, “ interagency statement on the use of alternative data in credit underwriting, ” https : / / www. federalreserve. gov / supervisionreg / caletters / ca % 201911 % 20letter % 20attachement % 20interagency % 20statement % 20on % 20the % 20use % 20of % 20alternative % 20data % 20in % 20credit % 20underwriting. pdf. kenneth p. brevoort, philipp grimm, and michelle kambara, data point : credit invisibles ( washington : consumer financial protection bureau, may 2015 ), https : / / files. consumerfinance. gov / f / 201505 _ cfpb _ data - pointcredit - invisibles. pdf. federal advisory council, which includes a range of banking institutions from across the country, recently noted that nontraditional data and the application of ai have the potential “ to improve the accuracy and fairness of credit decisions while also improving overall credit availability. ” 8 to harness the promise of machine learning to expand access to credit, especially to underserved consumers and businesses that may lack traditional credit histories, it is important to be keenly alert to potential risks around bias and inequitable outcomes. for example, if ai models are built on historical data that reflect racial bias or are optimized to replicate past decisions that may reflect bias, the models may amplify rather than ameliorate racial gaps in access to credit. along those same lines, the opaque and complex data interactions relied upon by ai could result in discrimination by race, or even lead to digital redlining, if not intentionally designed to address this risk. it is our collective responsibility to ensure that as we innovate, we build appropriate guardrails and protections to prevent such bias and ensure that ai is designed to promote equitable outcomes. as rayid ghani notes, “ … [ a ] ny ai ( or otherwise developed ) system that is affecting people ’ s lives has to be explicitly built to focus on increasing equity and not just optimizing for efficiency … [ w ] e need to make sure that we put guidelines in place to maximize the chances of the positive impact while protecting people who have been traditionally marginalized in society and may be affected negatively by the new ai systems. ” 9 federal advisory council ( fac ) record of meeting, ( december 3, 2020 ), https : / / www

for a new lease by a new tenant. data are through december 2023 for corelogic, january 2024 for pce, and february 2024 for realpage and zillow. the gray shaded bar indicates a period of business recession as defined by the national bureau of economic research. the shaded recession period extends from february 2020 through april 2020. source : bureau of economic analysis, personal consumption expenditures price index via haver analytics ; corelogic, inc. ; realpage, inc. ; zillow, inc. note : data extend through march 18, 2024. the data are at a business - day frequency and are estimated from smoothed nominal and inflation - indexed treasury yield curves. the gray shaded bar indicates a period of business recession as defined by the national bureau of economic research. the shaded recession period extends from february 2020 through april 2020. source : federal reserve bank of new york ; federal reserve board staff calculations. note : data extend through february 2024. the gray shaded bars indicate periods of business recession as defined by the national bureau of economic research. the shaded recession periods extend from december 2007 through june 2009 and from february 2020 through april 2020. source : bureau of labor statistics via haver analytics. note : data extend through february 2024. the labor force participation rate is a percentage of the relevant population. data are monthly, and values before january 2023 are estimated by federal reserve board staff in order to eliminate discontinuities in the published history. the gray shaded bars indicate periods of business recession as defined by the national bureau of economic research. the shaded recession periods extend from december 2007 through june 2009 and from february 2020 through april 2020. source : bureau of labor statistics via haver analytics ; u. s. census bureau ; federal reserve board staff calculations. note : data extend through january 2024 for available jobs and february 2024 for available workers. available jobs are employment plus job openings as of the end of the previous month. available workers are the labor force. data for employment and labor force before january 2023 are estimated by federal reserve board staff in order to eliminate discontinuities in the published history. the gray shaded bars indicate periods of business recession as defined by the national bureau of economic research. the shaded recession periods extend from december 2007 through june 2009 and from february 2020 through april 2020. source : bureau of labor statistics via haver analytics ; u. s. census bureau ; federal reserve board staff calculations. note : data extend through january 2024