines for fraud-related data, ensuring data integrity and compliance.
• Collaborate with fraud investigators, risk managers, compliance officers, and technology teams to develop and implement effective fraud prevention solutions.
• Communicate complex model insights and fraud trends to stakeholders, including senior management and regulatory bodies.
• Participate in cross-functional projects related to financial crime prevention and risk management.
• Stay abreast of emerging fraud trends and regulatory changes in the banking industry.
• Research and evaluate new machine learning techniques and technologies for fraud detection in the financial sector.
• Contribute to the development of innovative solutions for combating financial crime.

Qualifications and Requirements:

• Degree in Computer Science, Statistics, Mathematics, Finance, or a related quantitative field.
• A Master’s or Ph.D. degree is desirable but not required.
• Minimum of 3 years of experience as a data scientist, within the banking or financial services industry.
• Proven experience in developing and deploying machine learning models for transaction monitoring, customer behaviour.
• Familiarity with Credit Product construct.
• Familiarity with regulatory requirements and compliance standards related to financial crime (e.g., AML, KYC, GDPR).
• Strong proficiency in Python and relevant machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch).
• Expertise in SQL and experience with large-scale relational databases.
• Experience with fraud detection platforms and tools is desirable
• Knowledge of cloud platforms (e.g., AWS, GCP, Azure) and big data technologies (e.g., Spark, Hadoop).
• Knowledge of statistical analysis, time series analysis, and network analysis.
• Strong analytical and problem-solving skills, with a focus on detail and accuracy.
• Excellent communication and presentation skills, with the ability to convey complex information to diverse audiences.
• Ability to work effectively in a fast-paced, regulated environment.
• Strong understanding of banking operations and financial products.

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