---
title: Using External Coefficients to Enhance Model Accuracy for Fintech Companies
description: In this article we will go over what is coefficient, which coefficients are suitable for Fintech companies and their impact on the models.
---

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# Using External Coefficients to Enhance Model Accuracy for Fintech Companies

## 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](https://knowledgebase.incrmntal.com/knowledge/making-results-more-accurate-by-including-coefficients?hsLang=en).

#### **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.

 

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