Webster Bank Creates Data-Driven Risk Index to Monitor $1.3B in Retail Real Estate
Webster Bank revolutionized risk assessment for its $1.3 billion retail real estate portfolio by creating a Mobility Composite Score (MCS) using Placer.ai data, enabling real-time monitoring and proactive decision-making.
The Challenge
Webster Bank, a commercial bank in the Northeast, needed a systematic way to evaluate and monitor credit risk on $1.3 billion in retail real estate loans. Traditional metrics like debt service coverage ratio (DSCR) and loan-to-value (LTV) lacked real-time insight into evolving property trends.
The Outcome
Using Placer data, Webster Bank created a “Mobility Composite Score” (MCS), to assess property risk by tracking real-time visits and submarket rankings. The score is now part of Webster Bank’s internal risk reviews, acting as an early indicator of potential issues.
Traditional credit metrics like DSCR and LTV only tell part of the story. With Placer data we can track foot traffic in near real-time, giving us a forward-looking view of property performance. This tool is a game-changer for our credit analytics team and our internal bank partners."
