" class="no-js "lang="en-US"> US Market Looks For Industrial Revolution in Credit Risk Model
Thursday, June 13, 2024

US Market Looks For Industrial Revolution in Credit Risk Model Development Post-Covid

On June 30th, 2021, the United Kingdom’s Department for International Trade (DIT) and SPIN Analytics convened a Thought Leadership Roundtable to discuss how the US banking ecosystem could and should accelerate the digitization of credit risk modelling in the light of COVID-19. The DIT and SPIN Analytics invited industry experts to share their experience, discuss the key challenges, and explore potential solutions. The roundtable was moderated by Andrew Stott, Senior Advisor to SPIN Analytics.

Essential Takeaways from the Roundtable:

*The COVID-19 pandemic introduced unprecedented levels of market turbulence and government intervention, leading to a “credit model accuracy crisis” mitigated by government support and expert judgment around credit models.

*While there has been a lot of research and development on the use of machine learning and artificial intelligence as to improve risk models, the  process for developing and maintaining models remains largely manual, time consuming (up to 6+ months per model for regulated models), labor intensive,  costly, and inflexible. Large banks deploy hundreds or even thousands of models, requiring support from hundreds of internal experts across multiple functions. Offering a more automated approach to credit risk modelling will improve banks’ ability to attract and retain talent.

*FinTech’s and Neo banks have an advantage of being able to adopt a more automated data-led approach from the start but have less history and therefore take more time to develop accurate credit models. Very large banks have vast resources and usually an Innovation team which is accelerating the adoption of new technologies. In the middle, the small to medium-sized banks may feel themselves squeezed without the resources of the large banks and with less ability to create fintech-style data environments.

*Digitization, automation and Explainable AI which can be approved by all regulators, remain important components of emerging solutions and continuing advances in technology will drive an “Industrial Revolution” of credit risk modelling in the coming year or two. SPIN Analytics’ RISKROBOT platform allows banks to automate their credit risk modelling end-to-end by applying expert judgment and providing regulatory-compliant explainable models in 10x reduced timeframes.

“The Covid crisis has highlighted the vulnerability of banks in a changing credit context. The winners in future will be those who are most nimble in updating credit risk models and using data in a way that ensures credit decisions are non-discriminatory. Regulators will need to adapt to the technology advances but banks should be proactive in making proposals to regulators as new technology emerges. ” Sue Harnett, Independent Director at OFG Holding Company Bank Board, and at Life Storage. Previously held senior roles at First Niagara Financial Group, QBE, Citigroup and ABN Amro

“As banks move to accept cloud-based technologies and adopt new technologies such as homomorphic encryption, this will expand opportunities to pool data and thus vastly improve banks’ ability to develop and update credit risk models. This is starting to happen in anti-money-laundering and fraud and will continue to evolve. CISOs while having firm grip on data security should become enablers in such a scenario.” Charles Blauner, Partner and CISO in Residence, Team8 Ventures, and Venture Advisor at the Cyber Mentor Fund, previously 25 years in financial services including CISO at JPMorgan and Deutsche Bank, and most recently Global Head of Information Security at Citigroup.

“AI is allowing both new and incumbent banks to industrialize the use of data and we are seeing banks starting to share data to allow this to accelerate. This opens up big opportunities to automate the historically largely manual processes required in preparing data and building credit risk models.”

Sandip Nayak, Chief Strategy & AI OfficerLinear Financial Technologies. Previously SVP at Citi and Capital One.

“Banks face a talent war for credit risk modelling experts given the huge workloads and the limited resource available to tackle the internal and regulatory requirements. Automating end-to-end credit risk modelling will enable the most advanced banks to attract and retain talent by offering an environment that leverages expertise and vastly reduces manual processes.”
Marc Intrater, US Market Leader, SPIN AnalyticsPreviously Managing Director in Oliver Wyman, Head of Model Validation at Standard Chartered and Managing Director, Bank of America.  

“Our experience working with banks around the world,  has confirmed both the need and the opportunity to dramatically accelerate credit risk modelling, which our RISKROBOT software has demonstrated is now possible combining Explainable AI with expert judgment. We are riding the wave of innovation in Regulatory Credit Risk Modeling and Banks are joining our business trip as they want to control their destiny in scaling their teams and market share.”
Panos Skliamis, CEO and Co-Founder, SPIN Analytics

“The consensus from the roundtable is clear – credit risk modelling is on the threshold of a paradigm shift through the use of AI and other technologies to industrialize data preparation and management, and to take advantage of data sharing technology, allowing banks to leverage their scarce and stretched expert resources to operate in a much more dynamic and fulfilling model-building environment”
Andrew Stott, Senior Advisor, SPIN Analytics and formerly Head of Western Europe for Oliver Wyman and board member at BBVA

“The DIT is pleased to have organized this roundtable and to support UK fintechs like SPIN Analytics. We are especially pleased that SPIN Analytics and two other UK fintechs were selected by the Partnership Fund of New York for this year’s Fintech Innovation Lab.”

Frances Moffett-Kouadio FICE, Director Exports North America, UK Department for International Trade

The Department for International Trade (DIT) is a United Kingdom government department responsible for striking and extending trade agreements between the United Kingdom and foreign countries, as well as for encouraging foreign investment and export trade.

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