The Function and Role

Business Banking Modeling and Analytics (“BBMA”) is responsible for supporting the Business Banking business by applying data science to drive customer engagement, business intelligence, risk and portfolio management, as well as business compliance.

Specifically, the team is responsible for managing credit risk scorecards, Basel capital models, IFRS 9 provisioning models, customer / marketing predictive models (segmentation, propensity, cross-sell, anti-attrition, etc) and managing the marketing campaign operations (leads generation, fulfilment, tracking, etc) through online and offline channels.

Responsibilities

Monetize data + analytics in support of sales, marketing, product and portfolio managers in the following areas:
- Prospecting and improving new customer acquisition – segmentation, market/wallet sizing, product proposition, pricing, leads generation + scoring, etc
- Growing existing customer franchise and balances – cross-selling, retention, next best offer + conversation, personalized customer engagement (online + offline)
- Improving digital (mobile app and internet banking) adoption and customer interaction via personalized, omni-channel engagement
Candidate is expected to build predictive models/analytics using:
- a suite of statistical / data science techniques (regression, gradient boosted trees, network analytics, neural networks, NLP, audio/image processing, etc) that is best fit for purpose / use
- both structured and unstructured data (test, audio, image, streams, etc) that can be found within the bank and external partners, vendors or in the internet in general (social media, web-crawled data, etc)
Work with BB’s ecosystem / partnership team to increase monetization of partner / platform data (eg, e-commerce, payments, ERP solutions, etc), and actively source for new data sources / revenue streams
Manage regular marketing campaign operations, including regular reviews and feedback to improve conversion rate / campaign / model effectiveness
Work with the Group BBMA team to develop, enhance and manage credit risk models, including: application and behaviour scorecards / rating systems, Basel 2 capital models, IFRS 9 loss provisioning model, and early warning systems
Generate regular credit portfolio quality reports and run the monthly portfolio quality reviews with country and Group stakeholders. Conduct ad-hoc / deep dive analyses to identify risk hot-spots and work with the Credit team to address current or emerging issues. Support analytics for product program renewals, including proposing test-and-learn programs to expand / optimize credit policies, approval rates and potential target segments

Qualifications

>7 years of experience in retail / SME credit risk and/or marketing analytics roles within a bank, fintech, or consulting environment.
Undergraduate degree in a quantitative programme, such as Decision Science, Statistics, etc. MBA / post graduate degree is desirable
Very strong data/decision science, programming and technology skills:
- At the minimum, very proficient in SAS for data management and modeling
- Advantageous to have proficiency in Python or R for data science and Hadoop ecosystem for data management – uses Cloudera Apache Hadoop big data platform
- Adobe Marketing platform (Adobe Analytics, Campaign, etc) for online and offline marketing campaign management and insights
Analytical mind with sound business insight, excellent communicator (verbal and written), highly meticulous, and self-motivated
Maturity that will enable the candidate to be a credible counterpart to business managers and senior management, and the ability to develop on-going ‘trusted advisor’ relationships based on the ability to understand, analyse, discuss and address key business challenges raised