Announcing the Celent Model Risk Manager 2021 Award Winners

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9 March 2021
Neil Katkov and Arin Ray

Winning initiatives show that financial institutions are making clear strides in applying next-generation technology to risk management and compliance operations.

Congratulations to Celent's Model Risk Manager 2021 Award winners: Credit Suisse, Fino Payments Bank, Goldman Sachs, HSBC, Standard Bank, State Street, Swedbank, and United Overseas Bank.

Detailed case studies and video interviews on the winning initiatives are available as noted below.


Model Risk Manager of the Year 2021 Award Winner: Credit Suisse - Risk360 Advanced Risk Analytics Platform

Category: Digital and Emerging Technologies

Synopsis: Credit Suisse’s Chief Risk Office in Asia-Pacific created a cross-risk platform for risk identification and analysis across financial risk, operational risk, and compliance. This one-stop shop for risk and compliance uses in-memory machine learning algorithms to integrate and analyze data from multiple internal and external sources to provide risk officers with actionable alerts and support ad hoc analysis, all in one fell swoop.

Case Study and Video


Winner: Fino Payments Bank - Remote implementation of Enterprise-Wide Fraud Management During the Pandemic

Category: Legacy and Ecosystem Transformation

Synopsis: Fino Payments Bank implemented a modern, AI-enabled enterprise-wide fraud solution from Clari5 across all its channels. The implementation was completed remotely by both the bank and the vendor in response to the COVID-19 pandemic. Surprisingly, the remote implementation methodology—while requiring close, optimized project management—led to increased efficiencies and more rapid project delivery.

Case Study and Video


Winner: Goldman Sachs - Machine Learning-Powered Watchlist Screening Tool

Category: Data, Analytics, and AI

Synopsis: Goldman Sachs needed a watchlist screening solution that would be efficient in minimizing the number of hits and effective in catching blacklisted individuals while being scalable enough to support a fast-growing client base. The bank recognized the potential of machine learning-powered screening solutions and, after a due diligence of third party solutions available in the market, decided to build an in-house tool for screening consumer banking customers. The solution provides major business benefits, including a one hundredfold reduction in alert volumes and an estimated US$30 million cost savings achieved through headcount reduction due to optimal alert generation.

Case Study and Video


Winner: HSBC - Insurance-Focused Transaction Monitoring Solution Powered By Machine Learning And Cloud

Category: Legacy and Ecosystem Transformation

Synopsis: In this project HSBC set out with the view of developing an exclusively insurance-focused solution and achieved its goal. Its application of machine learning (ML) in insurance, especially its use of ML to generate transaction monitoring alerts automatically, is among the leading use cases of ML in AML. HSBC’s deployment of this solution, powered by Featurespace's ARIC platform, over Google Cloud is impressive and among the early AML cloud adoption instances among large financial institutions..

Case Study and Video


Winner: Standard Bank - KYC On The Go, A component of Remote Customer Onboarding

Category: Digital and Emerging Technologies

Synopsis: As evolving technologies lead to heightened customer expectations, Standard Bank has adopted digitization as a strategic pillar to support customer centricity as a source of competitive advantage. To support digital onboarding of small business customers, the bank implemented an in-house solution to digitize the KYC document collection process. The tool, built on Microsoft Power Apps, is simplicity itself, yet has enabled Standard Bank to replace a highly laborious paper-based process and at the same time achieve 100% compliance with KYC requirements.

Case Study and Video


Winner: State Street Global Advisors - Measuring Macroeconomic Risks For Portfolio Management

Category: Data, Analytics, and AI

Synopsis: State Street Global Advisors wanted the ability to monitor macroeconomic risks on its portfolios because it recognized the importance of understanding macroeconomic exposures for portfolio risk management, optimized portfolio construction, stress testing, and return attribution. They achieved this by projecting the fundamental factor returns against a set of macroeconomic factors and formulating a new macroeconomic model. This effort avoided the need to build a separate model from scratch, which can be operationally costly. It ensured that the adjusted model is aligned with fundamental models already in use. Development and implementation of the solution was facilitated by the active involvement of the vendor Qontigo.

Case Study and Video


Winner: Swedbank - Modernizing Card Fraud Management and Improving Customer Experience

Category: Legacy and Ecosystem Transformation

Synopsis: Swedbank was concerned that the SCA requirements in the EU's PSD2 regulation could introduce friction into the customer experience by requiring two-factor authentication (2FA) for online and contactless payments in its home markets in the Nordics and the Baltics. The bank responded by implementing a strategy to reduce customer friction by using machine-learning-based transaction risk analysis (TRA) supported by solutions from ACI Worldwide to maximize the SCA exemptions allowed by the regulation, thereby improving the customer experience while reducing fraud rates.

Case Study and Video


Winner: United Overseas Bank - Machine Learning-Powered Alert Triaging For AML Transaction Monitoring And Name Screening

Category: Data, Analytics, and AI

Synopsis: United Overseas Bank recognized the potential of artificial intelligence (AI) and machine learning (ML)–powered solutions to strengthen its control and streamline AML operations. Its co-development and implementation of Tookitaki’s AML Suite (AMLS) is a leading use case of AI application in AML, especially because the bank has applied it across both transaction monitoring and name screening processes at the same time. The solution has resulted in impressive outcomes in high accuracy in identifying both true positives and false positives and enhanced efficiency and effectiveness of the bank’s AML program. It strengthens UOB’s financial-crime compliance operations by allowing the bank to draw out faster and more precise information to detect and prevent suspicious money-laundering activities.

Case Study and Video

Insight details

Industry
Capital Markets, Corporate Banking, Retail Banking
Subscription(s) required to access this Insight:
Risk & Compliance, Financial Risk, Operational Risk
Insight Format
Blogs
Geographic Focus
Asia-Pacific, EMEA, LATAM, North America