メインコンテンツに移動

Banks tout machine learning amid regulatory concerns

Machine learning being used to build challenger models for model validation

surveillance-robot
Risk managers are getting comfortable with machine learning

Banks are doubling down on the use of machine learning techniques for model validation in the face of regulatory scepticism over ‘black box’ models.

Machine learning has allowed banks to slash the amount of time and resources they dedicate to complying with SR 11-7, the model risk management framework issued by US prudential regulators in 2011.

The guidance ushered in a stricter era of model

コンテンツを印刷またはコピーできるのは、有料の購読契約を結んでいるユーザー、または法人購読契約の一員であるユーザーのみです。

これらのオプションやその他の購読特典を利用するには、info@risk.net にお問い合わせいただくか、こちらの購読オプションをご覧ください: http://subscriptions.risk.net/subscribe

現在、このコンテンツをコピーすることはできません。詳しくはinfo@risk.netまでお問い合わせください。

Sorry, our subscription options are not loading right now

Please try again later. Get in touch with our customer services team if this issue persists.

New to Risk.net? View our subscription options

無料メンバーシップの内容をお知りになりたいですか?ここをクリック

パスワードを表示
パスワードを非表示にする

Most read articles loading...

You need to sign in to use this feature. If you don’t have a Risk.net account, please register for a trial.

ログイン
You are currently on corporate access.

To use this feature you will need an individual account. If you have one already please sign in.

Sign in.

Alternatively you can request an individual account here