In this article we will go over what is coefficient, which coefficients are suitable for Fintech companies and their impact on the models.
Fintech products (whether trading apps, neobanks, crypto platforms, or investment services) operate in markets where user behavior is heavily influenced by external financial signals. Market volatility, stock index trends, crypto swings, and macro-economic changes can meaningfully shift performance, even when no marketing actions occur.
INCRMNTAL’s models are already designed to separate marketing-driven results from natural market movement. However, when additional context is available, you can enrich the model with coefficients, external real-world variables that help explain fluctuations not caused by paid activity.
This makes the insights even more precise, stable, and reflective of true market conditions.
What Are Coefficients?
Coefficients are external features added to INCRMNTAL’s models to provide contextual signals that improve accuracy.
They help the model better understand:
- Which changes were influenced by marketing
- Which changes were driven by market forces, sentiment, or broader economic conditions
The core model works well without coefficients. However, by adding external signals—especially for fintech companies where user behavior is tightly connected to financial markets—you can make the results even more stable and reliable, particularly during volatile periods.
You can read more about coefficient also here.
Why Fintech Models Benefit From Coefficients
Fintech KPIs (registrations, verifications, trades, deposits, loan applications, top-ups, etc.) often respond to:
- Stock market rallies or corrections
- Crypto volatility
- Interest rate decisions
- Economic reports
- etc
The model already detects and adjusts for natural variation, but when strong external movements occur, coefficients provide additional visibility that helps the model:
- Understand the drivers behind sudden surges or dips
- Increase the precision of marginal and contribution values
- Provide clearer explanations for unexpected changes
Strengthen confidence in the decision-making process
Fintech-Relevant Coefficients You Can Include
In INCRMNTAL for most FinTech clients we use coefficients commonly used for fintech models, including the stock, index, and crypto-related indicators.
1. Stock Market Indicators
Because trading and investing activity is sensitive to stock movement, INCRMNTAL can ingest several stock-based indicators derived from top stocks (selected by market cap and trading volume):
-
MACD_mean_30d
A smoothed 30-day Moving Average Convergence/Divergence metric capturing market momentum.
-
Market_cap_mean7d
Seven-day smoothed average market capitalization of leading stocks or indices.
-
Max_daily_diff7d_stocks
Smoothed 7-day high–low price difference, reflecting market volatility.
-
ReturnEMA_30d
A smoothed 30-day return indicator.
-
Volume_mean7d
Seven-day smoothed trading volume metric.
These indicators help the model interpret peaks or drops in trading activity more precisely.
2. Stock Market Indices
Indices capture broad market movement and investor sentiment.
These may include:
- S&P 500
- NASDAQ
- Dow Jones
- FTSE 100
- CAC 40
- DAX
- Nikkei 225
- Local country-specific indices etc
Index fluctuations often influence app logins, deposits, trading volume, and new account creation. Adding them helps the model adjust more effectively during global or regional market events.
3. Crypto Market Indicators
Crypto markets can influence fintech usage even for apps not offering crypto through changes in risk appetite and user engagement.
Available coefficients include:
- crypto_symbol_daily_max_diff
Daily (high − low) price difference across major crypto assets, indicating volatility.
- crypto_symbol_daily_diff
Daily (close − open) price movement across assets.
Including crypto metrics helps the model interpret spikes in trading, deposits, or session volume caused by global crypto movements.
How INCRMNTAL Uses Coefficients
All coefficients act as external explanatory variables providing contextual information.
The model uses them to:
1. Add clarity on performance changes not driven by marketing
This helps distinguish between market-driven fluctuations and genuine marketing impact.
2. Make the baseline even more stable
The model already handles variability—coefficients simply enhance its understanding during unusual market periods.
3. Improve the precision of marginal and contribution values
Especially helpful for fintech companies operating in highly volatile markets.
4. Increase interpretability and confidence
Providing a clearer narrative behind unexpected movements in results.
Summary
INCRMNTAL’s core models are already built to identify the true incremental effect of marketing.
For fintech companies where user behavior is strongly influenced by financial markets. Adding coefficients provides an additional layer of context that makes the result.
By integrating stock indicators, indices, crypto metrics, macro-economic data, and regulatory or sentiment signals, fintech companies can achieve the most complete and reliable view of their incremental performance.
If you would like to explore additional coefficient options—whether the ones mentioned above or other external signals relevant to your business—please reach out to your INCRMNTAL Customer Success Manager, who can advise on availability, suitability, and next steps.
For any question please contact support@incrmntal.com , or open a support Ticket here