DATA DRIVEN & PREDICTIVE RISK MANAGEMENT
FOR THE REAL ESTATE INDUSTRY
RISK ALGORITHMS FOR
STRATEGIC DECISION MAKING
Uncovering risk clusters in your markets
how does it work?
QUANTITATIVE ANALYTICS AND
EARLY RISK DETECTION SYSTEM
(RE)IDENTIFYING KEY RISKS IN YOUR MARKETS
UNCOVERING HIDDEN FINANCIAL RISKS
COMBINING MARKETS AND PORTFOLIO DATA
changing the way you do financial risk management
MID-LONG TERM PREDICTIVE ANALYTICS
SHORT TERM PREDICTIVE ANALYTICS
IN DEPTH PORTFOLIO&
MARKET RISK ANALYTICS
automatised data extraction ( data warehouses, excel lists...)
easy re-adjustments and changes
24/7 access for all of the team members
SaaS, API or CORPORATE SOLUTION
1 TECH SOLUTION
2 POWER ALGORITHMS
3 CRUCIAL STEPS
ANALYSING BASIC FINANCIAL RISKS
1. Strategic planning
Together we analyse the basic risk challenges company is facing in the subject markets, marking down markets specifics as well as the strategic goals in mind.
2. Market Risk Radar
Using stochastic modelling and network analytics, we focus on your market interests and uncover hidden connections between market parameters, local and global markets identifying correlations and risk clusters.
3. Digital Portfolio Risk Twin
Results of market analytics are combined with the portfolio in order to offer 24/7 real time and predictive risk&performance insights and enable early risks detection.
Need help with analysing your risk challenges?
We are consulting you about the optimal risk inputs to include into your risk solution
and overcome all of the operational and legal challenges
you might have.
MEET THE FOUNDERS
Combining decades of Real Estate & Financing experience with advanced statistical modelling and ML programming expertise and advising on optimal advanced risk tools for your company
HIGH TECH TOOL MADE BY RISK & REAL ESTATE EXPERTS
The team combines over three decades of experience in Financing & Real estate industry with latest data science developments, while answering to legal and operational challenges connected with introducing effective tech solutions.