AI-Driven Business Continuity and Disaster Recovery in Financial Services: Minimizing Downtime through Predictive Intelligence and Autonomous Response Systems

In today's increasingly digitized financial environment, even moments of downtime can translate into serious financial losses, regulatory fines, and long-term reputational harm. As institutions become increasingly interconnected and dependent on digital infrastructure, traditional business continuity and disaster recovery processes—often manual, static, and reactive—are insufficient. This article shows how artificial intelligence (AI) is redefining resilience for financial institutions. From early anomaly detection on systems to autonomous decision-making during disasters, AI technologies bring new speeds, new accuracies, and new adaptabilities. The article also provides a practical, step-by-step guide for adopting AI-powered continuity strategies, including predictive analytics, automatic orchestration, and cognitive risk interpretation. It also touches on key performance indicators and why aligning with shifting regulatory expectations is important. For financial institutions looking to keep disruption to a minimum and construct future-proof continuity programs, AI is no longer merely a technological advantage—it's an operational imperative.

Authors

Institutions

Publication Details

Journal
Journal of Business and Management Studies
Published
2025-10-07
DOI
https://doi.org/10.32996/jbms.2025.7.6.2
Primary Topic
Insurance and Financial Risk Management
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

AI-Driven Business Continuity and Disaster Recovery in Financial Services: Minimizing Downtime through Predictive Intelligence and Autonomous Response Systems

Ramachander rao Thallada
Journal of Business and Management Studies
Insurance and Financial Risk Management
article

AI-Driven Business Continuity and Disaster Recovery in Financial Services: Minimizing Downtime through Predictive Intelligence and Autonomous Response Systems

Ramachander rao Thallada
article en

Abstract

In today's increasingly digitized financial environment, even moments of downtime can translate into serious financial losses, regulatory fines, and long-term reputational harm. As institutions become increasingly interconnected and dependent on digital infrastructure, traditional business continuity and disaster recovery processes—often manual, static, and reactive—are insufficient. This article shows how artificial intelligence (AI) is redefining resilience for financial institutions. From early anomaly detection on systems to autonomous decision-making during disasters, AI technologies bring new speeds, new accuracies, and new adaptabilities. The article also provides a practical, step-by-step guide for adopting AI-powered continuity strategies, including predictive analytics, automatic orchestration, and cognitive risk interpretation. It also touches on key performance indicators and why aligning with shifting regulatory expectations is important. For financial institutions looking to keep disruption to a minimum and construct future-proof continuity programs, AI is no longer merely a technological advantage—it's an operational imperative.

Journal of Business and Management StudiesVol. 7(6)
Ontario Council of University Libraries (CA)
Openalex Percentile: Top 63%
Insurance and Financial Risk Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

AI-Driven Business Continuity and Disaster Recovery in Financial Services: Minimizing Downtime through Predictive Intelligence and Autonomous Response Systems — Ramachander rao Thallada · Journal of Business and Management Studies (2025) | TGRS Research Map | TGRS